# **WHY AND HOW IS THE SELF RELATED TO THE BRAIN MIDLINE REGIONS?**

**Topic Editors Pengmin Qin, Niall W. Duncan and Georg Northoff**

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**ISSN** 1664-8714 **ISBN** 978-2-88919-265-6 **DOI** 10.3389/978-2-88919-265-6

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# **WHY AND HOW IS THE SELF RELATED TO THE BRAIN MIDLINE REGIONS?**

Topic Editors:

**Pengmin Qin,** University of Ottawa, Canada **Niall W. Duncan,** University of Ottawa, Canada **Georg Northoff,** University of Ottawa, Canada

The contrast of self vs other related activity, as shown by a meta-analysis by Araujo et al. (2013) from this ebook.

Araujo HF, Kaplan J and Damasio A (2013) Cortical midline structures and autobiographicalself processes: an activation-likelihood estimation meta-analysis. *Front. Hum. Neurosci*. 7:548. doi: 10.3389/fnhum.2013.00548

What the self is and where it comes from has been one of the great problems of philosophy for thousands of years. As science and medicine have progressed this question has moved to also become a central one in psychology, psychiatry, and neuroscience. The advent of in vivo brain imaging has now allowed the scientific investigation of the self to progress further than ever.

Many such imaging studies have indicated that brain structures along the cortical midline are particularly closely related to self-specific processing. This association between cortical midline structures (CMS) and self is reinforced by the involvement of these regions in other self-oriented processes, such as mind-wandering or stimulus valuation. Those midline regions involved in self- processing also overlap

with another network, the default mode network, which shows high brain activity during the so-called resting state, indicating that there may be a special relationship between selfprocessing and intrinsic activity.

Although such promising groundwork linking the self and CMS has been carried out, many questions remain. These include: what features of the midline regions lead to their apparent importance in self-processing? How can we appropriately account for confounding factors such as familiarity or task-effects in our experiments? How is the self-related to other features of the mind, such as consciousness? How is our methodology influencing our attempts to link the self and the brain?

The purpose of this ebook is to address some of these questions, including opinions, perspectives, and hypotheses about the concept of the self, the relationship between CMS and the self, and the specific function of these brain regions in self-processing. It also includes original research papers describing EEG, fMRI, and behavioral experiments investigating different aspects of the self.

# Table of Contents


*128 The Degree of Early Life Stress Predicts Decreased Medial Prefrontal Activations and the Shift From Internally to Externally Guided Decision Making: An Exploratory Nirs Study During Resting State and Self-Oriented Task* 

Takashi Nakao, Tomoya Matsumoto, Machiko Morita, Daisuke Shimizu, Shinpei Yoshimura, Georg Northoff, Shigeru Morinobu, Yasumasa Okamoto and Shigeto Yamawaki


Ayna Baladi Nejad, Philippe Fossati and Cédric Lemogne


Joseph M. Moran, William M. Kelley and Todd F. Heatherton

*185 Associative Account of Self-Cognition: Extended Forward Model and Multi-Layer Structure* 

Motoaki Sugiura

*201 A Pattern Theory of Self*  Shaun Gallagher

# Why and how is the self-related to the brain midline regions?

# **Pengmin Qin\*, Niall Duncan and Georg Northoff**

Mind, Brain Imaging and Neuroethics, University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada \*Correspondence: pengmin.qin@theroyal.ca

**Edited by:**

Hauke R. Heekeren, Freie Universität Berlin, Germany

**Keywords: self, cortical midline structure, resting state, patients with disorders of consciousness, mental disorders**

What the self is and where it comes from has been one of the great problems of philosophy for thousands of years. As science and medicine have progressed this question has moved to also become a central one in psychology, psychiatry, and neuroscience. The advent of *in vivo* brain imaging has now allowed the scientific investigation of the self to progress further than ever.

Many such imaging studies have indicated that brain structures along the cortical midline are particularly closely related to self-specific processing. This association between cortical midline structures (CMS) and self is reinforced by the involvement of these regions in other self-oriented processes, such as mind-wandering or stimulus valuation. Those midline regions involved in selfprocessing also overlap with another network, the default mode network, which shows high brain activity during the so-called resting state, indicating that there may be a special relationship between self-processing and intrinsic activity.

Although such promising groundwork linking the self and CMS has been carried out, many questions remain. These include: what features of the midline regions lead to their apparent importance in self-processing? How can we appropriately account for confounding factors such as familiarity or task-effects in our experiments? How is the self-related to other features of the mind, such as consciousness? How is our methodology influencing our attempts to link the self and the brain?

The purpose of this ebook is to address some of these questions, including opinions, perspectives, and hypotheses about the concept of the self, the relationship between CMS and the self, and the specific function of these brain regions in self-processing. It also includes original research papers describing EEG, fMRI, and behavioral experiments investigating different aspects of the self.

The included papers can be roughly divided into four groups as follows: the first group of papers both collate existing evidence that midline structures are involved in self-processing and produce evidence for new facets of it. Reviewing the literature,Knyazev (2013) provides an overview of existing EEG studies of self-related activity, highlighting an overlap between self-related activity and rest, as well as the apparent importance of the P300 ERP and alpha activity in self-processing. Similarly, Araujo et al. (2013) present a meta-analysis of imaging studies that associates the medial prefrontal cortex (mPFC) with self-traits, in contrast to posterior regions which are more associated with the traits of others. In an fMRI study, Qin et al. (2013) show that self-related stimuli interact differently with intrinsic activity in the auditory cortex than do

non-self-related. This finding provides backing for the hypotheses that self and intrinsic activity are particularly related. Looking at how self-trait priming affects task-performance, Bengtsson and Penny (2013) present experimental results and a Bayesian computation model for the effects observed. Finally, Colton et al. (2013) use fMRI to show that age-related trait stimuli activate midline regions and that this interacts with subject age, highlighting the importance of contextual information for self-related processing.

The second group of papers describes existing evidence for the different functions of the separate midline regions. Focusing on the mPFC, both D'Argembeau (2013) andAbraham (2013) discuss this region's role in the assignment of personal value or significance to self-related stimuli. Switching to the posterior midline regions, Brewer et al. (2013) review the literature relating to the role of the posterior cingulate cortex (PCC). They use this to present the idea that the PCC may be involved in the experience of being engaged with mental content. The PCC, as part of the DMN, is also discussed, along with mirror neurons, by Molnar-Szakacs and Uddin (2013) in their discussion of the role of CMS in self-relevant and social processing, suggesting a key role for them in embodiment and simulation. Also considering the role of midline regions in social cognition, Flagan and Beer (2013) discuss the mPFC and the social self, describing how different sub-regions may be involved in different aspects of self-evaluation.

Alterations of self are seen in many mental disorders, as well as in disorders of consciousness (DOC) – the focus of the third group. Crone et al. (2013) present an fMRI study of the response to self/other names in CMS of patients with DOC, adding to the literature on self in such conditions, as reviewed here by Demertzi et al. (2013). Early life stress is associated with a higher risk of mental disorders in later life – in a NIRS study Nakao et al. (2013) show that it is also correlated with changes in resting and selfrelated activity in the mPFC, with possible effects on how people make decisions. This finding fits in with many prior ones of a change in midline structure activity in mental disorders, such as depression, autism, or borderline personality disorder, as reviewed here by Zhao et al. (2013) and Nejad et al. (2013).

Finally, the fourth group provides analysis of the different concepts involved in the study of the self and discusses how these can be related to the brain. This is important for good experimental design and interpretation. This point is made by Sandrone (2013) in their perspective paper, suggesting also that a consideration of the mirror neuron system is also needed. Also important is how we interpret the term "self," a point made by Musholt (2013), who differentiates being a subject of conscious experience and being aware of oneself as such. Considering different relationships between midline regions and the self, Moran et al. (2013) puts forward three different aspects – thinking about people, binding stimuli, and directing thought – and discuss how these may be related to the mPFC. Finally models of how we may think about the self are presented by Sugiura (2013), advocating a forward processing model for considering different aspects of the self, and Gallagher (2013), who presents a concept of the self that sees it as an altering pattern of properties.

In summary, this ebook presents recent findings about the relationship between CMS and self-processing, and provides novel hypotheses and interpretations of these findings. Simultaneously, the "blind-spots" of current research, as well as new ideas about self-processing, are mentioned. Together, these papers may throw light on new directions for investigating the self.

# **REFERENCES**


*Received: 01 November 2013; accepted: 12 December 2013; published online: 25 December 2013.*

*Citation: Qin P, Duncan N and Northoff G (2013) Why and how is the self-related to the brain midline regions? Front. Hum. Neurosci. 7:909. doi: 10.3389/fnhum.2013.00909*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Qin, Duncan and Northoff. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# EEG correlates of self-referential processing

# **Gennady G. Knyazev \***

Institute of Physiology, Siberian Branch of Russian Academy of Medical Sciences, Novosibirsk, Russia

#### **Edited by:**

Georg Northoff, University of Ottawa, Canada

#### **Reviewed by:**

Alexander Fingelkurts, BM-Science Brain and Mind Technologies Research Centre, Finland Andrew Fingelkurts, BM-Science Brain and Mind Technologies Research Centre, Finland Rex Cannon, University of Tennessee, USA

#### **\*Correspondence:**

Gennady G. Knyazev, Institute of Physiology, Siberian Branch of Russian Academy of Medical Sciences, Timakova Street 4, Novosibirsk 630117, Russia e-mail: knyazev@physiol.ru

Self-referential processing has been principally investigated using functional magnetic resonance imaging (fMRI). However, understanding of the brain functioning is not possible without careful comparison of the evidence coming from different methodological domains. This paper aims to review electroencephalographic (EEG) studies of self-referential processing and to evaluate how they correspond, complement, or contradict the existing fMRI evidence. There are potentially two approaches to the study of EEG correlates of self-referential processing. Firstly, because simultaneous registration of EEG and fMRI has become possible, the degree of overlap between these two signals in brain regions related to self-referential processing could be determined. Second and more direct approach would be the study of EEG correlates of self-referential processing per se. In this review, I discuss studies, which employed both these approaches and show that in line with fMRI evidence, EEG correlates of self-referential processing are most frequently found in brain regions overlapping with the default network, particularly in the medial prefrontal cortex. In the time domain, the discrimination of self- and others-related information is mostly associated with the P300 ERP component, but sometimes is observed even earlier. In the frequency domain, different frequency oscillations have been shown to contribute to self-referential processing, with spontaneous self-referential mentation being mostly associated with the alpha frequency band.

**Keywords: self-referential processing, default mode network, EEG, ERP, oscillations**

Self-referential processing has been principally investigated using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), which currently dominate the field of human neuroscience. Electroencephalographic (EEG) studies are less numerous and, to the best of my knowledge, have not been systematically reviewed. Understanding of the brain functioning is not possible without careful comparison of the evidence coming from different methodological domains. Ideally, different methods are expected to complement each other. For example, excellent spatial resolution of fMRI could be complemented by excellent temporal resolution of EEG. In reality, however, different methods may give contradicting results. In such a case, a careful analysis of possible causes of the discrepancy is necessary. In this paper, I aimed to review EEG studies of self-referential processing and to evaluate how they correspond, complement, or contradict to the existing fMRI evidence. It is important to keep in mind that fMRI and EEG represent different aspects of brain activity and there may be a degree of incongruence between hemodynamic and electrophysiological signals. The relationship between EEG signal and concurrent changes in neuronal spiking and local field potentials are relatively well understood (e.g., Buzsaki and Draguhn, 2004; Basar, 2008). On the other hand, it is not yet clear how the changes in the blood oxygen level dependent (BOLD) signal relate to concurrent changes in neuronal events (Huettel et al., 2004; Debener et al., 2006). The quest to elucidate how the self is processed in the brain requires a solid understanding of the link between neuroimaging findings and their electrophysiological underpinnings.

Reliability and validity of a particular method is also a very important issue. Reliability is the cornerstone of any scientific enterprise. If a measurement is unreliable, it cannot be valid. However, if a method is reliable it can also be invalid (Carmines and Zeller, 1979). In this review, it is not possible to cover the issue of reliability and validity of EEG and fMRI methods in detail (for recent reviews, see e.g., Bennett and Miller, 2010; Thatcher, 2010). High levels of reliability (i.e., >0.95) of several quantitative EEG measures have been shown in many studies (e.g., Lund et al., 1995; McEvoy et al., 2000; Corsi-Cabrera et al., 2007; Gudmundsson et al., 2007; Näpflin et al., 2008; Towers and Allen, 2009; Schmidt et al., 2012). Somewhat smaller reliabilities are usually found for event-related potential (ERP) components. Thus, test-retest correlation coefficients for oddball task P300 amplitude range from 0.50 to 0.80 and for peak latency from 0.40 to 0.70 (Polich, 1986; Fabiani et al., 1987; Segalowitz and Barnes, 1993; Walhovd and Fjell, 2002). Hall et al. (2006) found higher testretest reliability for the P300 amplitude (0.86) and latency (0.88). Less evidence exists regarding reliability of fMRI measures. Vul et al. (2009), summarizing several studies, conclude that fMRI measures computed at the voxel level will not often have reliabilities greater than about 0.7. Lieberman et al. (2009) argued that fMRI reliability was likely around 0.90. Friedman et al. (2008) show that for median percent signal change measure, the median test-retest reliability was 0.76. Aron et al. (2006) found 1-year test-retest fMRI reliability in a classification-learning task exceeding 0.8. Similar test-retest reliability of fMRI activation during prosaccades and antisaccades at the group level was shown by

Raemaekers et al. (2007). However, these authors showed that reliable results could be obtained in some but not all subjects, mostly due to individual differences in the global temporal signal to noise ratio (SNR). Comprehensive discussion of the reliability of fMRI and effects of SNR could be found in Bennett and Miller (2010). Thus, it could be summarized that test-retest reliability, at least for some EEG measures, tends to be excellent and is at the border between good and excellent for most fMRI studies.

# **SELF-REFERENTIAL PROCESSING AND THE DEFAULT MODE NETWORK**

The concept of the default mode network (DMN) was first introduced by Raichle et al. (2001) basing on the evidence showing a consistent pattern of deactivation across a network of brain regions that occurs during the initiation of task-related activity (Raichle et al., 2001; Raichle and Snyder, 2007). The DMN includes the precuneus/posterior cingulate cortex (p/PCC), the medial prefrontal cortex (MPFC), and medial, lateral, and inferior parietal cortex. This network is active in the resting brain with a high degree of functional connectivity (FC) between regions. The more demanding the task the stronger the deactivation appears to be (McKiernan et al., 2006; Singh and Fawcett, 2008). A notable exception to this general pattern of deactivation during goal-directed activity occurs in relation to tasks requiring selfreferential thought and social cognition (Mitchell, 2006; Gobbini et al., 2007), which suggests that the DMN likely mediates active cognitive processes rather than being strictly a "default" network, which only shows inactivation. Recent studies show that these processes include first-person perspective (Greicius et al., 2003; Vogeley et al., 2004), task-independent thoughts (Binder et al., 1999; McKiernan et al., 2003), episodic memory (Greicius and Menon, 2004), social cognition and sense of agency processes (Decety and Sommerville, 2003; Gallagher and Frith, 2003), distinction between self- and non-self-related stimuli (see Northoff et al., 2006; Buckner et al., 2008; for a review), and social interaction tasks (Rilling et al., 2004, 2008). All this evidence implies that the DMN appears to be the seat of self-referential processing in the brain.

#### **APPROACHES TO THE STUDY OF EEG CORRELATES OF SELF-REFERENTIAL PROCESSES**

Electroencephalogram and fMRI represent different aspects of brain activity. Moreover, different EEG measures may also relate to different aspects of neuronal activity and show little or no correlation with each other. Therefore, a brief description of most popular measures that are used in EEG domain seems necessary for clearer understanding of later discussed studies. Firstly, EEG measures could be obtained in a resting condition or during performance of different tasks or presentation of different stimuli. In the former case they represent "spontaneous" or ongoing electrical activity and could be used to investigate EEG correlates of spontaneous self-referential processes, such as mind wondering and task-unrelated-thoughts. In the latter case, different measures of event-related changes in electrical activity, such as ERP and eventrelated oscillations, are used to study the processing of external self-related information.

Event-related potential is a powerful and very popular tool for the study of cortical dynamics that are phase-locked to (mostly) external stimuli and events. By calculating the mean of EEG epochs, the activity phase-locked to the stimulus is preserved, whereas non-phase-locked activity cancels itself out. It should be borne in mind that ERP is not the only kind of electrical cortical responses. A portion of these responses is time-locked to the stimulus, but is not temporally synchronized with it, meaning that this activity will cancel itself out during averaging. This kind of responses is usually labeled induced responses, as distinct from evoked responses that are phase-locked to the stimulus. There has been a long debate about how ERPs are related to ongoing oscillations and induced responses (e.g., Kolev and Yordanova, 1997; Makeig et al., 2002; Jansen et al., 2003; Klimesch et al., 2004). Most researchers agree that evoked and induced responses represent different aspects of brain function. Much evidence shows that evoked responses (e.g., different ERP components) are involved in stimulus perception and processing, that is, bottom-up processes. Induced responses, on the other hand, do not probably directly participate in stimulus perception and processing. However, they are involved in concomitant top-down processes, such as allocation of attention, memory retrieval, decision-making, and emotion. Linking evoked responses with bottom-up and induced responses with top-down processes is consistent with the theoretical framework suggested by David et al. (2006) who associate evoked and induced responses with "drivers" and "modulators," respectively. The mechanisms of action of drivers refer to classical neuronal transmission, either biochemical or electrical. Modulatory effects can engage a complex cascade of highly non-linear cellular mechanisms (David et al., 2006).

Oscillations are the most salient feature of EEG. They could be studied both in rest and during processing of external stimuli or tasks. Ongoing and event-related oscillations are usually categorized into five frequency bands: delta (0.5–3.5 Hz), theta (4–7 Hz), alpha (8–12 Hz), beta (13–30 Hz), and gamma (>30 Hz), although there is generally a lack of consistency between studies with maintaining a standard range of EEG bands. The five major bands are frequently subdivided into narrower sub-bands and there is no general agreement as to the boundaries of these sub-bands. This is a potential source of discrepancies in results of different studies. It was also suggested that there are substantial individual differences in EEG frequency band boundaries and they should be individually adjusted using alpha peak frequency as the anchor (Klimesch, 1999). These debates have partly lost their actuality due to the advent of modern methods of time-frequency representation, such as wavelet transform, and adoption of mass-univariate statistical approaches (e.g., Delorme and Makeig, 2004).

It is increasingly becoming clear that oscillations may have a special and very important role in the integration of brain functions (Nunez, 2000; Varela et al., 2001; Cantero and Atienza, 2005; Palva et al., 2005; Knyazev, 2007; Basar, 2008; Fingelkurts and Fingelkurts, 2010). Two different aspects of EEG oscillations could be potentially measured: the power of a particular oscillation at different cortical locations and its synchrony (i.e., phase consistency) over these locations. The former is usually measured by means of different time-frequency transforms, such as Fourier or wavelet transform, the latter by means of coherence or similar measures. To

evaluate event-related changes in oscillatory activity EEG is usually recorded before (the baseline) and during (the test period) presentation of stimuli or performance of a task; EEG changes in the test period relative to baseline are treated as"event-related"activity and are believed to reflect brain activation involved in the processing of the task in hand. Event-related oscillations are subdivided into evoked (phase-locked to the stimulus) and induced (non-phaselocked to the stimulus) parts, the latter usually being much larger in amplitude than the former. According to the currently most popular theory, the former oscillations are the building blocks of the ERP (e.g., Makeig et al., 2002; Klimesch et al., 2004). Beyond ERPs and oscillations, the global"microstates"(i.e., quasistable and unique topographic distributions of the whole-cortex electrical field potential, Lehmann, 1990) and local "microstates" (i.e., quasistable states within individual cortex locations, Fingelkurts and Fingelkurts, 2010) could be investigated both in rest and during performance of tasks.

Spatial localization of observed effects is an important and rather complicated issue in EEG research. Scalp EEG samples a volume-conducted, spatially degraded version of the electrical activity, where the potential at any location can be considered a mixture of multiple sources (Makeig et al., 2004). To overcome this limitation, different blind source separation and source reconstruction techniques have been devised. Blind source separation techniques, like independent component analysis (ICA), are increasingly becoming popular both in EEG and in fMRI research, but there are several principal differences in how these techniques are applied in the two domains. In EEG research, temporal ICA (TICA) is usually used, whereas in fMRI research, spatial ICA (SICA) is almost exclusively applied. There are several reasons for this, of which the most important is that the spatial dimension is much larger than the temporal dimension in fMRI data, whereas for EEG data, the temporal dimension is much larger than the number of sources (Calhoun et al., 2001). This methodological difference may impede the direct comparison of EEG and fMRI ICA results. To overcome this obstacle, Knyazev et al. (2011) developed a method, which allows application of SICA to EEG data. A series of simulations showed that both SICA and TICA performed adequately with spatially and temporally independent sources, but SICA outperformed TICA when sources were temporally correlated (Knyazev, 2013b).

The source reconstruction techniques could be roughly divided into two categories: 3D imaging (or distributed) reconstruction methods and equivalent current dipole approaches. The former consider all possible source locations simultaneously, allowing for large and widely spread clusters of activity. The latter rely on a hypothesis that only a few sources are active simultaneously and those sources are focal. It should be emphasized that all EEG source reconstruction methods are probabilistic modeling techniques, which at best point to the most probable location and do not give the "true" localization of sources. Besides, they typically have low spatial resolution. However, it should be kept in mind that fMRI data also represent results of statistical procedures to compare signals between groups or within subjects and do not show the direct structural localization of observed effects.

There potentially are two different approaches to the study of EEG correlates of self-referential processing. Firstly, because simultaneous registration of EEG and fMRI has become possible, the degree of overlap between these two signals in brain regions related to self-referential processing (e.g., the DMN) could be determined. Second and more direct approach would be the study of EEG correlates of self-referential processing *per se*. Below, I will discuss studies, which employed both these approaches and will try to show whether the results correspond, complement, or contradict the existing fMRI framework.

# **EEG CORRELATES OF THE DEFAULT MODE NETWORK**

Because DMN mostly operates in a resting state, many simultaneous EEG-fMRI studies attempted to reveal correlations between spontaneous fluctuations of BOLD and cortical electrical activity in this state. Since oscillations constitute the most salient feature of the spontaneous EEG,many of these studies correlated BOLD with different EEG frequency bands. Alpha oscillations have received most attention because they characterize quiet wakefulness and, like DMN, are inversely related to bottom-up sensory processing (Goldman et al., 2002; Laufs et al., 2003a,b; Moosmann et al., 2003; Goncalves et al., 2006; de Munck et al., 2007, 2008; Tyvaert et al., 2008; Jann et al., 2009, 2010; Sadaghiani et al., 2010). The general pattern that has been revealed in these studies is consistent with the picture in which thalamus shows positively correlated activity, while fronto-parietal and occipital regions exhibit negatively correlated activity. Together with studies reporting reduced attention to the external environment, these correlations suggest a reduction of activity in brain regions associated with externally directed attention and a potential increase in activity in the DMN (Larson-Prior et al., 2011). However, there are significant differences in reported positive alpha-band correlations to elements of the DMN (e.g., Laufs et al., 2003b; Ben-Simon et al., 2008; Jann et al., 2009). Laufs (2008) noted that the failure across studies to identify an average cortical BOLD signal pattern, which is positively correlated with alpha power, may be explained by nonuniform brain activity at the population level during periods of prominent alpha oscillations which fMRI group analysis must fail to detect. Later studies, which used more sophisticated approaches to data analysis, tend to show positive correlations of alpha oscillations with the DMN more frequently. Thus, Mantini et al. (2007) incorporated into their analysis EEG bands between 1 and 50 Hz averaged across the entire scalp and correlated with these bands the fMRI time courses of resting-state networks (RSNs) identified by the use of ICA. The DMN and the dorsal attentional network had strong relationship with alpha and beta rhythms, albeit in opposite directions, with the DMN showing positive whereas the attentional network showing negative correlation with these oscillations. Jann et al. (2010) report on the topographic association of EEG spectral fluctuations and RSNs dynamics using EEG covariance mapping. *T*-mapping of the covariance maps indicated that the strongest effects were again in the alpha and beta bands. DMN activity was found to be associated with increased alpha and beta1 band activity. Brookes et al. (2011b) analyzed magnetoencephalographic (MEG) data using a combination of beamformer spatial filtering and ICA. This method resulted in RSNs with significant similarity in their spatial structure compared with RSNs derived independently using fMRI. In this study, the DMN was identified using MEG data filtered into the alpha band. Wu et al. (2010)

using parallel ICA decompositions of the fMRI data in the spatial domain and of the EEG data in the spectral domain found widespread alpha hemodynamic responses and high functional connectivity (FC) during eyes-closed rest with predominant negative peaks in occipital, temporal, and frontal regions, biphasic responses in the DMN, and a positive peak in the thalamus. Eyesopen resting abolished many of the hemodynamic responses and markedly decreased FC. On the other hand,Mo et al. (2013)found that visual alpha power was positively correlated with DMN only when the eyes were open. This finding has been interpreted as indicating that under the eyes-open condition, strong DMN activity is associated with reduced visual cortical excitability, which serves to block external visual input from interfering with introspective mental processing mediated by DMN, while weak DMN activity is associated with increased visual cortical excitability, which helps to facilitate stimulus processing. Hlinka et al. (2010) showed that DMN's FC correlates positively with relative alpha and beta power. Ros et al. (2013) used neurofeedback to reduce alpha rhythm. Compared to sham-feedback, neurofeedback induced an increase of connectivity within regions of the salience network involved in intrinsic alertness and a decrease of connectivity in the DMN. The change in DMN connectivity was positively correlated with changes in "on task" mind wandering as well as resting-state alpha rhythm. Moreover, both mind wandering and alpha change correlated positively with connectivity in clusters of the precuneus both in the neurofeedback and in the sham group. Besides, for the sham group only, a more extensive positive correlation with restingstate alpha change was observed in a region of the MPFC. Hence, both neurofeedback and sham groups remained consistent with the reports of a positive association between alpha synchronization and DMN connectivity (Mantini et al., 2007; Jann et al., 2009; Hlinka et al., 2010). Meyer et al. (2013) investigated the relationship of ICA-derived RSNs and their correlated electrophysiological signals in eyes-open resting state. In 4 of the 12 subjects, negative alpha correlation with visual RSNs was found, however, due to large inter-subject variability, no significant correlations were found on the group level.

Some investigators correlatedfMRI BOLD signal with measures of EEG synchronization in the alpha frequency band. Jann et al. (2009) show that the BOLD correlates of global EEG synchronization in the alpha frequency are located in brain areas involved in the DMN. Sadaghiani et al. (2010,2012) adapted the phase-locking value to assess fluctuations in synchrony that occur over time in ongoing EEG alpha activity. Fluctuations in global synchrony in the upper alpha band correlated positively with activity in several prefrontal and parietal regions, as measured by fMRI. fMRI intrinsic connectivity analysis confirmed that these regions correspond to the well-known fronto-parietal network which has been consistently shown to be recruited by tasks that involve top-down attentional control processes. This apparent disagreement with the Jann et al.'s (2009) study is explained by the fact that different measures of phase synchrony and a fixed vs. individually determined high alpha range are employed in the two studies implying that results might correspond to functionally different oscillations (Sadaghiani et al., 2012). This latter notion is in line with the framework stating that the scalp-recorded alpha is the end-product of many alpha rhythms that are spatially averaged over the scalp (Basar et al., 1997; Nunez et al., 2001). Thus, Ben-Simon et al. (2008) demonstrated two spatially segregated yet simultaneously active networks associated with alpha rhythm modulations, which they call the induced and the spontaneous. These networks might be related to two endogenous processes of the "resting brain," one, which is tuned outward and is periodic, the other, which is focused inward and is persistent (Ben-Simon et al., 2008). The latter network showed a considerable overlap with the DMN. Two separable alpha-band networks were revealed also in a study by Chen et al. (2013) who employed a four-step analytic approach to the EEG: (1) group ICA to extract independent components; (2) standardized low-resolution tomography analysis (sLORETA) for cortical source localization of IC network nodes; (3) graph theory for FC estimation of epoch-wise IC band power; (4) circumscribing IC similarity measures via hierarchical cluster analysis and multidimensional scaling. During eyes-open compared with eyes-closed condition, graph analyses revealed two salient functional networks with fronto-parietal connectivity: a medial network with nodes in the MPFC/precuneus, which overlaps with the DMN, and a more lateralized network comprising the middle frontal gyrus and inferior parietal lobule. Interestingly, there is a hypothesis that an internal train of thought unrelated to external reality is produced through cooperation between autobiographical information provided by the DMN and the fronto-parietal control network which helps sustain and buffer internal trains of thought against disruption by the external world (Smallwood et al., 2012). This hypothesis explains why activation of the fronto-parietal network and the DMN is often observed together during periods of internally guided thought. If this hypothesis is true, the existence of two separable alpha-band networks associated with the DMN and the fronto-parietal network, respectively, would make functional sense. In any case, the involvement of alpha oscillations in both the top-down attentional control and the integration of internal mental processes are supported by numerous observations (see e.g., Klimesch et al., 2007; Knyazev, 2007 for reviews).

Other EEG frequency bands (most notably theta and gamma) also showed correlations with DMN BOLD signal. Medial frontal theta power changes were negatively correlated with the BOLD response in medial frontal, inferior frontal, p/PCC, inferior parietal, middle temporal cortices, and the cerebellum (Scheeringa et al., 2008). Meltzer et al. (2007) also found that fronto-medial theta most strongly negatively correlates with the MPFC, although negative correlations were also found with other DMN areas such as PCC. In the study by Mizuhara et al. (2004), the frontal midline theta showed negative correlation with BOLD signal over anterior medial regions. The inverse relationship between theta and BOLD in the DMN was also observed in the study by White et al. (2012). There is some evidence that delta, like theta, also shows negative correlation with the DMN. Thus, Hlinka et al. (2010) showed that DMN's FC correlates negatively with relative delta power. In a study by Dimitriadis et al. (2010), delta activity showed a widespread increase in areas overlapping with the DMN during the performance of arithmetic tasks, which are known to cause DMN's deactivation. Since delta and theta are indicated as the primary EEG frequencies in limbic structures (i.e., theta in hippocampus and delta in orbito-frontal cortex, see e.g., Knyazev, 2007, 2012 for review) the negative correlations with the DMN

may be influenced by projections from these structures to midline frontal regions (e.g., Brazier, 1967, 1968, 1969).

Contrary to theta and delta, gamma (30–50 Hz) power shows positive correlations with DMN BOLD signal at rest (Mantini et al., 2007) and decreases during the transition from resting state to an attention task which is interpreted as a correlate of DMN deactivation (Lachaux et al., 2008; Hayden et al., 2009; Jerbi et al., 2010; Berkovich-Ohana et al., 2012). Moreover, slow changes in the power of gamma oscillations make a significant contribution to the spontaneous local fluctuations of resting-state BOLD signals (Nir et al., 2007, 2008; He et al., 2008; Scholvinck et al., 2010) supporting the notion that gamma processing reflects local neural computations (Canolty and Knight, 2010; Siegel et al., 2012). Most interesting data on gamma-correlates of the DMN have been obtained in studies with depth recordings in humans (e.g., Jerbi et al., 2010). However, Wang et al. (2012) have shown that low-frequency oscillations (<20 Hz), and not gamma activity, predominantly contributed to inter-areal BOLD correlations. The low-frequency oscillations also influence local processing by modulating gamma activity within individual areas (Wang et al., 2012).

Basing on PET and fMRI findings of DMN localization and properties, some investigators attempted to derive EEG correlates of the DMN without simultaneous EEG-fMRI recordings. Chen et al. (2008) compared the spatial distribution and spectral power of seven bands of resting-state EEG activity in eyes-closed and eyes-open condition and termed the defined set of regional and frequency specific activity the EEG-DMN. Fingelkurts and Fingelkurts (2011) used measures of "operational synchrony" of alpha oscillations and found a constellation of operationally synchronized cortical areas including two symmetrical occipito-parietotemporal and one frontal spatio-temporal patterns (indexed as DMN) that was persistent across all studied experimental conditions. Interestingly, it was further shown, that such DMN operational synchrony was smallest or even absent in patients in vegetative state, intermediate in patients in minimally conscious state, and highest in healthy fully self-conscious subjects (Fingelkurts et al., 2012). Because fMRI research has shown that functional synchrony across elements of the DMN coheres through brain oscillations at very low frequencies (i.e., 0.1 Hz, Fransson, 2005; Fox et al., 2006), some studies investigated very low EEG frequencies (VLF, Vanhatalo et al., 2004; Helps et al., 2008, 2009, 2010; Broyd et al., 2011). It has been shown that VLF has a temporally stable and distinctive spatial distribution across the scalp with maximal power distributed across frontal midline and posterior regions (Helps et al., 2008, 2010). This scalp network shows deactivation of EEG power following the transition from rest to task (Helps et al., 2009, 2010) and these deactivations are correlated with attention performance (Helps et al., 2010; Broyd et al., 2011). Using sLORETA, the sources of this deactivation were localized to medial prefrontal regions, p/PCC, and temporal regions (Broyd et al., 2011). These results suggest similarities between the DMN as identified by fMRI and the VLF EEG network.

Some authors propose that the neural activity at a specific frequency band is unlikely to constitute the electrophysiological correlate of an RSN. Instead, microstates of the EEG signal have been proposed as potential electrophysiological correlates of spontaneous BOLD activity in the DMN (Britz et al., 2010; Musso et al., 2010; Yuan et al., 2012).

In sum, the study of spontaneous EEG correlates of the DMN appear to suggest that low-frequency EEG oscillations of delta and theta bands predominantly at frontal cortical sites correlate negatively with the DMN, whereas higher frequency oscillations (most notably alpha at parietal and occipital regions) show positive correlations with this network. It should be noted that although alpha, beta, and gamma oscillations show positive correlations with the DMN, specificities of these relationships are not equal for the three bands. It appears that alpha (and possibly slow beta) correlates positively with DMN and negatively with attentional networks whereas gamma shows positive correlations with most cognitive processes including attention (e.g., Muller et al., 2000; Fan et al., 2010; Hipp et al., 2011; Ossandón et al., 2012). Very low EEG frequencies could also be considered as promising candidates, although the functional significance of these oscillations has yet to be determined.

# **EEG STUDIES OF SELF-REFERENTIAL PROCESSING**

All EEG studies of self-referential processing could be subdivided into several categories basing on the nature of EEG phenomena under study and the kind of self-referential processing. Firstly, some studies attempted to correlate spontaneous EEG measures in a resting state with measures of spontaneous self-referential thoughts (e.g., retrospective self-reports). Secondly, EEG correlates of the processing of self-related vs. not self-related external stimuli have been investigated. The latter in turn could be categorized into studies using ERPs or oscillations as the outcome EEG measure. I will describe these three groups of studies separately and will try to summarize how they agree or disagree with each other and the existing fMRI framework.

#### **SPONTANEOUS EEG STUDIES**

There are few resting-state EEG studies, which attempted to correlate spontaneous EEG measures with measures of self-referential thoughts. Cannon and Baldwin (2012) sought to determine whether the current source density levels in the DMN as measured by sLORETA would correspond to other neuroimaging techniques and to understand the subjective mental activity associated with the DMN during baseline recordings and three experimental conditions. Participants completed subjective reports regarding the mental activities employed during baseline recordings. In all frequency bands from delta to beta, the DMN appeared to be preferentially involved in self-relevant, self-specific, or self-perceptive processes. Knyazev et al. (2011) used a combination of ICA and sLORETA source imaging to reveal RSNs in traditional EEG frequency bands. A short self-report scale was used to measure individual differences in the intensity of self-referential thoughts. Only alpha-band spatial patterns simultaneously showed a considerable overlap with the DMN and a positive correlation with the measure of self-referential thoughts. This group of researchers has replicated their findings in large and diverse groups of subjects coming from two different cultures and found culture-related differences in EEG correlates of self-referential thoughts (Knyazev et al.,2012). Specifically, the self-referential thought-related increase of alpha activity prevailed in the posterior DMN hub in Russian, but in the anterior DMN hub in Taiwanese participants. These culturerelated differences could be explained by different self-construal styles that prevail in different cultures (Markus and Kitayama, 1991), but they could be also explained by systematic culturerelated differences in personality (see e.g., Gartstein et al., 2005; Knyazev et al., 2008b for the evidence on persistent differences in temperament and personality across the lifespan between Russian and other cultures). This latter explanation seems particularly feasible in view of the evidence that similar differences in EEG correlates of self-referential thoughts have been found between extraverts and introverts (Knyazev, 2013a) and there is ample evidence that Eastern populations in general and Taiwanese population in particular are lower in Extraversion than most more western populations including Russia (see e.g., Allik and McCrae, 2004). This evidence gives interesting hint about the relationship between EEG correlates of self-referential thoughts and the dopaminergic basis of extraversion (Depue and Collins, 1999). Indeed, it has been shown that the association between extraversion and posterior vs. frontal EEG activity is mediated by dopamine (Wacker et al., 2006; Wacker and Gatt, 2010; Koehler et al., 2011) and there is ample evidence that the posterior and the anterior DMN hubs are differentially susceptible to dopaminergic influences (see Knyazev, 2013a for a review of this evidence).

A number of studies investigated EEG correlates of self-related mental processes during meditation. Lehmann et al. (2001) using LORETA images of the EEG gamma frequency band investigated locations of intra-cerebral source gravity centers and showed that self-induced meditational dissolution and reconstitution of the experience of the self involves the right fronto-temporal area. Travis (2001) compared EEG patterns during transcending (described as "silence and full awareness of pure consciousness, where the experiencer is left all by himself" Mahesh, 1963, p. 288, cited from Travis, 2001) to other experiences during Transcendental Meditation practice. To correlate specific meditation experiences with physiological measures, the experimenter rang a bell three times during the session. Subjects categorized their experiences around each bell ring. Transcending, in comparison to "other" experiences, was marked by higher EEG alpha amplitude at parietal sites and higher alpha coherence between Fz and Pz. Travis et al. (2010) showed that, compared to eyes-closed rest, Transcendental Meditation led to higher alpha1 frontal power and lower beta1 and gamma frontal and parietal power, higher frontal and parietal alpha1 interhemispheric coherence and higher frontal and fronto-central beta2 intra-hemispheric coherence. eLORETA analysis identified sources of alpha1 activity in midline cortical regions that overlapped with the DMN. Travis and Shear (2010) summarized that different meditation techniques are associated with different EEG bands. Focused attention techniques are characterized by beta/gamma activity; open monitoring techniques are characterized by theta activity; and self-transcending is characterized by alpha activity. Lastly, Travis et al. (2004) show that oscillatory activity (spontaneous and task-related) correlates with traitlike psychological characteristics along an object-referral/selfreferral continuum of self-awareness. Specifically, individuals who described themselves in terms of concrete cognitive and behavioral processes (predominantly object-referral mode) exhibited lower alpha and higher gamma power, whereas individuals who

described themselves in terms of an abstract, independent senseof-self underlying thought (predominantly self-referral mode) exhibited higher alpha and lower gamma power.

Default mode network is one among several networks with differentfunctional properties,including thosefor orienting attention (Corbetta et al., 2008) and memory encoding and retrieval (Maguire and Frith, 2004; Habecka et al., 2005; Burianova et al., 2010). Whereas task-specific networks are activated when attention is directed toward relevant stimuli, the DMN increases in activity during rest (Buckner et al., 2008). It is still unknown, however, how the brain switches functionally between default and task-specific networks. One interesting hypothesis is that transient functional organization of neural assemblies is brought about by synchronization of neural oscillations (von Stein et al., 2000;Varela et al., 2001; Ward, 2003). It should be borne in mind however that sometimes synchronization of an oscillation within a network may actually reflect the inhibition of this network (see e.g., Klimesch et al., 2007). Several EEG studies compared synchrony and spectral power measures within the task-specific networks (attention and memory) and the DMN during attention/working memory tasks vs. mind wandering. More power and phase synchronization in theta, alpha, and gamma frequency bands has been found during mind wandering between brain regions associated with the DMN, whereas during periods when subjects were focused on performing a visual task, there was significantly more phase synchrony within a task-specific brain network (Kirschner et al., 2012). Increases in theta oscillations in the medial frontal cortex, which are accompanied by decreases in beta and gamma oscillations at the same spatial coordinates and other brain areas, including nodes of the DMN, have been shown during working memory tasks (Brookes et al., 2011a). The increase in frontal theta power during working memory tasks has been shown to correlate with BOLD decrease in regions that together form the DMN (Scheeringa et al., 2009). The same study showed a right posterior alpha power increase, which was functionally related to BOLD decreases in the primary visual cortex and in the posterior part of the right middle temporal gyrus. No correlations were observed between oscillatory EEG phenomena and BOLD in the traditional working memory areas. These findings prompt an assumption that the observed increases in oscillatory power during working memory tasks actually reflect inhibition of neuronal activity that may interfere with working memory maintenance, with theta power increase being related to the inhibition of the DMN while alpha power increase being related to the inhibition of sensory perception (Scheeringa et al., 2009). Children demonstrate a stronger negative correlation between global theta power and the BOLD signal in the DMN during a working memory task relative to adults implying that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions (Michels et al., 2012). In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both adults and children, but only significant in adults in the frontal-parietal and posterior cingulate cortices. Moreover, theta synchronization, in contrast to EEG power, was positively correlated with response accuracy in both age groups. Thus, these studies show that increase of theta power correlates with DMN

suppression; increase of theta synchrony correlates with working memory performance; increase of alpha power, on the other hand, correlates with a suppression of sensory networks.

Summing up, the above outlined EEG studies appear to converge in showing that in resting condition, self-related thoughts are accompanied by an increase of spectral power in cortical regions overlapping with the DMN and these changes are most consistently found in the alpha band of frequencies. During working memory tasks, however, the deactivation of the DMN is reflected in an increase of medial frontal theta power with concomitant decrease of beta and gamma oscillations and an increase of alpha power in sensory cortices reflecting inhibition of neuronal activity that may interfere with working memory maintenance.

## **EEG CORRELATES OF THE PROCESSING OF SELF-RELATED INFORMATION**

Because self-related information could be presented via different sensory and functional domains (e.g., auditory, visual, sensorimotor, verbal, spatial, emotional, and so on), there could be domainspecific and self-specific effects. A meta-analysis by Northoff et al. (2006) of PET and fMRI studies of self-referential processing identified activation in cortical midline structures occurring across all functional domains (e.g., verbal, spatial, emotional, and facial). Cluster and factor analyses indicated functional specialization into ventral, dorsal, and posterior cortical midline areas. The latter encompasses the p/PCC and is considered involved in selfintegration (i.e., linkage of self-referential stimuli to the personal context, Northoff and Bermpohl, 2004). It is interesting, therefore, to look how EEG studies corroborate or contradict this framework. I will first present ERP and then oscillation studies of the processing of self-related stimuli.

Own body, own name, and the image of own face are the kind of stimuli that are frequently used in the studies of selfprocessing. It has been suggested that social cognition is one of the functions of the DMN (e.g., Mitchell, 2006) and it certainly constitutes a part of the self (e.g., Markus and Kitayama, 1991; Han and Northoff, 2009). Therefore, the processing of social stimuli and effects of social and cultural contexts are also relevant to the study of self-referential processing. Because real social behavior (i.e., interactions with other people) is not always possible to organize in a laboratory in a controlled manner, which is needed for EEG registration and subsequent meaningful analysis, virtual (i.e., modeled by means of a computer game) social interactions are frequently used.

#### **ERP STUDIES**

Many ERP studies of self-referential processing show that the discrimination of self from others is frequently associated with the well-known P300 ERP component, an evoked response to stimuli that are unexpected, salient, or motivationally relevant (Polich and Kok, 1995). Source localization of this response frequently shows activations in DMN structures associated with self-processing. Thus, the own hand elicited a greater positive component (P350– 500) than did other hand and the generator of this component was localized in the anterior cingulate cortex (ACC, Su et al., 2010). Mental imagery tasks with respect to the own body have been shown to elicit selective activation of the temporo-parietal

junction at 330–400 ms after stimulus onset (Blanke et al., 2005); duration of this activation, but not its strength, were found to correlate positively with perceptual aberration scores (Arzy et al., 2007). A higher P300 wave to the subject's own face than familiar or unfamiliar faces was observed in several studies (Ninomiya et al., 1998; Scott et al.,2005; Sui et al., 2006).Caharel et al. (2002) did not observe this effect, probably because of the very high occurrence of the subject's own face, illustrating the major habituation effect of such paradigms. Keyes et al. (2010) observed differences in the ERP waveforms much earlier, with increased N170 and vertex positive potential amplitude over posterior and fronto-central sites, respectively, for self relative to both friend and stranger faces. Cultural difference in neural mechanisms of self-recognition has been investigated both with regard to the long-term cultural experiences (Sui et al., 2009) and after modulation of temporary access to other cultural frameworks using a self-construal priming paradigm (Sui et al., 2013). For British participants, the own-face induced faster responses and a larger negative activity at 280–340 ms (N2) relative to the familiar face, whereas Chinese participants showed reduced N2 amplitude to the own-face compared with the familiar face (Sui et al., 2009). Furthermore, for British participants, priming an interdependent self-construal reduced the default anterior N2 to their own faces. For Chinese participants, however, priming an independent self-construal suppressed the default anterior N2 to their friend's faces (Sui et al., 2013).

Similarly to the processing of own face, participant's own name elicits a higher P300 amplitude (e.g., Fischler et al., 1987; Berlad and Pratt, 1995; Muller and Kutas, 1996; Holeckova et al., 2006). By presentation the participant's first name against a number of other first names in strict equiprobable fashion, it was possible to record an electrophysiological response to the subject's own name, which is independent of its probability of occurrence (Perrin et al., 1999, 2005). The characteristics of this ERP are consistent with those of the classical P300, but the latency (500 ms) was much longer than that usually obtained in response to pure tones (300 ms), this being probably the consequence of the difference in the length of the stimulus (Perrin et al., 1999). Differential ERPs to the own name were shown in altered states of consciousness, such as sleep (Perrin et al., 1999, 2005; Pratt et al., 1999) and in patients in a vegetative state (Perrin et al., 2006), suggesting that the identification of self-relevant stimuli remains in these states. Using an EEG-PET paradigm, Perrin et al. (2005) have shown that the amplitude of the P300 component, elicited when hearing one's own name, correlates with regional cerebral blood changes in right superior temporal sulcus, precuneus, and MPFC. Additionally, the latter was more correlated to the P300 obtained for the subject's name compared to that obtained for other first names. These results are in good agreement with fMRI studies showing differences in activation in MPFC and right paracingulate cortex (Kampe et al., 2003; Staffen et al., 2006) when comparing activation to presentation of the subject's own name to the activation to presentation of other names. These results are also in good agreement with the proposed critical role of midline structures in self-referential processing (Northoff and Bermpohl, 2004; Lou et al., 2005). Similar effects were observed when the selfrelevance effect in object recognition was studied (Miyakoshi et al., 2007).

Effects of the self-relevant possessive pronouns compared to non-self-relevant possessive pronouns were studied in several studies. These studies have shown that self-relevant possessive pronoun elicited significantly larger P300 amplitude than nonself-relevant possessive pronouns (Zhou et al., 2010; Shi et al., 2011) with sources of this activity being identified in MPFC, anterior cingulate, and postcentral cortex (Shi et al., 2011). Walla et al. (2007, 2008) showed that in the time range between 250 and 400 ms the information related to "my" and to "his" could be distinguished over occipital electrodes and in the temporal region. In a study by Esslen et al. (2008), self- vs. other-reference was investigated using trait adjectives in reference to the self or a close friend. The MPFC was found to be more active during the self-reference condition. In an interesting study by Herbert et al. (2011), the effect of emotional valence on ERPs elicited by self-relevant and non-self-relevant pronoun-noun expressions was investigated. From 350 ms onward, processing of self-related unpleasant words elicited larger frontal negativity, whereas processing of pleasant words elicited larger positive amplitudes over parietal electrodes from 450 ms after stimulus onset. This evidence is in line with above discussed evidence linking anterior DMN hub with processing of negative and posterior DMN hub with processing of positive self-related information (Knyazev, 2013a). However,Watson et al. (2007) observed larger N400 amplitudes for words with the self-positivity bias at fronto-central electrode sites. Further research is needed to disentangle the effects of self-reference and emotional valence on cortical electrical responses.

In sum, the discussed ERP studies generally concur with fMRI studies in suggesting that medial cortices (most notably MPFC and ACC) are the crucial structures for processing of self-relevant information. Additionally, they show that the time frame of this processing most frequently coincides with the well-known P300 ERP component.

## **OSCILLATION STUDIES**

Contrary to ERP, which reflects only the evoked (i.e., stimulusphase-locked) response, oscillations could be spontaneous, induced, or evoked. Spontaneous oscillations as correlates of selfreferential processes have been already discussed earlier. This chapter will review studies dealing with induced and evoked responses to self-related stimuli (see earlier in this review a discussion on possible functional meaning of these two kinds of responses). Many of these studies show that alpha suppression appears to be the most salient feature of induced responses to such kind of stimuli. Thus, by means of virtual reality technology, it has been shown that hand ownership and the experience of self-location are reflected in alpha (or mu) band power (8–13 Hz) modulations in bilateral sensorimotor cortices and posterior parietal areas (Lenggenhager et al., 2011; Evans and Blanke, 2013). Electrical neuroimaging showed that alpha power in the MPFC was correlated with the degree of experimentally manipulated self-location (Lenggenhager et al., 2011). Alpha activity in highly similar fronto-parietal regions was also modulated during a motor imagery task (Evans and Blanke, 2013). Hearing subject's own compared to other names was associated with increased alpha-band desynchronization at frontal sites in time window of 500–1000 ms (Höller et al., 2011). Selfrelated evaluation on personality traits compared to friend-related

evaluation induced stronger desynchronization and decreased phase synchrony in alpha and gamma bands, whereas preparatory self-related attentional orientation was marked by synchronization in these same bands (Mu and Han, 2013). However, in another study, the same authors show that relative to other referential traits, self-referential traits induced event-related synchronization of theta-band activity over the frontal area at 700–800 ms and of alpha-band activity over the central area at 400–600 ms (Mu and Han, 2010).

Several studies investigated EEG correlates of social cognition and behavior. Billeke et al. (2013) used EEG to study the neurobiology of perception of social risk in subjects playing the role of proposers in an iterated ultimatum game. The players were separated to high-risk and low-risk offers. Prior to feedback, high-risk offers generated a drop in alpha activity in an extended network. Moreover, trial-by-trial variation in alpha activity in the medial prefrontal, posterior temporal, and inferior parietal cortex was specifically modulated by risk and, together with theta activity in the prefrontal and PCC, predicted the proposer's subsequent behavior. Rejections of low-risk offers elicited a higher prefrontal theta activity than rejections of high-risk offers. Using a combination of ICA and sLORETA imaging Knyazev et al. (2011) showed that cortical patterns of alpha desynchronization in response to facial stimuli were different depending on whether these stimuli were presented in a context of social interactions or a judgment of facial affect task. In the former case, alpha desynchronization was found in the posterior DMN hub, whereas in the latter case it appeared at the terminal field of the ventral visual stream. Knyazev et al. (2013) used a computer game to model social interactions with virtual "persons," which included three major kinds of social behavior: aggressive, friendly, and avoidant. Most salient differences were found between avoidance and approach behaviors, whereas the two kinds of approach behavior (i.e., aggression and friendship) did not differ from each other. Comparative to avoidance, approach behaviors were associated with higher induced responses in most frequency bands,which were mostly observed in cortical areas overlapping with the DMN. The difference between approach- and avoidance-related oscillatory dynamics was more salient in subjects predisposed to approach behaviors (i.e., in aggressive or sociable individuals) and was less pronounced in subjects predisposed to avoidance behavior (i.e., in high trait anxiety scorers). These findings are in line with previous findings showing the effect of these personality traits on the perception of social emotional stimuli (Knyazev et al., 2008a) and oscillatory responses to approach- and avoidance-related cues (Knyazev and Slobodskoj-Plusnin, 2007).

The role of gamma activity in the p/PCC in autobiographical memory retrieval in humans was investigated by means of intracranial recordings (Dastjerdi et al., 2011; Foster et al., 2012). Late-onset (>400 ms) increases in broad high gamma power (70–180 Hz) within p/PCC sub-regions during episodic autobiographical memory retrieval was observed,while it was significantly reduced or absent when subjects retrieved self-referential semantic memories or responded to self-judgment statements, respectively. A significant deactivation of high gamma power was also observed during tasks, which require externally directed attention, such as arithmetic calculation (Foster et al., 2012).

All these studies show that induced oscillatory responses to self-related stimuli are mostly found in cortical areas belonging to the DMN and are most salient in the alpha band of frequencies, although responses in other frequency bands (most notably theta and gamma) are also frequently observed.

Few studies investigated evoked oscillatory responses to selfreferential stimuli. Miyakoshi et al. (2010) using the image of participant's own face observed phase resetting (i.e., evoked response, as measured by ITC values) in the theta band within the medial frontal area during 270–390 ms post-stimulus. Roye et al. (2010) during passive listening observed enhanced evoked oscillatory activity in the 35–75 Hz band for subject's own telephone ringtone, starting as early as 40 ms after sound onset, and found a co-activation of left auditory areas and left frontal gyri. Active detection of sounds additionally activated the superior parietal lobe supporting the existence of a fronto-parietal network of selective attention. Lastly, Knyazev et al. (2011) observed evoked alpha-band responses to facial stimuli in a social interaction task in the PCC.

#### **GENERAL SUMMARY AND UNRESOLVED QUESTIONS**

It could be summarized that in general, there is a good correspondence between imaging and EEG studies in localizing the selfreferential processing in the brain. Across different EEG measures and experimental paradigms, most studies find EEG correlates of these processes within the DMN; most frequently in the MPFC and other midline structures. This is remarkable, because midline structures are not directly accessible from the scalp and their activity could be only modeled by means of source imaging techniques, which have low spatial resolution and well-known other limitations. New information, which comes from EEG research and may not be obtained in fMRI studies concerns the temporal dynamics of self-referential processing and involvement of oscillations. Although some studies find self-processing-related differences in the ERP waveforms (Keyes et al., 2010) or evoked gamma response (Roye et al., 2010) very early (170 and 40 ms, respectively), most other studies show these differences at later stages, which are most frequently associated with the P300 ERP component. Given the well-known functional correlates of this component (i.e., salience detection), this evidence highlights the salience of self-related information and the tendency to pick it out from the stream of external stimuli. Most important and still most disputable question is the relation of EEG oscillations to

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#### **ACKNOWLEDGMENTS**

This work was supported by grants of the Russian Foundation for Basic Research (RFBR) No. 11-06-00041-a and 13-04-00182-a.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 20 March 2013; accepted: 24 May 2013; published online: 06 June 2013.*

*Citation: Knyazev GG (2013) EEG correlates of self-referential processing. Front. Hum. Neurosci. 7:264. doi: 10.3389/fnhum.2013.00264*

*Copyright © 2013 Knyazev. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.*

# Cortical midline structures and autobiographical-self processes: an activation-likelihood estimation meta-analysis

# **Helder F. Araujo1,2,3\*, Jonas Kaplan<sup>1</sup> and Antonio Damasio<sup>1</sup>**

<sup>1</sup> Brain and Creativity Institute, University of Southern California, Los Angeles, CA, USA

<sup>2</sup> Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA

<sup>3</sup> Graduate Program in Areas of Basic and Applied Biology, University of Oporto, Oporto, Portugal

#### **Edited by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada

#### **Reviewed by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada

Frank Van Overwalle, Vrije Universiteit Brussel, Belgium

#### **\*Correspondence:**

Helder F. Araujo, Brain and Creativity Institute, University of Southern California, 3620A McClintock Avenue, Los Angeles, CA 90089-2921, USA e-mail: haraujo@usc.edu

The autobiographical-self refers to a mental state derived from the retrieval and assembly of memories regarding one's biography. The process of retrieval and assembly, which can focus on biographical facts or personality traits or some combination thereof, is likely to vary according to the domain chosen for an experiment. To date, the investigation of the neural basis of this process has largely focused on the domain of personality traits using paradigms that contrasted the evaluation of one's traits (self-traits) with those of another person's (other-traits).This has led to the suggestion that cortical midline structures (CMSs) are specifically related to self states. Here, with the goal of testing this suggestion, we conducted activation-likelihood estimation (ALE) meta-analyses based on data from 28 neuroimaging studies. The ALE results show that both self-traits and other-traits engage CMSs; however, the engagement of medial prefrontal cortex is greater for self-traits than for other-traits, while the posteromedial cortex is more engaged for other-traits than for selftraits. These findings suggest that the involvement CMSs is not specific to the evaluation of one's own traits, but also occurs during the evaluation of another person's traits.

**Keywords: autobiographical-self, autobiographical memory, cortical midline structures, meta-analysis, fMRI, self**

# **INTRODUCTION**

The autobiographical-self can be described as a mental state deriving from a momentary access to information regarding facts and events in one's life (Damasio, 1998). The access depends on the retrieval and assembly of memories pertaining to a multitude of facts and events and is likely to vary with the kinds of memories involved. Access may focus on retrieval of relatively simple memory representations, as when one retrieves information regarding demographic aspects of one's identity (e.g., one's nationality); or it may be more specific and involve retrieval of representations of perceptual and emotional aspects of a particular episode (e.g., one's college graduation). The effort needed for the retrieval is likely to vary as well and it is probably smaller for memories pertaining to prominent aspects of one's biography than for memories regarding more remote events. Once memories are displayed, they may trigger a varied amount of related memories and the associated emotional responses. In brief, the nature and scope of the knowledge exhibited in an autobiographical-self state varies according to the domains of information that are recruited.

The investigation of the behavioral and neural correlates of the autobiographical-self has explored varied domains, including one's own name (e.g., Tacikowski et al., 2011), voice (e.g., Nakamura et al., 2001), body parts (e.g., Platek et al., 2008) and personality traits (e.g., Kelley et al., 2002), and autobiographical memories (e.g., Cabeza and St Jacques, 2007). Here, we focus on the domain of personality traits. By contrasting self-traits (i.e., deciding if a given personality trait accurately describes oneself) with other-traits (i.e., deciding if a given personality trait

accurately describes another person), some studies have found an advantage of self-traits over other-traits in terms of reaction times (RTs) and memory performance. This has led to the suggestion that information pertaining to self is processed differently from information pertaining to another person, and has become known as the"self-referent effect"(Rogers et al., 1977). Moreover, it has led to the idea that the neural basis of self-reference involves cortical midline structures (CMSs), namely the medial prefrontal cortex (MPFC), anterior cingulate cortex (ACC), and posteromedial cortices (PMCs) (reviewed in Northoff et al., 2006). The results of the existing studies are not conclusive, however, in regard to the existence of the self-referent effect (e.g., Symons and Johnson, 1997) as well as in regard to the association of CMSs with self-reference (e.g., Legrand and Ruby, 2009).

With the development of techniques capable of performing meta-analysis of neuroimaging data, some attempts have been made to investigate consistent differences between self and other in terms of brain activity (Northoff et al., 2006; Qin and Northoff, 2011; Qin et al., 2011; Denny et al., 2012). Although informative, the studies included in these meta-analyses varied in terms of the self-referential stimuli used (comprising, for example, autobiographical and episodic memories, personality traits, the participants' faces or other body parts, and the participants' names), as well as in terms of the tasks performed (including, for example, tasks in which the participants were not given any specific instructions other than to look at or to listen to the stimuli; and tasks in which the participants were asked to judge/evaluate or to reflect on aspects of the stimuli). This heterogeneity of domains and

approaches is a potential limitation given that autobiographicalself processes are likely to vary according to the stimuli and the tasks one uses (as discussed in Klein and Gangi, 2010). In addition, the kinds of "other" used in the original study and the relationship between self and other are likely to be decisive in establishing differences between self and other. The differences between self and other in terms of RTs and memory performance have been shown to be reduced or eliminated when the other is a close acquaintance, such as the participants'close friends (Symons and Johnson, 1997), or parents (Markus and Kitayama, 1991). In addition, activation in CMSs seems to vary according to who the other is. For example, activity in the MPFC during evaluation of traits for self is not different from that of a close other, but happens to be greater for self than for a distant other (Ochsner et al., 2005).

Here, we conduct meta-analyses of the previously reported brain activations restricted to the direct evaluation of personality traits pertaining to self ("self-traits") and to other ("other-traits"). We attempt to compare self and other in regard to processes underlying equivalent tasks with equivalent stimuli. We also investigate how the contrast of brain activity between self-traits and othertraits varied according to who the other is in relation to self (distant others versus close others).

Our working assumption is that in order to evaluate when a given personality trait describes one's self accurately, one needs to retrieve and assemble memories (an autobiographical-self state) and decide based on the knowledge accessed. These processes are likely to depend on structures capable of high-levels of integration, such as CMSs (Parvizi et al., 2006; Hagmann et al., 2008); they may also engage structures involved in emotion-related somatic representations such as the insula because of the subjective and emotional content of the personality traits (Damasio and Carvalho, 2013). Furthermore, evaluating when a given personality trait describes another person requires memory retrieval and decisions and is thus likely to involve similar brain structures. Nonetheless, we predict differences between self and other in terms of brain activity. These differences are probably commensurate with the differences present in the representations accessed during the evaluation. Representations regarding one's self are elaborated during a lifetime of episodes and events, whereas representations regarding another person are probably elaborated via a more limited amount of interactions with that person during the acquaintanceship. Thus the representations regarding one's self are probably more numerous and more easily retrieved than those regarding another person, and it is also probable that emotion responses associated with the evaluation are greater for self than for other. Finally, the differences between self and other may be greater when the other is a distant other than when the other is a close other, someone with whom one has a close relationship and interacts frequently over a long period of time.

#### **METHODS**

#### **STUDIES USED**

The studies included were found and retrieved via PubMed and PsychARTICLES, using "self" as a search word for studies that used functional magnetic imaging (fMRI). The citations within the retrieved publications were also explored as possible studies to include in the meta-analysis. This initial search was concluded by November 31, 2012. From the initial pool of retrieved publications, we selected only studies that investigated the direct evaluation of the domain of personality traits regarding self (i.e., the participants were asked to judge whether a set of personality traits described themselves), other (i.e., the participants were asked to judge whether a set of personality traits described another person), or both. We restricted the selection to studies that presented whole-brain analyses and included healthy subjects whose ages ranged from 18 to 50 years old.

The final selection assembled 28 publications, 31 studies (each study including a different set of participants; **Table 1**). We categorized the kind of other used in the experiments into two groups: (i) *distant others*, which included a well-known person from the public domain (e.g., former US President George W Bush); or a distant acquaintance of the subject (e.g., a classmate); (ii) *close others*, which included friends, siblings or romantic partners, or the participants' parents. Data regarding other-traits for underrepresented categories of other (i.e., Harry Potter in Pfeifer et al., 2007, and historic religious leaders in Han et al., 2010) were not included in the analysis.

The coordinates of the peaks of activation foci were recorded for each contrast in each experiment. Foci referring to the same contrast of interest (e.g., other > baseline) that derived from more than one experiment (e.g., distant other and the participant's mother) using the same group of participants, were analyzed together (for that contrast) in order to minimize within-group effects (Turkeltaub et al., 2011). The total number of foci, experiments, and participants for each contrast were as follows: (i) *self-traits* > *baseline*, 159 foci, 21 experiments, 340 participants; (ii) *other-traits* > *baseline*, 114 foci, 12 experiments, 219 participants for both distant and close others; 46 foci, 6 experiments, 95 participants for distant others; and 68 foci, 9 experiments, and 167 participants; (iii) *self-traits* > *other-traits*, 148 foci, 22 experiments, 383 participants for both distant others and close others; 98 foci, 15 experiments, 259 participants for distant others; 50 foci, 10 experiments, 185 participants for close others; (iv) *othertraits* > *self-traits*, 61 foci, 12 experiments, 218 participants, for distant others and close others combined; 23 foci, 7 experiments, 127 participants, for distant others; 38 foci, 6 experiments, 107 participants, for close others.

The baseline included in the studies was either rest (three experiments regarding self-traits > baseline) or an active task involving some judgment of trait words, such as in relation to the number of syllables of the words, the case, or the font in which the words were written, the valence of the words (17 experiments regarding self-traits > baseline; and all the experiments regarding other-traits > baseline).

Data regarding the RTs were also recorded; these data were available in 15 experiments: 9 referring to experiments that involved distant others, and 6 referring to experiments that involved close others.

#### **DATA ANALYSIS**

A probabilistic map of activation was generated for each contrast of interest using activation-likelihood estimate (ALE) with GingerALE2.3<sup>1</sup> . The steps involved in this estimation are explained in

<sup>1</sup>http://brainmap.org/ale/index.html



The same study is listed twice when it included two different populations.

detail in Turkeltaub et al. (2011). For a given contrast, the ALE values represent the likelihood of observing activity in that voxel for at least one group of participants (Turkeltaub et al., 2011). The coordinates in Talairach were transformed into MNI (SPM) using icbm2tal transform (Lancaster et al., 2007; Laird et al., 2010). Two thresholds were applied to the results: first, a threshold of *p* < 0.001 uncorrected; subsequently, a cluster size probability threshold of *p* < 0.05 determined by permutations of random data (5000 permutations). The ALE maps were compared between contrasts of interest using the ALE subtraction analysis (random effects, Laird et al., 2005) available in the same software. This included a permutation test (5,000 permutations) to determine the statistical significance of the differences, and a threshold of *p* < 0.001 (uncorrected). All the results are in MNI coordinates and were overlaid in a standard MNI brain (Colin27\_T1\_seg\_MNI.nii) using Mango<sup>2</sup> and MRIcroGL<sup>3</sup> .

The effect size for the difference in RT between self and other was assessed using the reported *t-*test and *F-*test parameters, and calculating point-biserial correlation *r* values, as suggested and explained in Rosenthal and DiMatteo (2001). In brief, the *r* values were calculated using the following formula: *r* = [*t* 2 /(*t* <sup>2</sup> + df)]1/2 , or *r* = [*F* 2 /(*F* <sup>2</sup> + dferror)]1/2. Then, the *r* values were converted into *Fisher Z* values; mean *Z* scores and corresponding 95% confidence interval were calculated for the experiments according to the kind of other (close others and distant others), and then transformed back into *r* values.

#### **RESULTS**

#### **REACTION TIMES**

Reaction times tended to be greater for other-traits than for self-traits. The average unstandardized difference between mean RTs for other-traits and mean RTs for self-traits was 24.53 ms (SEM = 12.56 ms; mean RTs reported in 13 experiments). Statistically significant differences between self-traits and other-traits were reported in six experiments (five regarding distant others,

<sup>2</sup>http://ric.uthscsa.edu/mango/

<sup>3</sup>http://www.mccauslandcenter.sc.edu/mricrogl/

and 1 regarding close others); in five of these experiments (four referring to distant others and 1 referring to close others), mean RTs were greater for other than for self.

The average unstandardized difference between mean RT for other-traits and mean RT for self-traits was greater when addressing distant others (*M* = 32.93 ms; SEM = 17.98 ms; *N* = 8 experiments) than when addressing close others (*M* = 11.10 ms; SEM = 15.9 ms; *N* = 5 experiments). The 95% confidence interval of the effect size *r* followed the same trend: for distant others, it was 0.897 ± 0.804 ms (*N* = 7 experiments); for close others, it was 0.299 ± 0.202 ms (*N* = 6 experiments).

## **META-ANALYSES OF BRAIN ACTIVATION Self-traits versus baseline**

The meta-analysis of activation foci for self-traits yielded eight clusters of significant activation-likelihood (ALE): bilaterally in MPFC, PMC, and lateral prefrontal cortex, and in the left insula and middle temporal gyrus (**Table 2**; **Figure 1**).

#### **Other-traits versus baseline**

The meta-analysis of activation foci for other-traits regarding distant and close kinds of other yielded eight clusters of significant ALE: bilaterally, in the MPFC and PMC, in the left inferior frontal, middle temporal, and angular gyri, and in the right orbitofrontal gyrus (**Table 3**; **Figure 2**). The same meta-analysis restricted to distant others (i.e., a category that includes a well-know person of the public domain or participants' distant acquaintances such as classmates or housemates) revealed 24 clusters of significant ALE: bilaterally in the PMC, MPFC, middle temporal and supramarginal gyri, and in the left superior frontal gyrus and temporal pole, and in the right orbitofrontal gyrus and cerebellum (**Table 3**). In addition, the same meta-analysis restricted to close others (i.e., a category that includes a close acquaintance or relative of the participants, such as the participants' parents, or a participant's best friend/or sibling) yielded six clusters of significant ALE: bilaterally in the MPFC and PMC, and in the left superior and inferior frontal gyri and middle temporal gyrus (**Table 3**).

#### **SELF-TRAITS VERSUS OTHER-TRAITS**

**Self-traits versus other-traits for both distant others and close others** In the meta-analysis of the activation foci for self-traits > othertraits, we observed four clusters of significant ALE: bilaterally, in the MPFC and ACC, in the left PMC, and in the right middle frontal gyrus (**Table 4**; **Figure 3**). The metaanalysis of the activations relative to the reverse contrast (othertraits > self-traits) yielded eight clusters of significant ALE: bilaterally in the PMC and medial temporal gyrus, and in the right basal forebrain, superior parietal lobule, and cerebellum (**Table 5**; **Figure 4**).

#### **Self-traits versus other-traits for distant others**

The meta-analysis of the activation foci for self-traits > othertraits regarding only distant others yielded nine clusters of significant ALE, namely, bilaterally, in the MPFC, in the right superior frontal gyrus, and in the left PMC, insula, and angular gyrus (**Table 4**; **Figure 3**). The meta-analysis of activation foci regarding the reverse contrast (other-traits > selftraits) rendered two clusters of significant ALE in, bilaterally, the PMC and in the left middle temporal gyrus (**Table 5**; **Figure 4**).

#### **Self-traits versus other-traits for close others**

The meta-analysis of the activation foci for self-traits > othertraits for only close others revealed clusters of volumes greater than 100 mm<sup>3</sup> bilaterally in the MPFC. In addition, one of the clusters we identified falls outside of the standard brain, but in proximity to the left insula/inferior frontal gyrus. Also, the same

**FIGURE 1 | Meta-analysis of activation foci (159 foci; 21 experiments) for self-traits compared with baseline**.

**Table 2 | Meta-analysis of activation foci for self-traits compared with baseline (159 foci; 21 experiments).**



**Table 3 | Meta-analysis of activation foci for other-traits compared with baseline in relation to both kinds of other (114 foci; 12 experiments), to distant others (46 foci; 6 experiments), and to close others (68 foci; 9 experiments).**

analysis yielded additional clusters of significant ALE with smaller volumes, namely, in the lateral prefrontal, temporal, and occipital lobes (**Table 4**; **Figure 3**). The meta-analysis of activations for the reverse contrast (other-traits > self-traits) revealed two clusters of volumes greater than 100 mm<sup>3</sup> , bilaterally, in the PMC and in the right basal forebrain, and clusters with smaller volumes, bilaterally, in the PMC, in the right cerebellum, and in the left superior parietal lobule (**Table 5**; **Figure 4**).

### **COMPARISONS BETWEEN CONTRASTS (SUBTRACTION ANALYSES) Other-traits** > **baseline for close others versus other-traits** > **baseline for distant others**

A subtraction analysis did not yield differences of ALE results for other-traits > baseline between close others and distant others. A conjunction analysis revealed an overlap of ALE scores for othertraits > baseline between the two kinds of other in a large cluster in the PMC (cluster 1 – MNI coordinates: −3, −54, −29; ALE: 10.2;

volume: 384 mm<sup>3</sup> ) as well as in smaller clusters in the left superior frontal gyrus (cluster 2 – MNI coordinates: −13, 45, 51; ALE: 7, 54; volume: 40 mm<sup>3</sup> ; cluster 3 – MNI coordinates: −11, 35, 50; ALE: 7, 51; volume: 32 mm<sup>3</sup> ) and in bilaterally in the PMC (cluster 4: MNI coordinates: −8, −57, −30; ALE: 7, 74; volume: 16 mm<sup>3</sup> ; cluster 5: MNI coordinates: 0, −56, 18; ALE: 7, 43; volume: 8 mm<sup>3</sup> ).

# **Self-traits** > **other-traits for close others versus self-traits** > **other-traits for distant others**

In a subtraction analysis, ALE results for self-traits > other-traits regarding close others were not different from those regarding distant others. Nonetheless, a conjunction analysis revealed an overlap of ALE results for self-traits > other-traits between the two kinds of others in three clusters in the MPFC/ACC (cluster 1 – MNI coordinates: −5, 45, 20; ALE: 9.8; volume: 112 mm<sup>3</sup> ; cluster 2 – MNI coordinates: 0, 44, 9; ALE: 8.7; volume: 40 mm<sup>3</sup> ; cluster 3 – MNI coordinates: −5, 37, 24; ALE: 8.2; volume: 24 mm<sup>3</sup> ) and one cluster in the frontal pole (cluster 4 – MNI coordinates: 8, 62, −6; ALE: 7.65; volume: 8 mm<sup>3</sup> ).



#### **Other-traits regarding close others** > **self-traits versus other-traits regarding distant others** > **self-traits**

A subtraction analysis did not yield differences of ALE results for other-traits > self-traits between close others and distant others. In addition, a conjunction analysis showed an overlap of ALE results (for other-traits > self-traits) between the two kinds of other in a cluster in the PMC (MNI coordinates: 2, −56, 29; ALE; 7.1; volume = 16 mm<sup>3</sup> ).

# **DISCUSSION**

The processes of memory retrieval and decision that support the evaluation of one's personality traits vary depending on the recalled material. For example, it has been shown that both behavioral measures and brain activity during the evaluation of one's traits depend on how relevant the trait is to the individual's identity (e.g., Markus, 1977; Kuiper, 1981; Lieberman et al., 2004). The same factors are also likely to play a role in the evaluation of traits pertaining to another person and possibly account, at least in part, for the varied results reviewed in the published studies. Still, a meta-analysis of those published data may help us gain a better perspective on the problem.

The results of the present meta-analyses reveal similarities and differences between self-traits and other-traits in terms of activation foci. Contrasted with baseline, self-traits and other-traits engage some of the same brain structures, including CMSs such as the MPFC and the PMC. Nonetheless, the results also reveal parametric differences between self and other in terms of activation in CMSs as well as in the insula and basal forebrain. The ALE results, referring to the contrast of other-traits with baseline and to the

contrasts between other-traits and self-traits, seem to indicate that these differences may depend on the kind of other on which the study focused. We note, however, that the subtraction analyses did not confirm an effect of the type of other in any of the contrasts.

The MPFC and PMC are important hubs of brain connectivity and are presumably capable of high-levels of integration (Parvizi et al., 2006; Hagmann et al., 2008). They are known to exhibit greater activation during rest and during passive tasks than during a variety of demanding exteroceptive tasks (reviewed in Buckner et al., 2008). This suggests that these regions are preferentially involved in processing recalled, internally generated representations, something that is supported by their significant involvement during mind wandering (Mason et al., 2007), lapses of attention in externally oriented tasks (Weissman et al., 2006), and imagining future events (Schacter et al., 2012). We believe that their engagement in the evaluation of personality traits relates to retrieval and assembly of memories and to involvement in decision processes. Moreover, although the MPFC and PMC are interconnected and frequently activated during some of the same tasks, it is probable that these structures differ from each other in terms of the scope of representations they process.

The data derived from our meta-analyses show that the MPFC is generally more active for self-traits than for other-traits, and, although not confirmed by the subtraction analysis, this difference seems to be greater in the case of a distant other than a close other. There is strong evidence that MPFC is involved in the participation of somatic signals in processes of decision-making (Bechara et al., 2000a,b). It is thus possible that the differences of MPFC activity relate to emotion-related somatic representations in response to the memories retrieved and the decision. These responses are probably greater for self-traits than for other-traits but the difference is possibly smaller when referring to a close other than when referring to a distant other. We note that the differences between self-traits and other-traits in terms of insula activity are commensurate with those found for MPFC activity. In addition, it is also possible that the MPFC may be particularly involved in memory retrieval, namely by processing perceptual and somatic representations of the memories retrieved and thus contributing to a so-called "felt-rightness" during the retrieval (Moscovitch and Winocur, 2002). As discussed earlier, individuals are likely to have greater amount of memories for self than for another person; moreover, the memories are also likely to contain a greater amount of information, including both perceptual and somatic, when they pertain to self than when they pertain to another person. These differences are probably greater for a distant other than for a close other.

Intriguingly, our meta-analyses show that the PMC is more active for other-traits than for self-traits. The analyses relative to the contrast other-traits > self-traits derive from a smaller number of experiments than those regarding the opposite contrast, and this may limit the related statistical power. Nonetheless, we believe that the differences of PMC activity relate to effort in memory retrieval. The representations that regard self are probably more efficiently retrieved than those regarding another person, as supported by data regarding the RTs. Greater effort would translate into greater PMC activity. It is possible that by abstracting from episodes and facts during their lives, individuals have preassembled summary representations for some of their own personality traits (Klein


**Table 5 | Meta-analysis of activation foci for other-traits compared with self-traits in relation to both kinds of other combined (61 foci; 12 experiments), to distant kinds of other (23 foci; 7 experiments), and to close kinds of other (38 foci; 6 experiments).**

**FIGURE 4 | Meta-analysis of activation foci for other-traits compared with self-traits in relation to both kinds of other combined (61 foci; 12 experiments), to distant kinds of other (23 foci; 7 experiments), and to close kinds of other (38 foci; 6 experiments)**.

and Loftus, 1993). It is also possible that individuals hold similar summary representations for aspects of their acquaintances' personalities although that is more likely to occur in the case of close acquaintances than distant ones (Fuhrman and Funder, 1995).

There is indeed evidence for involvement of the PMC in memory retrieval both for information that regards self and for information that regards other people or things (e.g., Wagner et al., 2005; Binder et al., 2009; Rissman and Wagner, 2012). In addition, it has been shown that activity in the PMC relates to the retrieval effort. For example, the PMC shows greater activity during the recall of information than during the repetition of information (Buckner et al., 1996; Schacter et al., 1996).

It is likely that sub-areas within the same CMS are differently activated in different conditions. For example, although the PMC is generally more active for other-traits, it shows also a cluster of greater activity for self-traits than for other-traits in the present meta-analysis. It has also been proposed that the MPFC is differentially activated by self and other, with the most ventral areas more active for self and more dorsal areas more active for other (reviewed in Amodio and Frith, 2006).

In conclusion, our results provide evidence that self-traits and other-traits may depend on the same brain structures, including CMSs. Moreover, the differences between self-traits and othertraits vary according to who the other is in relation to self. We believe that these findings are linked to processes of memory retrieval and decision that underlie the evaluation of personality traits.

#### **ACKNOWLEDGMENTS**

We thank Brenton Keller and Christoph Kiefer for their help in the retrieval of studies included in the meta-analyses.

# **REFERENCES**


autobiographical knowledge about the self," in *Advances in Social Cognition*, Vol. 5, eds T. K. Srull and R. S. Jr. Wyer (Hillsdale, NJ: Erlbaum), 1–49.


*Science* 315, 393–395. doi:10.1126/ science.1131295


adults: when social perspectivetaking informs self-perception. *Child Dev.* 80, 1016–1038. doi:10. 1111/j.1467-8624.2009.01314.x


for literature reviews. *Annu. Rev. Psychol.* 52, 59–82. doi:10.1146/ annurev.psych.52.1.59


M. (2010). Reduced functional coupling in the default-mode network during self-referential processing. *Hum. Brain Mapp.* 31, 1117–1127. doi:10.1002/hbm.20920


**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 29 April 2013; accepted: 20 August 2013; published online: 04 September 2013.*

*Citation: Araujo HF, Kaplan J and Damasio A (2013) Cortical midline structures and autobiographicalself processes: an activationlikelihood estimation meta-analysis. Front. Hum. Neurosci. 7:548. doi: 10.3389/fnhum.2013.00548*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Araujo, Kaplan and Damasio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Self-specific stimuli interact differently than non-self-specific stimuli with eyes-open versus eyes-closed spontaneous activity in auditory cortex

#### **Pengmin Qin<sup>1</sup>\*, Simone Grimm<sup>2</sup> , NiallW. Duncan<sup>1</sup> , Giles Holland<sup>1</sup> , Jia shen Guo<sup>2</sup> ,Yan Fan<sup>2</sup> , AnneWeigand<sup>2</sup> , Juergen Baudewig<sup>2</sup> , Malek Bajbouj <sup>2</sup> and Georg Northoff <sup>1</sup>**

<sup>1</sup> Mind, Brain Imaging and Neuroethics Unit, University of Ottawa Institute of Mental Health Research (IMHR), Ottawa, ON, Canada <sup>2</sup> Cluster Languages of Emotion, Free University of Berlin, Berlin, Germany

#### **Edited by:**

Jennifer S. Beer, University of Texas at Austin, USA

#### **Reviewed by:**

Brent L. Hughes, Stanford University, USA Taru Flagan, University of Texas at Austin, USA

#### **\*Correspondence:**

Pengmin Qin, Mind, Brain Imaging and Neuroethics Unit, University of Ottawa Institute of Mental Health Research, 1145 Carling Avenue, Room 6435, Ottawa, ON K1Z 7K4, Canada e-mail: pengmin.qin@theroyal.ca

Previous studies suggest that there may be a distinct relationship between spontaneous neural activity and subsequent or concurrent self-specific stimulus-induced activity. This study aims to test the impact of spontaneous activity as recorded in an eyes-open (EO) resting state as opposed to eyes-closed (EC) on self-specific versus non-self-specific auditory stimulus-induced activity in fMRI. In our first experiment we used self-specific stimuli comprised of the subject's own name and non-self-specific stimuli comprised of a friend's name and an unknown name, presented during EO versus EC baselines in a 3 name condition × 2 baseline design. In Experiment 2 we directly measured spontaneous activity in the absence of stimuli during EO versus EC to confirm a modulatory effect of the two baseline conditions in the regions found to show an interaction effect in Experiment 1. Spontaneous activity during EO was significantly higher than during EC in bilateral auditory cortex and non-self-specific names yielded stronger signal changes relative to EO baseline than to EC. In contrast, there was no difference in response to self-specific names relative to EO baseline than to EC despite the difference between spontaneous activity levels. These results support an impact of spontaneous activity on stimulus-induced activity, moreover an impact that depends on the high-level stimulus characteristic of self-specificity.

**Keywords: eyes-open, eyes-closed, resting state, self, spontaneous activity, intrinsic activity, rest-stimulus interaction, self-specific stimulus**

#### **INTRODUCTION**

Spontaneous (or intrinsic) neural activity is operationally defined as activity that is relatively stable during the so-called"resting state" in which a subject is physically and mentally at rest (but awake) and exposed to a minimized stimulus array. The potentially important role of the brain's spontaneous activity has been suggested by findings that show such activity in many brain regions by a variety of methodologies (Panksepp, 1998; Raichle et al., 2001; Llinas et al., 2002; Freeman et al., 2003; Shulman et al., 2003, 2007, 2009; Raichle, 2009, 2010; Lauritzen et al., 2012). A question that suggests itself is what this role may be, including its contribution to or impact on the brain's response to stimuli (Northoff et al., 2010).

One approach to this question that has emerged recently is based upon the finding that there is a strong overlap between regions that show high spontaneous activity in the resting state and those that show a response to self-specific stimuli and tasks, with this overlap particularly marked in cortical midline regions (D'Argembeau et al., 2005; Beer, 2007; Schneider et al., 2008; Qin and Northoff, 2011; Whitfield-Gabrieli et al., 2011). In contrast, responses to non-self-specific stimuli do not show such an overlap (Qin and Northoff, 2011). The overlap is suggestive of some form of distinct relationship between spontaneous activity and self-specific stimulus processing, possibly including an interaction between spontaneous activity and self-specific stimuli

that is different than for non-self-specific stimuli. Such possibilities remain hypothetical but attractive and open to further investigation.

Preliminary work investigating the relationship between spontaneous and stimulus-induced activity in general has been carried out. For example, recent human imaging studies have shown that higher spontaneous activity immediately preceding a stimulus is predictive of higher stimulus-induced activity in the auditory cortex (Sadaghiani et al., 2009; Northoff et al., 2010). Similar effects have also been observed in visual cortex (Hesselmann et al., 2008) and somatosensory cortex (Boly et al., 2007).

An alternative approach was taken by Lerner et al. (2009), which attempted to modulate the level of spontaneous activity by using eyes-open (EO) and eyes-closed (EC) baseline conditions whilst stimuli consisting of musical tones were presented. It was found that the tones induced greater BOLD signal response in the auditory cortex during the EO than the EC condition. That said, a limitation of this particular study was that the spontaneous activity level itself in the auditory cortex during EO and EC conditions was not measured in the absence of stimuli (i.e., in the resting state). This makes it more difficult to interpret the observed effect as being a result of modulating spontaneous activity.

Modulation of spontaneous activity by EO versus EC can be seen in light of a growing literature on differences in brain activity produced by switching between these two states (Fox et al., 2005; Fransson, 2005; Barry et al., 2007; Yang et al., 2007; McAvoy et al., 2008; Bianciardi et al., 2009; Yan et al., 2009; Fingelkurts and Fingelkurts, 2010;Wu et al., 2010; Donahue et al., 2012). For example, in EEG, the mean power of the delta, theta, alpha, and beta bands is less in EO than EC across the scalp (Barry et al., 2007, 2011; Chen et al., 2008). In fMRI, functional connectivity between brain regions is weaker in EO than EC (Wu et al., 2010). Visual and auditory cortices show higher neural activity during EO than during EC (Marx et al., 2004; Qin et al., 2012a). Taken together, these studies demonstrate that EO versus EC can effectively change activity throughout large portions of the brain, including sensory and non-sensory regions.

Building on this described background, the aim of the current experiment was thus to investigate the question of the relationship between spontaneous and self-specific activity by presenting selfspecific stimuli and non-self-specific stimuli during EC and EO using fMRI. In addition, we aimed to measure simple spontaneous activity (in the absence of stimuli) in the regions identified as being of interest in the main interaction [(self-specific, non-self-specific stimuli) × (EC, EO)] analysis. We used auditory stimuli for several reasons. Firstly, a robust differential response to auditory selfspecific stimuli subject's own name (SON) versus non-self-specific stimuli (other names) has been found in auditory cortex (Di et al., 2007; Qin et al., 2010). Correlations between spontaneous activity and stimulus-induced activity have also been seen in the same region (Sadaghiani et al., 2009; Northoff et al., 2010). Thirdly and from a practical perspective, the use of auditory as opposed to visual stimuli allowed for even-handed stimulus presentation during both EO and EC.

Our study is comprised of two experiments. The first of these is an investigation of the impact of the EO/EC dimension of spontaneous activity on self-specific versus non-self-specific auditory stimulus-induced activity in auditory cortex using EO versus EC baselines during stimulus presentation. We used selfspecific versus non-self-specific stimuli in the form of the SON versus other names. Given that the overlapping between high spontaneous and self-specific stimulus-induced activity may indicate a distinct relationship between each other, and the previous study indicated that the brain regions with high spontaneous brain activity were involved in the self-specific processing (Gusnard, 2005), we hypothesized that the spontaneous brain activity change (EO versus EC) would impact activity induced by self-specific stimuli differently than by non-self-specific stimuli. In Experiment 2 we directly measured spontaneous activity in the absence of stimuli (i.e., the resting state) during EO versus EC to confirm a modulatory effect of the two baseline conditions in the regions found to show an interaction effect in Experiment 1.

# **MATERIALS AND METHODS**

#### **SUBJECTS**

Both Experiments 1 and 2 used the same 18 subjects (15 female, 3 male, age 20–34 years, mean age 27.1). The subjects did not suffer from any medical, neurological, or psychiatric disorders. All subjects had first names consisting of two syllables as part of the design of Experiment 1 (see below). Experiments 1 and 2 were

run on different days (interval 8.5 ± 7.25 days, mean ± SD across subjects). Informed written consent was obtained from all subjects. The study was approved by the ethics committee of the Free University of Berlin.

#### **DESIGN**

#### **Experiment 1. Interaction between EO versus EC baseline and self-specific versus non-self-specific stimulus-induced activity**

In Experiment 1 we investigated the effect of EO versus EC spontaneous activity on self-specific versus non-self-specific auditory stimulus-induced activity. Based on an established paradigm (Qin et al., 2012b) we used three name conditions. The SON was the condition of interest (self-specific), whilst the name of a friend of the subject (FN) and a name unknown to the subject (UN) were used as control conditions (non-self-specific). Unknown names were names in common usage but that did not belong to anyone personally known to the respective subjects. Names were all first names with two syllables (including SON, as per subject inclusion criteria) and of the same gender as the subject. All name stimuli were spoken by the same male researcher who was not known to the subjects and were presented at 75 dB. Mean duration was 541 ± 96 ms (mean ± SD).

The experiment was a 3 name condition (SON, FN, UN) × 2 baseline (EO, EC) factorial design. For each subject there was one run of EO and one run of EC. In each run there were three blocks each of SON, FN, and UN for a total of nine name condition blocks. A block was comprised of 10 presentations of the relevant name, once every 2 s. This meant that each block was 20 s in length. Inter-block interval was 40 s. The order of the blocks was pseudorandomized within the EO and EC runs. Ordering of the EO and EC runs was counterbalanced across subjects.

During the EO block, the subject was instructed to keep their EO and fixate on a white cross displayed on a black background on the in-scanner screen. During the EC run, the subject was instructed to close their eyes prior to the run starting. In both runs, subjects were instructed to relax and listen to the names as they were presented. In both Experiment 1 and 2, below, an inscanner camera was used to monitor the subjects and ensure that they followed the EO/EC requirements.

### **Experiment 2. EO versus EC spontaneous activity**

In Experiment 2 we measured spontaneous activity itself in EO versus EC resting states in the whole brain. There were five blocks each of EO and EC, presented alternately. The duration of EO blocks was four TR's and the duration of EC blocks was five TR's with TR = 8 s. EC blocks were longer than EO to allow the brain sufficient time to stabilize in the EC activity pattern. The start of an EC condition was indicated to the subjects by a single tone at 1000 Hz and 75 dB for 100 ms whilst the start of an EO condition was indicated by a double tone comprised of two single tones with an interval of 80 ms. Additionally, an open eye or closed eye icon was presented on screen in the scanner. The tones were extremely short relative to the length of the resting state blocks and the icons were small, simple, and static, so we judged the practical value of these instructional signs to outweigh any minor impact as stimuli on spontaneous activity. Subjects were instructed to relax with EO or closed according to the tone/icon prompts.

#### **DATA ACQUISITION AND PROCESSING**

Images were acquired on a Siemens 3.0T MAGNETOM TrioTim syngo MRI scanner at the Free University of Berlin. A 3D anatomical image was first acquired using a fast SPGR sequence (TR = 1.9 ms, TE = 2.25 ms, FOV = 256 mm × 256 mm, matrix = 256 × 256, slice thickness = 1 mm) for functional image registration and localization. Data for Experiment 1 were acquired using an EPI sequence (TR = 2 s, TE = 30 ms, θ = 90°, FOV = 192 mm × 192 mm, matrix = 64 × 64, slice thickness = 3 mm, gap = 0 mm). Each volume had 37 axial slices, covering the whole brain. Data for Experiment 2 were acquired using the same EPI sequence as Experiment 1 except TR = 8 s. For Experiment 2 a sparse sampling sequence was be used in order to reduce the effect of scanner noise on spontaneous brain activity (Gaab et al., 2007a,b, 2008).

Functional data were processed using the AFNI software package (Cox, 1996). Data underwent 2D and 3D head motion corrections, masking for removal of the skull, and spatial smoothing using a kernel of 6 mm full-width at half-maximum. Data were then converted to MNI space and resampled to 2 mm isotropic voxels.

#### **ANALYSIS**

# **Experiment 1 main part. Interaction between EO versus EC baseline and self-specific versus non-self-specific stimulus-induced activity**

One subject was excluded due to excessive head motion (>3 mm). The data from Experiment 1 were submitted to deconvolution analysis using a general linear model (3dDeconvolve, AFNI) to obtain a whole-brain voxel-wise map of estimated linear coefficients for the three name conditions relative to the two baselines, for a total of six coefficient maps: SON during EO, SON during EC, FN during EO, FN during EC, UN during EO, and UN during EC. The 10 name presentations in each block were regarded as 1 entirety (BLOCK model in 3dDeconvolve) in the deconvolution analysis. The 40-s inter-block intervals gave enough room for the modeling.

Since all coefficients are relative to their respective baseline, they discount any trivial contribution to activity of baseline level itself, isolating the stimulus-induced change from baseline and thus the presumed stimulus-induced component of activity. The approach here was intended to reveal any non-trivial effect of baseline as a statistical factor on the stimulus-induced component itself.

The whole-brain voxel-wise maps of coefficients for the three name conditions relative to the two baselines were entered into a 3 × 2 ANOVA (3dANOVA, AFNI). Interaction regions were identified as those regions showing a name × baseline interaction effect at an FWE-corrected threshold of *p* < 0.05 based on clusters of 80 or more voxels with an uncorrected *p* < 0.005, with the group mean of the whole-brain mask used for FWE correction (AlphaSim, AFNI). These interaction regions were then taken as ROI's for subsequent analysis.

Mean coefficients across voxels were calculated for each ROI. One-sample *t*-tests on these coefficients (two-tailed, *p* < 0.05) were done for each of SON, FN, and UN during EO and EC baselines to test for stimulus-induced signal changes relative to baseline. Paired *t*-tests were then done to test for differences in stimulus-induced signal between baselines. Bonferroni correction (*p* < 0.05) was applied across the ROI's.

# **The additional exploratory part of Experiment 1: stimulus-induced activity in brain regions involved in self-specific processing**

In addition to the above main analysis, an exploratory analysis of the effect of the different EO and EC baselines on self-related stimulus-induced activity in regions, other than the auditory cortex, that are involved in self-specific processing was carried out. To identify these regions, a whole-brain voxel-wise contrast of self-specific (SON) to non-self-specific (FN and UN) stimuli was made. Prior work has shown that the brain response to FN and UN is differentiable and so these two non-self conditions were included for completeness. In the exploratory analysis, FN and UN were grouped together as this work has also shown that SON-related activity is differentiable from both of these conditions which could work as the control conditions for self-specific stimuli and so they were taken as together representing non-selfspecific stimuli (Qin et al., 2012b). Since FN and UN may make the signal twice, we take half of each into the contrast [SON −0.5 (FN + UN)] (3dANOVA3, AFNI). Those regions identified as being more active during self-specific stimulus presentation (using an FEW-corrected threshold of *p* < 0.05) were then taken as ROIs and analyzed in the same manner as the auditory cortex ROIs described above.

#### **Experiment 2. EO versus EC spontaneous activity**

One subject was excluded due to excessive head motion (>3 mm). The data from Experiment 2 were submitted to deconvolution analysis using a general linear model (3dDeconvolve, AFNI) to obtain a whole-brain voxel-wise map of estimated linear coefficients for the contrast [EO – EC]. Mean coefficients across voxels were calculated for the ROI's from both parts of Experiment 1. One-sample *t*-tests (two-tailed) were done to test for differences in spontaneous activity between EO versus EC. Bonferroni correction (*p* < 0.05) was applied across the three ROI's from Experiment 1 Main Part (bilateral auditory cortex and left inferior parietal lobule, name condition × baseline interaction effect), and independently across the five ROI's from Experiment 1 Additional Exploratory Part [posterior cingulate cortex (PCC), right/left inferior frontal gyrus (r/lIFG), right anterior insula (rAI), left temporoparietal junction (lTPJ), self-specific versus non-self-specific stimulus-induced activity].

# **RESULTS**

#### **EXPERIMENT 1 MAIN PART. INTERACTION BETWEEN EO VERSUS EC BASELINE AND SELF-SPECIFIC VERSUS NON-SELF-SPECIFIC STIMULUS-INDUCED ACTIVITY**

The bilateral auditory cortex and left parietal lobule emerged as regions showing a significant name (SON, FN, UN) × baseline (EO, EC) interaction effect (**Table 1**).

In left auditory cortex, one-sample *t*-tests for each of SON, FN, and UN during EO and EC baselines to test for stimulus-induced signal changes relative to baseline found significant changes for all conditions in all ROI's: SON during EO (*t* = 6.13, *p* < 0.001 Bonferroni correction), SON during EC (*t* = 8.45, *p* < 0.001 Bonferroni correction), FN during EO (*t* = 7.07, *p* < 0.001 Bonferroni


**Table 1 | Experiment 1 regions of interest identified by interaction effect of name condition (SON, FN, UN) and baseline (EO, EC).**

Cluster size >= 80 voxels (2 mm isotropic), p < 0.05 FWE corrected. The coordinates are the peak coordinates.

correction), FN during EC (*t* = 3.25, *p* = 0.005 Bonferroni correction), UN during EO (*t* = 7.63, *p* < 0.001 Bonferroni correction), UN during EC (*t* = 3.20, *p* = 0.006 uncorrected, *p* = 0.018 Bonferroni correction).

Paired *t*-tests for differences in stimulus-induced signal between baselines revealed significantly stronger signal changes in UN (*t* = 3.95, *p* = 0.001 uncorrected, *p* = 0.003 Bonferroni correction) and FN (*t* = 3.51, *p* = 0.003 uncorrected, *p* = 0.009 Bonferroni correction) during EO than during EC. In contrast, no such difference was observed for SON (**Figure 1A**).

Results in right auditory cortex (**Figure 1B**) mirrored those in left. One-sample *t*-tests revealed marginally significant signal changes for SON during EO (*t* = 2.55, *p* = 0.022 uncorrected, *p* = 0.066 Bonferroni correction) and significant signal change for SON during EC (*t* = 3.40, *p* = 0.004 uncorrected, *p* = 0.012 Bonferroni correction), and for FN and UN during EO (*t* = 2.16, *p* = 0.046 uncorrected, *t* = 3.29, *p* = 0.005 uncorrected, *p* = 0.015 Bonferroni correction respectively) though not during EC.

Paired *t*-tests revealed significantly stronger signal changes for UN during EO when compared to EC (*t* = 3.47, *p* = 0.003 uncorrected, *p* = 0.008 Bonferroni correction). The difference for FN approached significance (*t* = 1.80, *p* = 0.09 uncorrected). No such difference was observed for SON.

In left inferior parietal lobule, one-sample *t*-tests showed that only SON during EO induced significant signal (*t* = 4.13, *p* = 0.001 uncorrected, *p* = 0.003 Bonferroni correction) while SON during EC did not. UN induced marginally significant signal changes during EO (*t* = 2.31, *p* = 0.035 uncorrected, *p* = 0.11 Bonferroni correction). Paired *t*-tests reveal that marginally stronger signal changes for SON during EO than EC (*t* = 2.592, *p* = 0.02 uncorrected, *p* = 0.06 Bonferroni correction). There is no difference for UN between during EC and EO while there is significantly stronger signal change for FN during EC than during EO (*t* = 2.829, *p* = 0.012 uncorrected, *p* = 0.036 Bonferroni correction).

#### **THE ADDITIONAL EXPLORATORY PART OF EXPERIMENT 1: STIMULUS-INDUCED ACTIVITY IN BRAIN REGIONS INVOLVED IN SELF-SPECIFIC PROCESSING**

To identify activation regions for the additional exploratory part of Experiment 1, the contrast [SON −0.5 (FN + UN)] across both EO and EC baselines yielded significant signal changes in

condition (SON, FN, UN) and baseline (EO, EC) in bilateral auditory cortex. Graphs show estimated coefficients (mean across region ± SE) for name conditions relative to baselines. **(C)** From Experiment 2. Estimated coefficients of the contrast [EO – EC] in the same ROIs. r/lAC = right/left auditory cortex. \*Significant difference.

**Table 2 | Experiment 1 (supplemental) regions of interest identified by activation for [SON** −**0.5 (FN** + **UN)] across EO and EC.**


Cluster size >= 80 voxels (2 mm isotropic), p < 0.05 FWE corrected. \*Region did not pass FWE correction (see text).

The coordinates are the peak coordinates.

five clusters in the PCC, bilateral inferior frontal gyrus (r/lIFG), rAI, and lTPJ respectively. Note that the cluster in rAI did not pass the FWE correction but we retained it since previous studies have shown this region to be involved in self-specific stimulus processing (Qin and Northoff, 2011; Qin et al., 2012b) (**Table 2**; **Figure 2**).

One-sample *t*-tests for each of SON, FN, and UN during EO and EC baselines to test for stimulus-induced signal changes relative to baseline revealed the following significant changes: in PCC, SON induced signal change during EO (*t* = 2.63, *p* = 0.018 uncorrected) and FN negative signal change during EO (*t* = 2.19, *p* = 0.043 uncorrected) (**Figure 2A**). In Left inferior frontal gyrus (lIFG), SON induced signal change during EO (*t* = 5.06, *p* < 0.001 Bonferroni correction) and EC (*t* = 4.09, *p* = 0.001 uncorrected, *p* = 0.005 Bonferroni correction) (**Figure 2B**). In Right inferior frontal gyrus (rIFG), SON

induced signal change during EO (*t* = 3.33,*p* = 0.004 uncorrected, *p* = 0.02 Bonferroni correction) and EC (*t* = 5.03, *p* < 0.001 Bonferroni correction) and UN signal change during EO (*t* = 2.19, *p* = 0.044 uncorrected) (**Figure 2C**). In rAI, SON induced signal change during EO (*t* = 3.38, *p* = 0.004 uncorrected, *p* = 0.02 Bonferroni correction) and EC (*t* = 4.08, *p* = 0.001 uncorrected, *p* = 0.005 Bonferroni correction) (**Figure 2D**). In lTPJ, SON induced signal change during EO (*t* = 5.39, *p* < 0.001 Bonferroni correction) and EC (*t* = 5.57, *p* < 0.001 Bonferroni correction), FN signal change during EC (*t* = 2.41, *p* = 0.029 uncorrected), and UN signal change during EO (*t* = 5.10, *p* < 0.001 Bonferroni correction) (**Figure 2E**). Paired *t*-tests for differences in stimulus-induced signal between baselines revealed no significant differences.

#### **EXPERIMENT 2. EO VERSUS EC SPONTANEOUS ACTIVITY**

In the two ROIs in auditory cortices from Experiment 1 main part (bilateral auditory cortex, name condition × baseline interaction effect), one-sample *t*-tests for signal differences between EO/EC resting states revealed higher spontaneous activity during EO than EC in right auditory cortex (*t* = 2.91, *p* = 0.01 uncorrected, *p* = 0.03 Bonferroni corrected) and a trend toward a similar difference in left auditory cortex (*t* = 2.01, *p* = 0.06 uncorrected) (**Figure 1C**). In the left inferior parietal lobule, the spontaneous activity did not show any difference between during EO and during EC.

In the five ROI's from Experiment 1 Additional Exploratory part (PCC, r/lIFG, rAI, lTPJ, self-specific versus non-self-specific stimulus-induced activity), one-sample *t*-tests revealed no significant difference between spontaneous activity during EO versus EC. In lTPJ, a trend toward higher activity during EC was seen (*t* = 2.58, *p* = 0.02 uncorrected) (**Figure 2F**).

#### **DISCUSSION**

We report an interaction study between the EO versus EC variance of spontaneous activity and self-specific versus non-selfspecific auditory stimulus-induced activity in fMRI. Non-selfspecific stimuli (friends' names and unknown names) induced significantly stronger BOLD signal changes relative to respective baseline during EO versus EC baselines in auditory cortex. In contrast, self-specific stimuli (subjects' own names) did not induce different signal changes between baselines. Thus, our results show an interaction effect of self-specific/non-self-specific stimuli and EO/EC baseline. These findings are consistent with a previous brain imaging study (Lerner et al., 2009) as well as EEG studies (Griskova-Bulanova et al., 2011a,b) that indicate EO versus EC baselines can affect neural response to auditory stimuli. Our results extend these findings by showing that EO versus EC interacts with self-specific stimuli differently than non-self-specific.

In the same regions, our second experiment confirmed that spontaneous brain activity as directly measured in the absence of stimuli (i.e., the resting state) is modulated (increased) by EO versus EC. This finding is also consistent with previous studies that indicate EO can arouse the entire cortex (Barry et al., 2007, 2009) and that EO is associated with stronger activation than EC across sensory cortices, not just visual cortex (Marx et al., 2003; Brandt, 2006; Wiesmann et al., 2006; Hufner et al., 2009; Qin et al., 2012a).

In additional exploratory work, we also investigated the effects of self-specific versus non-self-specific names across both baselines in the whole brain. This yielded significant activity differences in PCC, rAI, lIFG, rIFG, and lTPJ (**Figure 2**), generally consistent with previous studies (Kelley et al., 2002; Northoff and Bermpohl, 2004; Mitchell et al., 2005; Northoff et al., 2006; Platek et al., 2006; Uddin et al., 2007; Zhu et al., 2007; Yaoi et al., 2009; Qin and Northoff, 2011; Qin et al., 2012b).

Considering our results further,spontaneous brain activity during EO was significantly higher than during EC (**Figure 1C**) in auditory cortex, and non-self-specific names yielded stronger signal changes relative to EO baseline than to EC (**Figures 1A,B**). These combined findings are consistent with previous findings in auditory cortex where higher spontaneous activity immediately preceding a stimulus predicts higher stimulus-induced activity (Sadaghiani et al., 2009). In contrast to non-self-specific names, there was no difference in response to self-specific names relative to EO baseline than to EC, despite the difference between spontaneous levels themselves.

In light of the general trend of interaction between spontaneous activity and stimulus-induced activity (higher resting state activity, stronger stimulus-induced activity) (Bianciardi et al., 2009; Sadaghiani et al., 2009; Hesselmann et al., 2010; Northoff et al., 2010; Donahue et al., 2012), one interpretation of these interaction results could be framed in terms of modulation of stimulusinduced activity by underlying spontaneous activity. Previous studies have indicated that spontaneous activity may be associated or involved with self-specific processing (Gusnard, 2005), This theory is consistent with the fact that in the resting state in which spontaneous activity is particularly pronounced, external input and engagement is minimized, allowing a balance to shift more toward internal (neuro-intrinsic as well as interoceptive) input, which is in general more self-referential. See Northoff et al. (2006) for a survey and meta-analysis of pertinent research results. Thus,we might expect self-specific stimulus-induced activity to be impacted more in step with spontaneous activity by factors that affect the latter such as EO versus EC. Meanwhile, we might expect non-self-specific stimulus-induced activity to be impacted in a manner more dissociated with spontaneous activity. Our finding here of no difference in self-specific stimulus-induced activity relative to spontaneous baseline as opposed to a significant difference for non-self-specific stimuli is in keeping with this theory.

It could be argued that the differences in stimulus-induced activity during EO and EC observed in this study are the result of modulation of attention. However, previous cross-modal studies suggest that attending more to visual stimuli tends to inhibit response to auditory stimuli in auditory cortex (Laurienti et al., 2002; Mozolic et al., 2008). Our findings were the opposite: friend's names and unknown names induced higher activity

during EO than EC, making an explanation based on attention more problematic than one based on spontaneous activity.

Aside from the auditory cortex, the left inferior parietal lobule also showed a name condition × baseline interaction effect. This result needs to be treated with caution, however, as of the 6 name condition × baseline combinations only SON during EO induced a significant signal change in the region. Moreover, the signal changes for FN during EC were stronger as opposed to weaker than during EO, which was inconsistent with the trend of our findings in other regions and may be inconsistent with the previous studies mentioned above. Finally, unlike in auditory cortex there was no difference between EO and EC spontaneous activity levels. The interaction effect in the left inferior parietal lobule may thus merit more investigation in the future to clarify these issues.

As mentioned in the introduction, EO versus EC can cause changes in activity throughout the brain. Some of these changes may be meaningfully categorized as changes in spontaneous activity that can directly contribute to stimulus processing. But others may not be – for example, a greater propensity for mind wandering during EC (Yan et al., 2009). The line here is certainly blurry. Future work could use both neural and behavioral measures to further address the distinction between modulation of spontaneous activity as it directly contributes to stimulus processing and modulation of other cognitive processes that affect stimulus processing more indirectly.

There is another issue that should be mentioned. It may be argued that the EO resting condition should be more properly seen as an activation state (Barry et al., 2007; Logothetis et al., 2009). Nonetheless, numerous studies have used an EO resting state with apparently reasonable justification (Fox et al., 2005; Fransson, 2005; Barry et al., 2007; Yan et al., 2009), for example, when spontaneous activity is to be related to the responses to stimuli that are presented visually. In addition, it should be considered that the brain receives constant input during both the EO and EC condition (auditory, proprioceptive, etc.), and so a differentiation between the EO and EC as an activation state or not becomes less tenable.

In summary, spontaneous brain activity during the EO resting state was significantly higher than during EC in bilateral auditory cortex and non-self-specific names yielded stronger signal changes relative to EO baseline than to EC. This supports the idea that spontaneous activity can impact neural response and processing of stimuli. From this perspective, it may be onesided to generally investigate response to stimuli solely by varying those stimuli. Rather, it may be fruitful to vary both stimuli and spontaneous activity or baseline. Moreover, our results show that modulation of spontaneous activity did not affect self-specific stimuli as it did non-self-specific, suggesting that an impact of spontaneous activity on stimulus processing is complex at least insofar as it can depend on the high-level stimulus characteristic of self-specificity.

#### **ACKNOWLEDGMENTS**

We are grateful to the staff at the Free University of Berlin for technical support in data acquisition. We are also grateful to CIHR, EJLB, and HDRF/ISAN for financial support.

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thalamocortical inputs: a voltagedependent dye-imaging study in mouse brain slices. *Proc. Natl. Acad. Sci. U. S. A.* 99, 449–454. doi:10.1073/pnas.012604899


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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 14 May 2013; accepted: 16 July 2013; published online: 29 July 2013.*

*Citation: Qin P, Grimm S, Duncan NW, Holland G, Guo J, Fan Y, Weigand A, Baudewig J, Bajbouj M and Northoff G (2013) Self-specific stimuli interact differently than non-self-specific stimuli with eyes-open versus eyes-closed spontaneous activity in auditory cortex. Front. Hum. Neurosci. 7:437. doi: 10.3389/fnhum.2013.00437*

*Copyright © 2013 Qin, Grimm, Duncan, Holland, Guo, Fan, Weigand, Baudewig , Bajbouj and Northoff. This is an openaccess article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.*

# Self-associations influence task-performance through Bayesian inference

# **Sara L. Bengtsson<sup>1</sup> andWill D. Penny <sup>2</sup>\***

<sup>1</sup> Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden <sup>2</sup> Wellcome Trust Centre for Neuroimaging, University College, London, UK

#### **Edited by:**

Niall W. Duncan, University of Ottawa, Canada

#### **Reviewed by:**

Juliana Yordanova, Bulgarian Academy of Sciences, Bulgaria Brian D. Gonsalves, University of Illinois, USA

#### **\*Correspondence:**

Will D. Penny, Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London WC1N 3BG, UK e-mail: w.penny@ucl.ac.uk

The way we think about ourselves impacts greatly on our behavior. This paper describes a behavioral study and a computational model that shed new light on this important area. Participants were primed "clever" and "stupid" using a scrambled sentence task, and we measured the effect on response time and error-rate on a rule-association task. First, we observed a confirmation bias effect in that associations to being "stupid" led to a gradual decrease in performance, whereas associations to being "clever" did not. Second, we observed that the activated self-concepts selectively modified attention toward one's performance. There was an early to late double dissociation in RTs in that primed "clever" resulted in RT increase following error responses, whereas primed "stupid" resulted in RT increase following correct responses. We propose a computational model of subjects' behavior based on the logic of the experimental task that involves two processes; memory for rules and the integration of rules with subsequent visual cues. The model incorporates an adaptive decision threshold based on Bayes rule, whereby decision thresholds are increased if integration was inferred to be faulty. Fitting the computational model to experimental data confirmed our hypothesis that priming affects the memory process. This model explains both the confirmation bias and double dissociation effects and demonstrates that Bayesian inferential principles can be used to study the effect of self-concepts on behavior.

**Keywords: priming, self-esteem, rule task, cognitive control, Bayesian, normative model, computational model**

# **1. INTRODUCTION**

High self-esteem is characterized by thinking well of oneself, whether it is a true or distorted appreciation. Low self-esteem denotes a less consistent and more uncertain regard about one's abilities (Campbell, 1990). Self-esteem is the evaluative dimension of self-concepts (Harter and Baumeister, 1993). Taking a cognitive architectural approach of personality, self-concepts can be viewed as knowledge structures of attributes of oneself formed from experience and organized as any other mental concept (Markus, 1977; Cervone et al., 2004). They are used to guide the processing of selfrelevant information (Kelly, 1955; Markus, 1977), and emerging evidence shows that the way we think about ourselves impacts on aspects such as depression (Harter and Baumeister, 1993), obesity (Ternouth et al., 2009), school performance (Spinath et al., 2006), and criminal behavior (Trzesniewski et al., 2006).

Functional neuroimaging studies have consistently highlighted processes of the anterior medial prefrontal cortex (aMPFC) as part of reflecting upon one's own character (for a review, see Amodio and Frith, 2006). Enhanced activation is seen when participants judge whether or not traits apply to themselves as compared to when they make judgments about others' character (Kelley et al., 2002; Mitchell et al., 2002) and subsequently when the traits are high as compared to low in self-relevance (Moran et al., 2006). Furthermore, Macrae et al. (2004) showed that high activation in the aMPFC when judging self-relevant traits resulted in better recollection when debriefed after the experiment of which adjectives

had been presented. Bengtsson et al. (2009) found that this area is sensitive to task instructions that make participants specifically monitor their own performance. When told that the task they took was a measure of their ability there was enhanced neural activation in aMPFC when the participants made errors, compared to a group who were told that the task they took was a piloting task. Task difficulty was titrated so that accuracy was matched between the two groups.

Stored in long-term memory, the concept of self may not change extensively over an individual's lifespan (Marcus and Kunda, 1986; Campbell, 1990). However, the influence of selfconcepts on behavior will vary depending on applicability and accessibility of the knowledge structures to the task the individual is encountering (Higgins, 1990). This is exemplified in priming studies where, e.g., priming for "old" makes people more likely to walk slower down the corridor than they would otherwise do (Bargh et al., 1996), or when primed with associations to "professor" people become more likely to score highly on a quiz (Dijksterhuis and van Knippenberg, 1998). Priming refers to the passive and unobtrusive activation of relevant mental representations by environmental stimuli such that people are not and do not become aware of the influence exerted by those stimuli (Bargh and Chartrand, 2000). Dual-process models (Smith and DeCoster, 2000; Strack and Deutsch, 2004) stipulate that human behavior is the result of interactions between automatic/impulsive processes on the one hand and controlled/reflective processes on the other.

According to the Strack and Deutsch (2004) model, the Impulsive system is a network of associative nodes, with connections differing in their weight according to how frequently they occur together. Incoming information is always processed by the impulsive system, where the influence of the system on behavior is greatly determined by the extent of pre-activation of specific connections in the associative network. The Reflective system, which focuses attention toward relevant stimuli, is subjected to the individual's awareness and control. Goal oriented conflict between the two systems costs energy, and can impact cognitive performance, such as results on an IQ-test when conflicts arise between the implicit and explicit self-concept of intelligence (Dislich et al., 2012).

We have previously found that errors on a subsequent working memory task take on a different meaning when participants are primed with associations to "clever" and "stupid." "Clever" priming led to increased activity in aMPFC as well as post-error slowing in reaction times, whereas "stupid"-priming was followed by increased activation in insula when the participants made errors and absence of post-error slowing (Bengtsson et al., 2011). Rabbitt (1966) suggested that the slowing of responses immediately after errors is due to the validation of an error, and thus transient changes in response strategy to minimize the possibility of further errors. This proposal is supported by empirical findings that post-error slowing lowers the probability of committing a subsequent error in the post-error trial (Rabbitt, 1966; Danielmeier et al., 2011). Thus, our results suggest that "stupid"-associations led to greater uncertainty as to whether errors had occurred or not. We further speculated that the results may reflect a conflict between the implicit self-associations (e.g., "clever") and the explicit self-associations (I'm making an error), and that in the case of "clever" the post-error slowing reflects a greater surprise about the outcome. This interpretation is supported by the model of Notebaert et al. (2009), where they propose that post-error slowing represents an attention-grasping (surprising) event. They showed that slowing occurs when the outcome is rare, rather than to errors in particular. When correct responses outnumbered error responses, post-error slowing occurred, whereas when the majority of the trials were incorrect post-correct slowing was observed. In fact, influential theoretical models of self-regulation propose that individuals adjust their behavior so as to minimize the discrepancy between active selfassociations and goals. Carver and Scheier (1998) in their model have taken inspiration from control theory and propose that the active self-concept functions as a reference, and in a discrepancyreducing feedback loop individuals aim to adjust behavior so as to minimize the discrepancy between action and the reference. Similarly, Conway and Pleydell-Pearce (2000) propose that the active self-concept functions as a working memory control process to filter what self-relevant information to encode in order to reduce the tension between active self-knowledge and goals.

The aim of the present study is to test our predictions from Bengtsson et al. (2011): priming with associations to "clever" leads participants to treat errors as more surprising than when they are primed "stupid," since an error would then generate a larger discrepancy between expectations and outcome. If this is true, using the same logic, we would also expect a greater surprise to

correct responses when participants are primed with "stupid" associations. We examined these predictions in a behavioral study using a rule-association task (Crone et al., 2006). Additionally, we develop a computational model to improve the understanding of underlying mechanisms. We use Bayesian probability theory to test if behavior may be regulated based on the probabilistic attribution of outcomes to a subject's own abilities. The aim of the model is to shed light on what we mean by various concepts such as self and esteem. Previously, Bayesian theory has proven useful in understanding brain and behavior on many levels (Doya et al., 2007), from sensory perception (Ernst and Banks, 2002) to motor learning (Kording and Wolpert, 2004) and social interaction (Yoshida et al., 2008) (for a recent review, see Penny, 2012). However, to our knowledge, there has to date been no research on using Bayesian inference to probe the mechanisms relating trait-associations to behavior.

Our model makes the following assumptions (a) that our behavioral task embodies two processes (i) memory: remembering a rule for how to behave and (ii) response accumulation: integrating stimuli with rule memory to produce an appropriate response, (b) the decision threshold for the response accumulation process, β, adapts over trials by switching to a higher value if accumulation was inferred to be incorrect on the previous trial, (c) mean reaction time is proportional to a log-odds ratio (log β/[1 − β]), (d) estimates of memory integrity (the probability of correctly remembering the rule) are updated over time. Additionally, we hypothesize that priming affects the memory process and test this hypothesis by fitting our model to subjects' behavioral data. This hypothesis stems from the notion that both working memory and priming are considered to be top-down processes where they both depend on goal-directed processes that rely on previous knowledge. The response accumulation process can be considered a bottom-up process since it relies on sensory stimuli (Pessoa and Ungerleider, 2004).

## **2. MATERIALS AND METHODS**

This section first describes the participants involved in the study and the behavioral task they performed. The "Bayesian Model" section then describes the assumed component processes underlying the task, and how the probability of them failing relates to incorrect task performance. It also describes how the decision threshold for the accumulation process is adaptively switched between low and high levels, and how reaction time is related to this threshold. The section on "Model Likelihood" describes how the experimental data (time series of error/correct outcomes and reaction times) are related to model parameters such as memory integrity and decision thresholds. Finally, the "Model Fitting" section describes how the model is fitted to the experimental data.

#### **2.1. PARTICIPANTS**

Fifteen native English speaking volunteers (aged 24.7 ± 4.1 years; 8 females) took part in the study. In addition to these participants three subjects were tested but excluded because of technical failure or performance below chance-level. The participants all gave written informed consent, and the study was approved by the joint ethics committee of the Institute of Neurology and University College London Hospital, London, UK.

#### **2.2. STIMULI AND TASK DESCRIPTION**

Each subject took part in a total of six experimental sessions, and each session comprised a priming part followed by a ruleassociation part. We used a within-subject design where each participant was primed both with associations to "clever" and "stupid." The order of the priming categories was counterbalanced between participants; the participants begun with either three consecutive sessions that involved the "clever" prime or three consecutive sessions that involved the "stupid" prime. The participants were primed using the scrambled sentence task (Bargh and Chartrand, 2000). In our study, each scrambled sentence consisted of six words and participants judged whether or not it could be made into a grammatically coherent sentence by using five of the six words. The participants responded "yes" by pressing a button corresponding to their right index finger or "no" by pressing a button corresponding to their right middle finger on a button-box. Each sentence was presented for 8000 ms during which time the participant had to respond. In each session, 70% of the sentences had words that were synonyms for either "clever" or "stupid," and 30% of the sentences were neutral. The neutral sentences were introduced in accordance with the description of Bargh and Chartrand (2000), with the aim to disguise the purpose of the language task. Examples of sentences in the "clever" condition are "pupil intelligent Todd and his pencil" and "the brightest nothing idea everything promoted," and examples of sentences in the "stupid" condition are "welcome not morons one are here" and "the room obtuse had white green."

We measured the effect of the priming on response time (RT) and error-rate on a computer-based rule-association task (Crone et al., 2006) (**Figure 1**). In this task, participants were asked to respond to targets that could be either "bivalent" or "univalent." Bivalent targets refer to visual targets that were associated with different responses depending on which of two rules is currently relevant. The outcome of the response target was to either press the left or the right button. The univalent target was associated with fixed responses. A rule cue was presented on a computer screen for 1000 ms, this was followed by a blank screen for 500 ms before the response cue appeared. A pause of 2000–8000 ms occurred before the next rule cue was presented. For example, if the rule cue consisting of four triangles (**Figure 1**) was followed by a butterfly (response cue) the participant should press the right button on the keypad, whereas if the star appeared as the rule cue (**Figure 1**) and was followed by a butterfly (response cue) the participant should press the left button. The task consisted of a distribution of 70% bivalent cues and 30% univalent cues in randomized order, which gives roughly the same number of presentations of each rule cue. There was no particular hypothesis for modulation of expectancy. We followed approximately the distribution used in Crone et al. (2006).

Eight scrambled sentences were presented followed by a sequence of 50 rule trials. This constitutes a session and there were three consecutive sessions for each prime (clever and stupid). Prior to data collection, participants practiced the rule task for 80 trials, and the language task for 20 trials, with all the sentences being of neutral character. The data was analyzed using custom written Matlab scripts (Matlab r2010a, The Math Works, Natick, MA, USA). The participants performed the task inside an fMRI-scanner

and performed a second task after the above described paradigm but these data will be presented elsewhere.

To disguise a link between the two tasks, we told the participants that we would alternate between a language task and a rule task. Our explanation was that the experimenters had long experience of participants getting bored during experiments, and this was a way to prevent this from happening. After the experiment the participants were debriefed as to whether they thought any of the tasks would influence performance on the other task, and whether they noticed any theme in the sentences. The debriefing was adapted from Bargh and Chartrand (2000) to fit with the present tasks. None of the participants reported any link between the two tasks. One participant reported that the sentences had either a positive or a negative character, another participant reported that some sentences had words related to "clever" in them. However, none of these participants reported any understanding that one task would influence the other. Therefore, these participants were included in the analysis. After the experiment the participants also filled out the Rosenberg Self-esteem scale (Rosenberg, 1965), which is a 10-item questionnaire measuring the participant's general explicit self-esteem, and the State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983) which consists of 40 questions on anxiety.

#### **2.3. BEHAVIORAL DATA ANALYSIS**

As mentioned in the Section "Introduction," a delay in RT on a correct trial after an error is often observed in cognitive task performance, and is suggested to reflect participants' control over behavior (Rabbitt, 1966). In the present paper we consider two types of trials; correct following correct (CC) and correct following error (EC). Reaction times on CC trials are referred to as RTs after correct, and on EC trials as RTs after error. We do not consider RTs on error trials themselves because generally these may vary substantially, without known cause.

First we looked at the overall RTs for CC trials and EC trials respectively. We then organized data from "early" and "late" trials using an epoch length of *N*CC for CC trials and an epoch length of *N*EC for EC trials. Here "epoch length" refers to the number of trials that define the early and late periods. Fewer trials are used for the EC category due to the smaller number of errors than corrects. We present results obtained with *N*CC = 20 and *N*EC = 3 although our effects are robust over a range of parameters. This means that the first twenty CC trials of the first session were compared with the last twenty CC trials of the third session for each priming category (clever/stupid), and the first three EC trials of the first session were compared to the last three EC trials of the third session for each priming category. The data was compared using Student's paired *t*-tests.

We investigated accuracy for each priming category by computing the mean error rates in percent for each of the three sessions, and made pairwise comparisons between sessions within a priming category as well as between priming categories using two-tailed paired *t*-tests.

We also investigated whether there was any correlation between RT and correct rate. RT was first aggregated over participants with subject means subtracted. We then regressed these RTs onto error rate, using data from sessions 1 and 3.

In addition, we investigated if there was any correlation between scores on the psychometric questionnaires (Rosenberg's selfesteem questionnaire and the STAI) and the difference in error rate between late and early sessions after "stupid"-priming, the mean error-rate after "clever"-priming, as well as the difference in RT between late and early sessions after "stupid"-priming.

## **2.4. COMPUTATIONAL MODEL**

#### **2.4.1. Rule-association task**

Here we describe a model of the bivalent trials of the ruleassociation task. We focus on the bivalent,rather than the univalent trials, as the latter were not affected by priming (see Results).

For the bivalent trials participants must remember and act on a rule. For rule A, participants should press the left button when the tree cue appears and the right button when the butterfly cue appears. For rule B, participants should press the right button when the tree cue appears and the left button when the butterfly cue appears. Which rule is active is indicated by one of two rule symbols presented earlier (**Figure 1**). Success requires that neural circuits in the motor system integrate information from working memory about which rule is active (A or B) with information from the visual system about which cue is present (tree or butterfly). We call these two processes "memory" and "response accumulation." The term accumulate refers to Evidence Accumulation (EA)-type models established in decision theory in which evidence is accumulated until a threshold is reached and an action is triggered (Gold and Shadlen, 2001). These models are reviewed in Bogacz et al. (2006). We denote successful rule memory with *m<sup>t</sup>* = 1 and successful response accumulation with *c<sup>t</sup>* = 1 where *t* refers to trial

number. We denote the probabilities of these events as

$$\begin{aligned} p(m\_t = 1) &= \pi \\ p(c\_t = 1) &= \beta\_t \end{aligned} \tag{1}$$

We also refer to π as memory integrity. The quantity β*<sup>t</sup>* is also referred to as the decision threshold (see below).

Both of the processes being correct leads to a correct outcome on that trial, *b<sup>t</sup>* = 1. Importantly, we note that a correct outcome can also be achieved by incorrect memory *m<sup>t</sup>* = 0 and incorrect cue integration *c<sup>t</sup>* = 0, i.e., a "fluke." If the two processes are independent then the probability of the various combinations *p*(*m*, *c*) follows from the standard rules of probability theory (Wackerly et al., 1996) as shown in **Figure 2**. The probability of a correct outcome is given by

$$\begin{split} r\_t &= p(b\_t = 1) \\ &= \beta\_t \pi + (1 - \beta\_t)(1 - \pi) \end{split} \tag{2}$$

We assume that our normative participant knows the outcome of a trial. In our experiment no explicit feedback was given to the participants as to whether they were correct or incorrect on a given trial. However, on tasks that encourage quick responses participants are often aware of making an error at the time they respond (Rabbitt, 1966). We also know from imaging studies that there is error related activation in the mid-anterior cingulate cortex (mid-ACC) when people make errors without receiving external feedback (Bengtsson et al., 2011). We therefore assume that the normative subject has access to this information.

Our normative subject does not, however, know whether memory for the task or response accumulation were correct on that trial. They can however infer the probabilities of these events using Bayes rule (Bernardo and Smith, 1993). After a given outcome, the probability that response accumulation was incorrect can be computed. These *posterior* probabilities are given by Bayes rule and can be read off from **Figure 2**.

**FIGURE 2 | On each trial, memory m of the rule is either correct or incorrect, and accumulation c is either correct or incorrect**. The figure shows the four possible combinations of these events. There are thus two ways in which a correct outcome can be produced, and two ways in which an incorrect outcome (error) can be produced. If π is the probability of correct memory, β the probability of correct integration, and these two events are independent, then the probabilities of the joint events p(m, c) are given as in the figure.

$$p(c\_t = 0 | b\_t = 0) = \frac{(1 - \beta\_t)\pi}{(1 - \beta\_t)\pi + \beta\_t(1 - \pi)}\tag{3}$$

$$p(c\_t = 0 | b\_t = 1) = \frac{(1 - \beta\_t)(1 - \pi)}{(1 - \beta\_t)(1 - \pi) + \beta\_t \pi} \tag{4}$$

#### **2.4.2. Adaptive decision threshold**

A consistent finding in the decision-making literature is that individuals generally slow down their response following an error so as to regain control over behavior (Rabbitt, 1966). In the context of evidence accumulation models of decision making, one mechanism for delaying responses is to increase the decision threshold. Indeed, the idea that decision thresholds are adaptively updated has been explored in the decision-making literature (Bogacz et al., 2006; Simen et al., 2009). These adaptive thresholding processes have been studied in the context of simple two-alternative forced choice (2AFC) tasks (for a review, see Bogacz et al., 2006). One algorithm for adapting the decision threshold is to decrease it if the previous trial was correct and increase it if the previous trial was incorrect (Myung and Busemeyer, 1989). However, such an approach is not straightforwardly implemented in more complex decision tasks.

For example, in the rule-association task used in this paper, an incorrect trial outcome may not be due to incorrect evidence accumulation. An incorrect outcome may rather be due to faulty working memory. Therefore, before deciding whether to increase or decrease the decision threshold it is necessary to *infer* whether the accumulation process was correct or incorrect. We propose that, for normative subjects, this inference is made using Bayes rule and refer to the resulting process as Bayesian Adaptive Thresholding (BAT).

In this paper we use a simple two-state model for this adaption process which provides two levels of decision threshold (or "accumulation success"); low and high, denoted by β[1] and β[0]. If response accumulation was inferred to be incorrect on the current trial then the decision threshold for the next trial should assume the high level. Similarly, if it was inferred to be correct then a low threshold will be used on the following trial. This is the specific BAT process assumed in this paper. The price to pay for using a high threshold is that the response will be delayed and this relation can be quantified using a reaction time model (see next section). One might also conceive of a BAT process in which β*<sup>t</sup>* is continuously updated. We have, however, focused on a discrete model as it relates more directly to the behavioral results (specifically the early to late double dissociation reported in Section 3.1.3).

To incorporate the adaptive threshold into our model we substitute β*<sup>t</sup>* = β[*ct*-1] into equations (2–4). For example, the outcome probability from equation (2) becomes

$$p(b\_{t} = 1 | \boldsymbol{\varepsilon}\_{t-1}) = \beta [\boldsymbol{\varepsilon}\_{t-1}] \pi + (1 - \beta [\boldsymbol{\varepsilon}\_{t-1}])(1 - \pi) \tag{5}$$

This shows that the outcome on the current trial depends on whether participants believed response accumulation was successful on the previous trial. In Section 2.5 below we show how this relation can be used to write down the likelihood of an outcome sequence. This quantity is necessary for estimating model parameters from data.

#### **2.4.3. Reaction time model**

We use an Evidence Accumulation (EA)-like model to describe the process of integrating working memory with sensory input (Gold and Shadlen, 2001). EA or Drift Diffusion Models (DDMs) describe how evidence is accumulated until a threshold is reached and then an action is triggered. Specifically, the quantity that is accumulated is the log odds ratio, log *p*/[1 − *p*] where *p* is the probability with which it is believed one should make a specific response (e.g., left button press). These models are known to be optimal for 2AFC decision tasks (Bogacz et al., 2006). Gold and Shadlen (2001) review a large body of work in which neural firing rates on 2AFC tasks are seen to correlate with log odds ratios.

For the rule-association task employed in this paper it is not clear, however, that such simple EA models are optimal. Recently Yu et al. (2009) have described a normative model of the Eriksen Flanker task, and in later work (Liu et al., 2009) they also provide a connection to DDMs from which they derive semi-analytic formulae for reaction times and error rates. We note that a similar approach is possible for the bivalent rule-association task where, mathematically, the rule cue rather than the flankers act as the "context" variable. The univalent rule-association task is a 2AFC task. Switching between the univalent and bivalent conditions requires an additional task-switching process.

We have outlined how the above approach can be applied to the rule-association task in ongoing, unpublished work (Bengtsson and Penny, 2013). This has motivated us to assume that the average reaction time is proportional to a log-odds ratio threshold (this is the case for simple EA models and the approach described in Bengtsson and Penny, 2013). That is, the likelihood of RT data, *y*, is given by

$$p(\boldsymbol{y}\_t|\boldsymbol{c}\_{t-1}) = N(\boldsymbol{y}; \mu\_{\boldsymbol{y}}, \sigma\_{\boldsymbol{y}}) \tag{6}$$

$$\mu\_{\boldsymbol{y}} = \mu \theta\_T$$

$$\theta\_T = \log\left(\frac{\beta[\boldsymbol{c}\_{t-1}]}{1 - \beta[\boldsymbol{c}\_{t-1}]}\right)$$

where µ is the evidence accumulation slope, and θ*<sup>T</sup>* is the logodds ratio threshold. Larger β values produce higher θ*T*'s and thus longer RTs. The β[0] and β[1] values described earlier therefore produce a short and a long average RT, as depicted in **Figure 3**.

#### **2.4.4. Me-Focus**

A complementary view on the inferential process subsequent to an outcome is the extent of "me-focus." This is the extent to which a subject identifies themselves with the outcome of a trial. In our experimental context we hypothesize that the self is most strongly associated with the memory process. The extent of "me-focus" can therefore be quantified by the probability *p*(*m<sup>t</sup>* = *b*|*b*). For correct and incorrect outcomes these are given by

$$p(m\_t = 0 | b\_t = 0) = \frac{\beta\_t (1 - \pi)}{(1 - \beta\_t)\pi + \beta\_t (1 - \pi)}\tag{7}$$

$$p(m\_t = 1 | b\_t = 1) = \frac{\beta\_t \pi}{(1 - \beta\_t)(1 - \pi) + \beta\_t \pi} \tag{8}$$

We conclude this section with a brief summary of the model assumptions. We have assumed (a) that our behavioral task

embodies two processes (i) memory: remembering a rule for how to behave and (ii) response accumulation: integrating stimuli with rule memory to produce an appropriate response, (b) the decision threshold for the response accumulation process adapts over trials by switching to a higher value if accumulation was inferred to be incorrect on the previous trial, (c) mean reaction time is proportional to a log-odds ratio (log β/[1 − β]). The adaptive thresholding procedure follows from an application of Bayes rule (Bernardo and Smith, 1993) and the reaction time model is based on similar properties of 2AFC (Bogacz et al., 2006) and contextual decision-making tasks (Liu et al., 2009).

#### **2.5. MODEL LIKELIHOOD**

This section describes how the behavioral data on error rates and reaction times can be related to model parameters such as memory integrity and accumulation thresholds.

#### **2.5.1. Outcome likelihood**

The outcome on the current trial depends on whether we believed accumulation was correct on the previous trial. This in turns depends on the outcome of that trial and whether we believed accumulation was correct on the trial before that. The probability of an outcome sequence comprising, for example, *T* = 3 trials *b* = {*b*1, *b*2, *b*3} is therefore given by the product

$$p(b|\pi,\beta) = p(b\_3|b\_2, b\_1)p(b\_2|b\_1)p(b\_1)\tag{9}$$

where

$$p(b\_3|b\_2, b\_1) = \sum\_{c\_2} \sum\_{c\_1} p(b\_3|c\_2) p(c\_2|c\_1, b\_2) p(c\_1|b\_1) \tag{10}$$

$$p(b\_2|b\_1) = \sum\_{c\_1} p(b\_2|c\_1) p(c\_1|b\_1)$$

As the sequence grows in length one can see that computation of the likelihood becomes exponentially expensive, because the number of terms in equation (10) grows as 2(*<sup>T</sup>* <sup>−</sup> 1) .

#### **2.5.2. Low-order approximation of outcome likelihood**

However, it turns out that these (*T* − 1)th-order conditional probabilities can be adequately approximated by lower-order conditional probabilities. We use the first order approximation

$$p(b\_t | b\_{t-1}, \dots, b\_1) \approx p(b\_t | b\_{t-1}, c\_{t-2} = 1)\tag{11}$$

That is, by assuming that accumulation was correct on the trial before last (its more likely to be correct than not, unless π and β are very low). Under this approximation the outcome on trial *t* then depends on the outcome at *t* − 1 only

$$p(b\_t | b\_{t-1}, c\_{t-2} = 1) = \sum\_{c\_{t-1}} p(b\_t | c\_{t-1}) p(c\_{t-1} | c\_{t-2} = 1, b\_{t-1}) \tag{12}$$

assuming *c*<sup>0</sup> = 1. The likelihood of a sequence of outcomes, *b*, is then given by

$$p(b|\pi,\beta) \approx p(b\_1) \prod\_{t=2}^{T} p(b\_t|b\_{t-1}, c\_{t-2}=1) \tag{13}$$

#### **2.5.3. Joint likelihood**

The likelihood of outcomes, RTs, and integration sequence is given by

$$p(b, \boldsymbol{y}, \boldsymbol{c} | , \boldsymbol{\pi}, \boldsymbol{\beta}) = \prod\_{t=1}^{T} p(b\_t | \boldsymbol{c}\_{t-1}) \prod\_{t=1}^{T} p(\boldsymbol{c}\_t | \boldsymbol{c}\_{t-1}, b\_t) \prod\_{t=1}^{T} p(\boldsymbol{y}\_t | \boldsymbol{c}\_{t-1}) \tag{14}$$

From this we can compute the joint likelihood of outcomes and RTs

$$p(b, \boldsymbol{\wp}|, \boldsymbol{\pi}, \boldsymbol{\beta}) = \sum\_{i=1}^{2^{\boldsymbol{T}}} p(b, \boldsymbol{\wp}, c\_i | , \boldsymbol{\pi}, \boldsymbol{\beta}) \tag{15}$$

and the likelihood of an integration sequence

$$p(c\_i|b, \boldsymbol{\uprho}, \boldsymbol{\uppi}, \boldsymbol{\upbeta}) = \frac{p(b, \boldsymbol{\uprho}, c|, \boldsymbol{\uppi}, \boldsymbol{\upbeta})}{p(b, \boldsymbol{\uprho}|, \boldsymbol{\uppi}, \boldsymbol{\upbeta})} \tag{16}$$

Equation (15) again involves an exponentially expensive summation. But we can use the same low-order approximation as before, this time to approximate the joint likelihood. This lowerorder approximation has been validated by comparing exact and approximate likelihoods on short data sequences (e.g., *T* = 10). We have also generated synthetic data and found that the approximate likelihood is maximized by values that are very similar to the true known parameter values.

#### **2.5.4. Reaction time likelihood**

We can integrate out the variable *c<sup>t</sup>* <sup>−</sup> <sup>1</sup> to see how reaction time is dependent on the outcome of the previous trial (assuming that integration was correct on the trial before that)

$$p(y\_t | b\_{t-1}, c\_{t-2} = 1) = \sum\_{c\_{t-1}} p(y\_t | c\_{t-1}) p(c\_{t-1} |, c\_{t-2} = 1, b\_{t-1}) \tag{17}$$

#### **2.6. MODEL FITTING**

The following model fitting procedure used a Bayesian estimation algorithm (Gelman et al., 1995) to estimate model parameters from behavioral data. The work in this paper is therefore Bayesian in two ways (i) providing a computational model of subject behavior and (ii) estimating the parameters of that model from data.

#### **2.6.1. Fitting group data**

We fit the Bayesian model to data from the group of participants as follows. We focus on a main empirical finding of the paper; that for the stupid prime, the RTs after correct responses are negatively correlated with correct response rate (see Section 3.1.2). We used the model to regress RTs *y* onto correct rates, *r:* first, we inverted equation (2) to write π as a function of β and *r*

$$
\pi(\beta, r) = \min\left(1, \frac{r - 1 + \beta}{2\beta - 1}\right) \tag{18}
$$

where the *min* operator is required to ensure that π < 1. The value of β to be used depends on whether or not response accumulation was inferred to be correct on the previous trial. But for the purpose of the group model fitting we used the approximation β = β<sup>1</sup> (accumulation assumed correct on previous trial, i.e., *c<sup>t</sup>* <sup>−</sup> <sup>1</sup> = 1). Second, we used equation (17) to relate β[1], β[0], µ, and π(β, *r*) to expected RT (this integrates over *c<sup>t</sup>* <sup>−</sup> <sup>1</sup> but assumes *c<sup>t</sup>* <sup>−</sup> <sup>2</sup> = 1). Model fit was then assessed using the squared difference between these expected RTs and the actual RTs. Log model likelihood was defined equal to negative model error. We then employed a Bayesian estimation procedure with uniform priors

$$p(\beta[1]) = U(0.5, 1)\tag{19}$$

$$p(\beta[0]) = U(0.5, 1)$$

$$p(\mu) = U(50, 1000)$$

where *U*(*a*, *b*) denotes a uniform density with minimum and maximum values *a* and *b.* The posterior parameter density *p*(β[1], β[0], µ|*y*, *r*) was then estimated using a Metropolis-Hastings algorithm (Gelman et al., 1995) with 20,000 iterations. The first 10,000 samples were discarded to accommodate burn-in effects. The remaining 10,000 samples then comprise our approximation to the posterior density.

#### **2.6.2. Fitting individual subject data**

We fitted the model to both RT and outcome data from the first and last sessions. This was implemented separately for each subject and type of priming (stupid or clever). The memory integrity variable π was allowed to be different for the two sessions; π<sup>1</sup> (first) and π<sup>2</sup> (last). The likelihood of a model was approximated as described above. We then employed a Bayesian inference procedure with uniform priors

$$\begin{aligned} p(\pi\_1) &= U(0,1) \\ p(\pi\_2) &= U(0,1) \\ p(\beta[1]) &= U(0.9,0.94) \\ p(\beta[0]) &= U(0.999,1) \end{aligned}$$

$$p(\mu) = U(310,420)$$

where the priors over β[1], β[0], and µ are constrained by the results of the group analysis (see Section 3.2.3). The posterior parameter density was then estimated using the Metropolis-Hastings algorithm with 20,000 iterations. The first 10,000 samples were again discarded to accommodate burn-in effects. We also computed the posterior mean for each subject and type of priming and used two-way paired *t*-tests to test whether memory integrity varied over sessions. This was implemented separately for the stupid and clever prime data. We hypothesize that priming affects memory integrity.

# **3. RESULTS**

## **3.1. BEHAVIORAL RESULTS**

We first analyzed the univalent trials, and found no significant difference between the two primes in the number of errors; stupid (6.9 ± 1*.*8) and clever (6.0 ± 0.6). All the data analyses and modeling that follow therefore relate to the bivalent trials.

# **3.1.1. Error rates by session**

When participants are primed "stupid" the mean error rates are 7, 12, and 18% for sessions 1–3. They are significantly different between sessions 1 and 2 (*p* = 0.01, *t* = 2.98, *df* = 14), 2 and 3 (*p* = 0.02, *t* = 2*.*6, *df* = 14), and 1 and 3 (*p* < 0.01, *t* = 3.37, *df* = 14). Thus, we observed that when "stupid"-associations are evoked participants' performance becomes increasingly worse whereas when participants are primed "clever" the mean error rates are 8, 9, and 8% for sessions 1–3 (no significant differences). We refer to this as a confirmation bias. Additionally, we find that only in session 3 are stupid error rates significantly higher than clever error rates (*p* < 0.01, *t* = 3.54, *df* = 14). Boxplots of these effects are shown in **Figure 4**. These effects remain significant if the outlying participant (participant 10 – see small circles in top row of **Figure 4**) is removed.

# **3.1.2. Stupid prime: reaction time versus error rate**

Since we had observed that the correct rate was deteriorating over time when participants had been primed stupid we investigated whether there was any correlation between RT and correct rate for this condition. RT was first aggregated over participants with subject means subtracted. We then regressed these RTs onto error rate, using data from sessions 1 and 3. For RT after errors we obtained (*r* = −0.03, *p* = 0.81) and for RT after corrects (*r* = −0.41, *p* = 0.001). For every percentage point decrease in correct rate there is a 5 ms increase in RT (after corrects). The same pattern of results was found using data from all sessions and after removing an outlying participant.

# **3.1.3. Reaction times in early versus late epochs**

We now focus on the early and late epochs for both priming conditions. The overall mean RT is 848 ms. RTs for clever are significantly longer than for stupid (874 ms versus 822 ms, *p* = 0.03, *t* = 2.03, *df* = 14). For EC trials there is a significant early to late increase when participants are primed clever (*p* = 0.01, *t* = 2.4, *df* = 14), but not when they are primed stupid (*p* = 0.22, *t* = 0*.*80, *df* = 14). For CC trials there is a significant early to late increase when participants are primed stupid (*p* = 0.03, *t* = 2.03, *df* = 14), but not when they are primed clever (*p* = 0.39, *t* = 0.30, *df* = 14). We refer to this as an early to late double dissociation. RTs for EC and CC trials are shown in **Figure 5**.

It is only when looking at performance over time that we can disentangle the differences between the two mental states. Looking at the overall RTs for CC trials there was no significant difference between stupid and clever (871 ms versus 905, *p* < 0.14, *t* = 1.09, *df* = 29). For EC trials there was a trend for stupid being shorter than clever (773 ms versus 842, *p* < 0.07, *t* = 1.51, *df* = 29).

#### **3.1.4. Correlation between psychometric scores and behavior**

We did not find any significant correlation between psychometric scores and behavior. Difference in error rate between late and early sessions after "stupid"-priming (Rosenberg: *r* = −0.26, *p* = 0.36; STAI: *r* = 0.11, *p* = 0.71), the mean errorrate after "clever"-priming (Rosenberg: *r* = −0.32, *p* = 0.25; STAI: *r* = −0.42, *p* = 0.17), the difference in RT between late and early

red line indicates the median, the edges of the box are the 25th and 75th

in the top row are all from participant 10.

sessions after "stupid"-priming (Rosenberg: *r* = −0.11, *p* = 0.71; STAI: *r* = 0.24, *p* = 0.45).

"stupid" (p = 0.22, solid line). (Right) Reaction times (ms) after

#### **3.2. MODELING RESULTS**

We first present a number of qualitative features of the model, and then make inferences about model parameters from data fitting.

#### **3.2.1. Inferring faulty accumulation**

Equations (3 and 4) give the probability of inferring that the process of integrating the visual cue with memory for the rule (the response accumulation process) was faulty, given an error or a correct response on that trial. **Figure 6** (Left) shows how these two probabilities, *p*(*c* = 0|*b* = 0) and *p*(*c* = 0|*b* = 1), vary with memory integrity, π. From the red curve it can be seen that participants will be more likely to attribute an error (*b* = 0) to faulty response accumulation (*c* = 0) as π increases. Similarly, from the blue curve, we see they will be more likely to attribute a correct response (*b* = 1) to faulty response accumulation as π decreases. If we assume that priming influences π, and further that "stupid" priming reduces π and "clever" priming increases it, then the above mechanism will cause the double dissociation observed in the early-late RT data. The negative slope of the blue curve then provides a simple explanation of the negative correlation between RT after corrects and correct rate (see Section 3.1.2).

#### **3.2.2. Me-focus**

The extent of me-focus is quantified by the probability *p*(*m* = *b*|*b*), given in equations (7 and 8), and shown in **Figure 6** (Right), subsequent to error outcomes (red curve) and correct outcomes (blue curve). Increasing π increases me-focus after correct and decreases me-focus after error. Thus, when primed clever, the attribution of an outcome to the self is increased after correct and decreased after an error.

#### **3.2.3. Fitting group data**

We now focus again on a main empirical finding of the paper; that for the stupid prime, the RTs after correct responses are negatively correlated with correct response rate (see Section 3.1.2). We fitted

are primed "stupid" (p = 0.03, solid line, \*), but not when they are primed "clever" (p = 0.39, dotted line). Error bars indicate the standard error of the mean.

the computational model to this data by regressing RTs *y* onto correct rates, *r,* as described in Section 2.6. A Metropolis-Hastings procedure was used to obtain 10,000 samples from the posterior density *p*(β[1], β[0], µ|*y*, *r*). **Figure 7** shows 1000 samples from this posterior; the ones that produce the best 10% of model fits. The middle plot shows a negative posterior correlation between µ and β[1]; i.e., the same model fit can be achieved by increasing µ and decreasing β[1]. Nevertheless, we can be confident that, e.g., 0.9 < β[1] < 0.94 and 310 < µ < 420. Importantly, we can be highly confident that β[0] > β[1] indicating that inferred faulty response accumulation does indeed cause an increase in the decision threshold for the next trial. In what follows we use the high probability parameter values β[1] = 0.92, β[0] = 0.9998, and µ = 360.

## **3.2.4. Confirmation bias**

If participants act as ideal Bayesian observers and update their beliefs about π then one will observe a confirmation bias effect. For example, if priming acts to induce a prior distribution over π and this prior places more probability mass on smaller values of π than does the likelihood, then posterior values will be lower than the maximum likelihood value. If this Bayesian updating mechanism operates, e.g., between sessions then the performance in the second session will be worse than in the first. In other words, if you think you're going to do badly then you will.

We provide a numerical example of confirmation bias based on data from a single participant (participant 11). We used outcome data *b* from the first session for when this participant was primed stupid. We used the β values obtained from the group parameter estimation (previous section). The likelihood *p*(*b*|π) = *p*(*b*|π*,*β) can be computed as described in Section 2.5.

The temporal scale of hypothesized Bayesian updating in the brain is unknown. It could happen discretely after each session or may be a slow process that is continually in operation. In our numerical example we compute the likelihood based on the first 10 outcomes only (9 of which were correct). This is for numerical convenience only as this small number of outcomes allows us to use the exact likelihood rather than an approximation to it

**FIGURE 6 | Inferring faulty accumulation (left) participants are more likely to attribute errors (b** = **0) to incorrect accumulation (c** = **0) for larger values of** π **(red curve).** Conversely, participants are more likely to attribute correct responses (b = 1) to incorrect accumulation for smaller values of π (blue curve). These curves were computed from equation (3) (red) and equation (4) (blue) with a value of β<sup>t</sup> = 0.9. The blue and red

curves take on values 0 and 1 at π = 1 (perfect rule memory). The value 1 − β<sup>t</sup> determines the intercept at π = 0.5 and thus controls the gradient of each of the above effects. Me-focus (Right) The extent of a subjects "me-focus" is quantified by the probability p(m = b|b) shown here subsequent to error outcomes, b = 0 (red curve) and correct outcomes, b = 1 (blue curve).

(see Section 2.5). This likelihood is plotted as the blue curve in **Figure 8**.

We then hypothesize that the stupid prime takes the form of the black curve in **Figure 8**. This was implemented using a beta density (Bernardo and Smith, 1993). The posterior density *p*(π|*b*) is then computed using Bayes rule and is shown as the red curve, which clearly exhibits a confirmation bias. The particular form of the prior density here, e.g., beta density, is unimportant for our

argument. As longs as the prior places more probability mass on smaller values of π than does the likelihood, a confirmation bias will ensue.

## **3.2.5. Fitting individual subject data**

We first present individual subject results for the three participants showing the largest confirmation bias effect (participants 2, 10, and 11). **Figure 9** shows the posterior distributions for the π<sup>1</sup> and π<sup>2</sup> parameters. We can be confident that π<sup>2</sup> < π<sup>1</sup> for each participant. This shows that the confirmation bias effect is consistent with a reduction in π, i.e., is consistent with a priming effect mediated by a change in π.

We then used a two-way paired *t*-test to test whether memory integrity varied over sessions for the group of 15 subjects. This analysis was based on the posterior mean estimates of memory integrity. For the stupid prime data there was a significant difference between sessions (mean π<sup>1</sup> = 0.88, mean π<sup>2</sup> = 0.80, *p* = 0.02, *t* = 2.63, *df* = 14). For the clever prime data there was no significant difference between sessions (mean π<sup>1</sup> = 0.85, mean π<sup>2</sup> = 0*.*88,*p* = 0.25,*t* = 1.2,*df* = 14). This confirms our hypothesis that priming affects memory integrity: stupid priming significantly reduces π whereas clever priming does not significantly affect it.

# **4. DISCUSSION**

In this paper we provide novel behavioral findings of how attention to the cognitive task can be changed depending on which selfconcept is currently active in mind. We observed a double dissociation between outcome (errors/corrects) and prime (clever/stupid). We augmented this finding by providing empirical evidence that Bayesian principles can be applied to self-regulatory processes such as "feeling stupid" and "feeling clever." This strengthens the theory that, in the healthy individual, inner standards of ability beliefs are clearly defined structures (Kelly, 1955; Markus, 1977). Our findings are important because they demonstrate that the way self-concepts regulate behavior is based on the same general principles that guide decision-making processes on many levels (Doya et al., 2007).

Our model is simple in that it make use of two processes. One process refers to remembering which rule is active. This is a working memory process and as such it is a top-down process. The other process refers to the motor system integrating information from working memory with information from the visual system

about which cue is present. The basic model then derives from the logic of the experimental task, whereby the task can be implemented correctly if both processes are either correct or if both are incorrect. As these processes are correctly implemented with some level of probability, Bayesian inference can be used to quantify the effects of changing these probabilities. Additionally, the model also incorporates an adaptive decision threshold based on Bayes rule, whereby decision thresholds are increased if integration was inferred to be faulty. We refer to this as Bayesian Adaptive Thresholding (BAT).

This paper hypothesized that priming affects the memory process. We were able to test this hypothesis by fitting our computational model to subjects' behavioral data. Our results showed that stupid priming significantly reduces memory integrity (π) whereas clever priming does not significantly affect it. The Bayesian Adaptive Thresholding scheme, combined with the effect of priming on memory, then explains a main experimental finding of the paper; the early-to-late double dissociation in reaction times.

When participants are primed "clever" and make an error they are more likely to attribute the mistake to a fault in the motorintegration process rather than the working memory process, and will increase their decision threshold on the next trial so as to increase the likelihood of correct evidence accumulation. This naturally leads to a longer RT after an error response. Conversely, following priming with associations to "stupid," the participants believe they have worse memory, and are therefore more likely to attribute an error to a fault in the working memory process. As a consequence, they will not increase their decision threshold on the next trial and thus not delay RT. The uncertainty in topdown processing seen for "stupid" makes them more likely than those primed "clever" to attribute correct responses to a "fluke," in which both the working memory and the evidence accumulation processes are considered faulty. They tend to increase their decision threshold, and produce a longer RT on the next trial.

The lack of confidence in the participants' memories after "stupid"-priming also explains why if you think you are going to do badly then you will (the confirmation bias); they should slow down after making an error but do not, and so continue to make errors. In other words, prior beliefs about performance are combined with estimates of actual performance (the "likelihood") to set future levels of memory performance that are consistent with both. Since the priming is implemented via this prior, if the participants act as ideal Bayesian observers, their future performance will be determined by how the prior is affected by the prime. When participants have been primed "stupid" they place more probability mass on smaller values of memory integrity. Since this prior here places lower values on memory performance than does the likelihood, the performance deteriorates over the course of the experiment. This is analogous to leading psychological theories of self-regulation which stipulate that for consistency and predictability of self the discrepancy between self-ability beliefs and behavior is reduced (Bandura, 1982; Carver and Scheier, 1998). These theories are based on numerous behavioral findings, one example being an experiment where women who were told that females perform badly on math tasks then went on to perform worse than they would otherwise do (Spencer et al., 1999). We did not observe a change in performance level after "clever"-priming and suggest that this is because performance was commensurate with their beliefs; they did well and expected to do so.

We find further that when participants are primed "clever" they readily switch between attributing the cause of outcome to either of the processes. When the same participants are primed with associations of being "stupid" inferring the cause of outcome becomes less distinct. A complementary view on the inferential process subsequent to an outcome is the extent to which a participant identifies themselves with the outcome of a trial. Since memory integrity is in concordance with the influence of the prime it can be assigned "me-focus." The integration process on the other hand, is a system which is not directly affected by priming, and can therefore be interpreted as "task-focused." When associations to "clever" are active, in situations of making errors, the participants will readily reduce their me-focus and place emphasis on task processes; a mechanism that may reflect the discrepancy between their expectation and their actual performance. When making errors following "stupid"-priming the participants are more likely to attribute errors to a faulty memory process,i.e.,me-focus,as well as to think of correct responses as flukes. This finding is supported by previous studies showing that depressed individuals (Greenberg and Pyszczynski, 1986) and low self-esteem individuals (DiPaula and Campbell, 2002) are more likely to persist in higher levels of self-focus after failure over time. Our model assumes the existence of these two processes but we have not directly observed them. The causes underlying the behavioral differences elicited by our priming study can, more generally, be described in terms of state characteristics and more enduring characteristics. Here the enduring characteristics are defined as stable, relatively general characteristics of the self that are consistent across situations, whereas states are transient characteristics that can change from moment to moment. Our model allows us to operationalize these definitions such that the"state"corresponds to the inferred state of the memory process (correct or not) and integration process (correct or not). The state thus changes from trial to trial. Whereas, the more enduring characteristic corresponds to the subject's memory integrity, which changes on a longer time scale (e.g., session to session).

This paper has focused on the effect of priming on a very specific behavior – performance in a rule-association task. However, we have reason to expect that our computational approach will itself generalize, or can easily be generalized, to other behaviors. The core ideas of our approach are that (i) task performance depends on two component processes: a memory process and an evidence accumulation process, and that multiple combinations of the component processes can produce a correct outcome (e.g., both correct or both incorrect) (ii) after a trial, Bayesian inference is used to infer whether evidence accumulation was correct, and the decision threshold for the next trial is set accordingly. This model could be directly applied for example, to 1-back working memory tasks (match current to previous item), or the AX continuous performance tasks (press left if X follows A – the "target" is AX, right otherwise; Braver and Cohen, 2000). For more complex tasks such as n-back working memory (n > 1) one may conceive of multiple memory processes (one for each of the n previous items) instead of a single memory process. Or for the "12AX" task (if the last numeral you saw was a 1, the target sequence is "AX," if a 2 its "BY"; Frank et al., 2001) we may again need multiple memory

processes (one for last letter, one for last numeral). Nevertheless, for all of these cases, it will be possible to use Bayes rule to infer whether the evidence accumulation process was correct and so derive an appropriate Bayesian Adaptive Thresholding scheme.

One weakness of our study is that we did not use a reaction time model derived from optimality principles, rather we simply assumed that RTs were normally distributed with a mean reaction time being proportional to the log-odds ratio of the decision threshold. This is known to be a correct assumption for 2AFC tasks, and the rule accumulation task (Bengtsson and Penny, 2013). Our decision to use this rather simple model was motivated by the fact that the focus of this paper is on between-trial rather than within-trial dynamics (i.e., investigation of BAT scheme and effect of priming). Nevertheless, it will be possible in future studies to replace the simple Gaussian reaction time model with ones derived from optimality principles. These are now available, for example, for the Eriksen Flanker task (Liu et al., 2009), the Stop-Go task (Shenoy and Yu, 2011), and we are currently working on the rule-association task (Bengtsson and Penny, 2013).

The switching dynamics that our model portrays after "clever" priming resemble the pattern of transient brain activation of the aMPC observed in Bengtsson et al. (2011) where activation goes up for errors and down for correct responses when participants are primed "clever." It is interesting to note that the priming impacts on the confidence in memory processes, which themselves are processed on the aMPC (Summerfield et al., 2009). Our model suggests that the enhanced activation seen in aMPC after "clever" priming when participants make errors reflects a switch away from me-focus to task-focus. That this signal only occurs when there is a positive expectation on performance is in line with findings that this area is signaling errors when participants are more motivated to do well on a task (Bengtsson et al., 2009), and when the errors reinforce individuals' optimism (Sharot et al., 2011). Taken together, it suggests that self-related activation of aMPC that occurs during errors reflects processes of discrepancies when it is relevant to sustain positive aspects of self.

We have no direct evidence in this study that the priming actually targets self-concepts. According to the misattribution theory,

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In this paper we have highlighted the impact psychological factors can have on decision-making systems. We find that a contributing factor to optimal cognitive control is the implicit associations that people make to themselves as being clever. Our model suggests that these top-down associations regulate the efficiency of attentional switching between one's own abilities and the task, as well as the confidence in one's own memory processes.

#### **ACKNOWLEDGMENTS**

We would like to thank Peter Dayan for commenting on an early version of this manuscript. This work was supported by VINN-MER, Vinnova – Swedish Governmental Agency for Innovation Systems, VR – the Swedish Research Council, Cornells Stiftelse, and a core grant from the Wellcome Trust.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 30 April 2013; paper pending published: 18 June 2013; accepted: 02 August 2013; published online: 19 August 2013.*

*Citation: Bengtsson SL and Penny WD (2013) Self-associations influence taskperformance through Bayesian inference. Front. Hum. Neurosci. 7:490. doi: 10.3389/fnhum.2013.00490*

*Copyright © 2013 Bengtsson and Penny. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Age differences in neural response to stereotype threat and resiliency for self-referenced information

# **Gabriel Colton, Eric D. Leshikar and Angela H. Gutchess\***

Department of Psychology, Brandeis University, Waltham, MA, USA

#### **Edited by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada

#### **Reviewed by:**

Cheryl Grady, University of Toronto, Canada Joe Moran, Natick Soldier Research and Development Center, USA

#### **\*Correspondence:**

Angela H. Gutchess, Department of Psychology, Brandeis University, 415 South Street, Waltham, MA 02453, USA

e-mail: gutchess@brandeis.edu

# To investigate the contribution of cortical midline regions to stereotype threat and resiliency, we compared age groups in an event-related functional MRI study. During scanning, 17 younger and 16 older adults judged whether words stereotypical of aging and control words described them. Judging stereotype words versus control words revealed higher activations in posterior midline regions associated with self-referencing, including the precuneus, for older adults compared to younger adults.While heightening salience of stereotypes can evoke a threat response, detrimentally affecting performance, invoking stereotypes can also lead to a phenomenon called resilience, where older adults use those stereotypes to create downward social-comparisons to "other" older adults and elevate their own selfperception. In an exploration of brain regions underlying stereotype threat responses as well as resilience responses, we found significant activation in older adults for threat over resilient responses in posterior midline regions including the precuneus, associated with self-reflective thought, and parahippocampal gyrus, implicated in autobiographical memory. These findings have implications for understanding how aging stereotypes may affect the engagement of regions associated with contextual and social processing of self-relevant information, indicating ways in which stereotype threat can affect the engagement of neural resources with age.

**Keywords: aging, stereotypes, fMRI, self-referencing, cortical midline regions, stereotype threat, cognition**

# **INTRODUCTION**

Stereotypes represent shared beliefs that save time and energy by allowing one to judge other people based on group membership rather than on the basis of their complex and unique personalities (McGarty et al., 2002). The development and maintenance of aging-related stereotypes is unique relative to other group-related stereotypes for several reasons. First, older adults are the only stigmatized group that transitions from an out-group (i.e., as they are seen by young adults) to an inevitable in-group as those young adults reach old age. Second, there is initially no reason for younger adults to defend against negative aging-related stereotypes as they only apply to others. With aging, individuals may begin to internalize and become susceptible to aging-related stereotypes (Levy and Banaji, 2002). Third, negative aging-related stereotypes are perpetuated and are present across cultures (Cuddy et al., 2005) and held by both younger and older adults alike (Boduroglu et al., 2006), illustrating the potential far-reaching implications of aging-related stereotype research.

Aging-related stereotypes can be both positive (e.g., wise, accomplished, enlightened, and respected) and negative (e.g., forgetful, slow, confused, and inept) (Mueller et al., 1986; Levy, 2003). While stereotypes are useful to the extent that they can help direct interactions with others from different groups, they can also be detrimental under some circumstances. Steele and Aronson's (1995) seminal work on stereotype threat exemplified this by demonstrating that African American students' performance on a personally important ability (academic performance) was impaired when they were primed to think about relevant negative

stereotypical information prior to the task. African American students performed similarly to their white counterparts under nonthreatening conditions, suggesting that the performance decrement seen under threatening conditions was not indicative of the students' actual abilities. Studies in older adults have also demonstrated the negative impact of stereotype threat on cognitive function (e.g., memory), psychomotor function (e.g., walking rate and handwriting), physiological factors (e.g., heart rate and blood pressure), and self-worth (e.g., will to live) compared to older adults who do not experience a threat manipulation (Bargh et al., 1996; Horton et al., 2008, 2010; for a review see Levy, 2003).

In addition to how much value one places on the ability being measured (Hess et al., 2003), such that stereotype threat conditions are more detrimental to individuals who place high importance on the stereotyped ability, the self-relevance of a stereotype influences the extent to which stereotype threat impacts performance (Shih et al., 2002). To date, no extant work has investigated how the self-relevance of stereotypes impacts neural response<sup>1</sup> . The social cognitive network (for a review, see Lieberman, 2007; Van Overwalle, 2009), encompassing regions including medial prefrontal cortex and temporo-parietal junction, is broadly implicated in stereotype-relevant processes. The network is thought to underlie evaluative processing, mentalizing about others, and making social rather than non-social judgments (Quadflieg et al., 2009, 2011;

<sup>1</sup>While research on stereotype threat does investigate the threat represented to the self, that literature focuses on performance decrements, rather than mentalizing about the self. Thus, this research will be reviewed elsewhere.

Quadflieg and Macrae, 2011). This same network is also implicated in thinking about the self and uniquely supports memory enhancements for self-relevant information (Rogers et al., 1977; Symons and Johnson, 1997; Kelley et al., 2002; Fossati et al., 2004; Macrae et al., 2004). Given the overlapping networks involved in self-referencing and stereotyping, as well as the self-relevance of aging-related stereotypes over the lifespan, the intersection of these topics offers a way to explore the self-relevant processes evoked by stereotypes across age groups.

The cortical midline network implicated in self-referencing, as well as stereotyping, has been divided into distinct subcomponents on the basis of meta-analysis and functional task dissociations. Northoff et al. (2006) propose that ventral anterior regions [including ventral medial prefrontal and anterior cingulate cortex (ACC)] are responsible for coding self-referentiality of information, dorsal anterior regions (including dorsal medial prefrontal cortex) may reflect the evaluative components of self-referencing, particularly compared to other stimuli or persons, and that posterior midline regions [including precuneus and posterior cingulate (PCC)] potentially reflect "self in context," including autobiographical memory. Another distinction separates anterior regions (medial prefrontal cortex; mPFC), engaged during more inwardfocused thought, from posterior regions (PCC; lingual gyrus), reflecting a more outward-directed, social and contextual focus, on the basis of response to different types of goals (Johnson et al., 2006; Mitchell et al., 2009). MPFC and PCC can also be distinguished on the basis of thinking about internal (i.e., character traits) and external (i.e., appearance) features of self and other (Moran et al., 2011).

The present study investigates the effects of aging on the recruitment of cortical midline regions during self-relevance judgments about words related to age-related stereotypes, compared to control words. To test this, we created a set of positive and negative trait adjectives, some of which are stereotypical of older adults (e.g., wise, frail) and some that are not stereotypical of either age group (e.g., friendly, irrational). Both younger and older participants judged the self-descriptiveness of these words.

Due to the greater self-relevance of age-related stereotypes, we expect greater activity in anterior and posterior midline regions in older than in younger adults for stereotyped relative to control words. Both younger and older adults have been shown to engage mPFC and mid-cingulate during judgments of self-relevance (Gutchess et al., 2007; see age differences during successful encoding in Gutchess et al., 2010) and mPFC when making judgments about same- versus other-age individuals (Ebner et al., 2011). Moreover, mPFC and PCC activity in younger adults increases linearly with increasing self-relevance of stimuli (Moran et al., 2006, 2009), suggesting that highly self-relevant words engage this region more than less or non-self-relevant words. Because stereotyped words may apply more to older versus younger adults, we predicted that older adults would engage regions implicated in self-relevance (e.g., mPFC, PCC) more than young in response to stereotyped words versus control words. We additionally anticipated that this relationship would be magnified for stereotyped words *endorsed* by participants as self-relevant, compared to non-endorsed words.

While cortical midlines regions are considered to be part of the "default network" broadly implicated in social cognition but deactivated during tasks demanding external attention, it is important to consider the effects of aging on this network during tasks thought to rely on this network (rather than on the *suppression* of this network). Some studies of aging report that this network is disrupted with aging, including during self versus nonself-judgments (Grady et al., 2012). These changes could reflect different strategies, types of processes, or foci across age groups during tasks (Grady et al., 2012), and thus it is important to consider the response of the network to various types of content. The engagement of cortical midline regions is affected by aging as a function of thinking about different self-relevant agendas, such as hopes (e.g., aspirations for career success) and duties (e.g., obligation to care for parents or grandchildren) (Johnson et al., 2006; Mitchell et al., 2009). While activity in both anterior (e.g., mPFC) and posterior (e.g., PCC) cortical midline regions is attenuated with age, the age difference is exaggerated for anterior regions. Engagement of anterior regions reflects thinking about hopes and aspirations, and this is considered to be less of a motivational focus for older adults (Mitchell et al., 2009). Instead, older adults may place more focus on duties and obligations, consistent with post-task reports and more intact engagement of posterior regions (Mitchell et al., 2009). These differences potentially indicate more age-related changes to an inward self-focus, reflected by anterior regions, than to an outward self-focus, governed by posterior regions (Johnson et al., 2006; Mitchell et al., 2009; see also Northoff et al., 2006).

This distinction allows for the possibility that the ways in which older adults make self-relevant judgments may be more contextual and social, particularly for stereotyped information, compared to younger adults. This may occur because age-related stereotypes may reflect limitations in how one achieves goals and fulfills obligations. The overlap between self-referencing and agerelated stereotypes is intriguing due to potential differences in the extent to which an individual sees him or herself as a member of the target group, conforming to the stereotypes. Older adults have more complex and varied views of the typical older adult than do younger adults (Hummert, 2011). This is consistent with the out-group homogeneity effect, which posits that people view out-group members as more similar to each other than in-group members (Park and Rothbart, 1982). Interestingly, while presenting older adults with negative age-related stereotypical information may lead to an increasingly negative peer-perception, it also can lead to an increasingly positive self-perception (Pinquart, 2002). When reflecting on age-related stereotypes, older adults created an additional out-group of "other old people." By projecting the negative stereotypes onto that group rather than themselves, older adults reduced the personal relevancy of the stereotype. This phenomenon, termed "resiliency" (Pinquart, 2002), stood in contrast to previous studies showing that negative stereotypes (threatening conditions) adversely affected self-concept as well as performance (for a review see Levy, 2003; see Meisner, 2012 for a meta-analysis). The current study will investigate resiliency within our self-relevance paradigm by separating words reflecting a positive self-image (endorsed words reflecting positive aging stereotypes and denied, or non-endorsed, words reflecting negative aging stereotypes) from words signifying a threat response (endorsed words reflecting negative aging stereotypes and denied

words reflecting positive aging stereotypes). Given that participants will view these words without being explicitly aware of the presence of negative age-related stereotypes, we may have more sensitivity to detect age differences, as overtly directing older adults toward specific stereotypes may allow them to try to actively resist them (Hess et al., 2004).

Combined with our expectation that older adults will have a more heterogeneous perspective on same age peers than young, we hypothesize that older adults' judgments of self-relevance of traits will have a more social-comparison focus (e.g., downward socialcomparison, such that one compares favorably to peers) than younger adults, particularly for aging-related stereotypes (Johnson et al., 2006; Mitchell et al., 2009). Specifically, this should be reflected in older adults' increased activation of posterior midline regions (PCC/precuneus), compared to younger adults, when self-relevance judgments are made for stereotyped versus control words. If older adults process age-related stereotype information in a manner oriented to social context, this outward focus could lead to a threatened response (e.g., via salience of negative aging stereotypes) or a resilient response (e.g., via downward social-comparisons).

Previous research on stereotype threat reveals that emotional and control processes are invoked under threat. In response to gender-based stereotype threat conditions, activation increased in ventral anterior cingulate cortex (vACC) (Krendl et al., 2008) and the amygdala (Wraga et al., 2007), regions implicated in the evaluation and regulation of emotion (Bush et al., 2000). Given the potential conflict between self- versus group-relevance of stereotypical information, we also predicted that cognitive control regions, such as ACC and dorsolateral prefrontal cortex (DLPFC) (Gehring and Knight, 2000; Kim et al., 2010), could be implicated. If group membership is salient and a trait is descriptive of older adults in general but not of the self, older adults should experience conflict. Activation in control regions could allow an older adult to respond in a resilient manner. We hypothesized that ACC and DLPFC, implicated in cognitive control and conflict resolution, would show larger activations for resilient responses relative to threatened responses for older adults. We also expect ventral ACC and amygdala to exhibit greater activation for threat relative to resilient responses because threat responses should evoke a greater need for emotional processing. Younger adults' neural activity should not differentiate resilient from threatened responses, as stereotypes should not elicit the need for conflict resolution in the case of a resilient response, or emotional processing in the case of a threat response.

Taken together, this study had three main goals. First, we investigated potential age differences in self-referential processing of stereotyped information, focusing on cortical midline regions associated with self-relevance. Second we assessed whether older adults exhibited a more social-comparison/contextual self-focus, reflected by greater activation than young adults in posterior regions, as opposed to an inward-directed self-focus when making decisions about stereotyped information. Third, we examined the neural basis of resiliency and stereotype threat for older compared to younger adults, predicting that brain activations implicated in conflict resolution and emotional processing, respectively, would underlie these two response types.

# **MATERIALS AND METHODS**

#### **PARTICIPANTS**

Seventeen young (ages 18–35) and 16 older adults (ages 66–83) participated in this study in exchange for compensation. Sample characteristics are presented in **Table 1**. One additional older participant was unable to complete the fMRI portion of the experiment due to discomfort in the scanner. Criteria for fMRI participation included right-handedness, English as a native language, good neurological, psychological, and physical health, and no CNS-active medication or other contraindications for MRI. The Brandeis University and Partners Healthcare Institutional Review Boards approved the study, and all participants provided written informed consent.

#### **NEUROPSYCHOLOGICAL MEASURES**

Each participant completed a health and demographic questionnaire, a digit comparison speed of processing task (Hedden et al., 2002) and a vocabulary task (Shipley, 1986). Older adults completed the Mini-Mental State Exam (MMSE; Folstein et al., 1975) in order to assess the orientation of the elderly participants. All elderly participants scored 27 or higher (out of 30) on the MMSE, as a means to include only cognitively intact older adults. Scores from these measures are presented in **Table 1**.

#### **MATERIALS AND PROCEDURE**

Stimuli consisted of 216 trait adjectives. Seventy-two were stereotypical of older adults; half were positive (e.g., wise) and half were negative (e.g., frail). One hundred forty-four were control words and not stereotypical of either age group, with half positive (e.g., friendly) and half negative (e.g., irrational). Stereotypical words were taken from previously normed materials (Mueller et al., 1986; Bargh et al., 1996; Levy, 1996, 2003; Matheson et al., 2000; Boduroglu et al., 2006). Stereotype words were then assigned two unique control words from Anderson's (1968) word norms and Affective Norms for English Words (ANEW; Bradley and Lang, 1999), matched on valence, word length, and word frequency based on Kucera–Francis and Throndike–Lorge measures of written frequency. Valence was determined for each stereotype word using Anderson's word norms (Anderson, 1968). Words that were not present in Anderson's word norms were assigned valence based on the valence of a root word or using the ANEW (Bradley and

#### **Table 1 | Means and standard deviations for demographics and performance measures.**


Self-rated health reflects a rating on a 5-point scale, in comparison to others of one's own age group. A rating of 4 denotes "better than average."

Lang, 1999). The distribution of trial types across the different conditions, broken down by endorsement, is presented in **Table 2**.

The experiment was presented using E-Prime software (Psychology Software Tools, Pittsburgh, PA, USA) and responses were recorded using a MRI-compatible button box. Before entering the scanner, participants were trained on the experimental tasks. The experimenter read instructions out loud while the participant read along, and then verbally confirmed understanding of the task. Participants completed a short practice session and were allowed to ask clarification questions. Once in the scanner, participants viewed 144 trait adjectives (96 control half positive, half negative and 48 stereotype words half positive, half negative) and judged whether each word was self-descriptive (e.g.,"Are you compassionate?"). Stimuli appeared for 3 s with an additional second in which to make a response, followed by 2–20 s of fixation in a jittered design. For each trial, participants indicated a "yes" response using their index finger or a "no" response using their middle finger of their right hand. The 144 trait adjectives were split into three runs, each lasting 5 min. The entire scan session lasted approximately 45 min.

Approximately 10 min after the end of the encoding trials, participants were presented with surprise self-paced recall and recognition tasks outside of the scanner. These data will not be presented here, as they are not the focus of the current investigation. Before being debriefed and compensated for their time, participants completed a feedback questionnaire and an adjective rating sheet, in which they rated the extent to which adjectives described younger versus older adults. These ratings verified that both younger and older adults rated the stereotype words as more descriptive of older adults compared to the control words.

#### **fMRI ACQUISITION**

A Siemens Avanto 1.5 T scanner was used to acquire all structural and functional scans. An echo-planar imaging (EPI) sequence (TR = 2000 ms; TE = 40 ms) acquired 26 AC/PC oriented 5 mm thick slices (with a 1 mm skip between slices). Stimuli were projected onto a white screen behind the scanner, which the participant viewed through a mirror mounted to the headcoil. Participants who needed vision corrected wore MRI-compatible glasses. High-resolution structural images were acquired using a multiplanar rapidly acquired gradient echo sequence (MP-RAGE).

#### **fMRI ANALYSIS**

Data were analyzed using Statistical Parametric Mapping (SPM8; Wellcome Trust Centre for Neuroimaging) implemented in MAT-LAB R2012a (The Mathworks Inc., Natick, MA, USA). The first five volumes of each session were discarded to allow for equilibration effects. The resulting EPI volumes were corrected for differences in slice time acquisition, using the middle slice of each volume as a reference, and spatially realigned to the first acquired volume to correct for movement. Each participant's structural scan was coregistered to the mean EPI image produced from the realignment step and subsequently segmented and normalized to the Montreal Neurological Institute T1 average brain template. These normalization parameters were then applied to every EPI volume. The normalized EPIs were resliced into 3 mm × 3 mm × 3 mm

**Table 2 | Means and standard deviations for the number of responses of each type at encoding.**


resolution then spatially smoothed using an 8 mm full-width at half-maximum Gaussian kernel.

Analyses of the functional data from the study were carried out in two steps. In the first step, neural activity was modeled as a series of delta functions for each participant, coinciding with onsets of the various stimuli types convolved with a canonical hemodynamic response function. For each participant, 12 covariates were created, representing the 8 conditions of interest, 1 for "No Response" trials, and 3 representing each of the functional runs. Voxel-wise parameter estimates for all covariates were obtained by restricted maximum-likelihood (ReML) estimation, using a temporal high-pass filter (cutoff 128 s) to remove low-frequency drifts. Intrinsic autocorrelation within each session were corrected by applying a first-order autoregressive, AR(1), model. The data were scaled to a grand mean of 100 over all voxels and scans (Friston et al., 2007).

In the second analysis step, contrasts of the parameter estimates for each participant were submitted to a group analysis treating participant as a random effect. For each subject, we modeled four trial types: Stereotype Yes, Stereotype No, Control Yes, Control No. This lead to a 2 × 2 × 2 (word type: stereotype/control × decision: yes/no × age: young/old) mixed model ANOVA. A second ANOVA examined effects of resiliency and threat to the stereotyped words. To do this, we modeled positive stereotype words endorsed (i.e., "yes" responses at encoding) and negative stereotype words that were denied (i.e., "no" responses at encoding), together into a trial type called resilience. We grouped positive stereotype words that were denied and negative stereotype words that were endorsed into a trial type called threat. All words were processed in a selfreferential manner. It is possible that all decisions made were objective, i.e., all "yes" responses were for words that were actually self-descriptive, and "no" responses were for words that were truly not self-descriptive, but in accordance with previous literature (Pinquart, 2002 – resiliency; Steele and Aronson, 1995 and other studies – threat) both resiliency and threat can have effects on performance that can cause participants to respond differently than they would in a non-experimental setting. We therefore presume that a threat versus resiliency response to a certain trial would be best characterized by the aforementioned grouping of trial types.

In all ANOVAs, eight group contrasts modeling the mean across conditions for each of the 33 participants were also added to each model to remove between-subject variance of no interest. Statistical parametric maps (SPMs) were created from the *T*-statistics for the various ANOVA effects of interest, using a single pooled error estimate for all contrasts, whose non-sphericity was estimated by ReML, as described in Friston et al. (2002). Results for each ANOVA are reported from two-tailed *t*-contrasts, threshold at *p* < 0.001, uncorrected with a minimum cluster size of 5.

#### **RESULTS**

Consistent with our focus on the effects of aging on self-referential processing of stereotyped information, we conducted three sets of contrasts.

#### **AGE** × **STEREOTYPICALITY**

There was an interaction between age and word type with regions showing higher activation for stereotype words than for control words for older relative to younger adults<sup>2</sup> . These effects emerged in posterior midline regions, including precuneus (BA 23, 7) and bilateral lingual gyrus (BA 18, 37). These regions were implicated in self-referential judgments about duties and obligations, a type of self-relevant agenda that remains highly motivating for older adults (Mitchell et al., 2009). All regions with significant activations can be seen in **Table 3A**. Although we also expected to see anterior midline frontal activations (such as mPFC) for this contrast, no activation emerged using the above threshold. Examining the reverse contrast to identify regions showing higher activation for control words than for stereotype words for older compared

<sup>2</sup>Note that the contrast of (Old >Young) (Stereotype > Control) is equivalent to the contrast of (Young > Old) (Control > Stereotype).

to younger adults yielded no significant activations. Neither did the main effect of word type (stereotype or control) yield any significant activation.

#### **AGE** × **STEREOTYPICALITY** × **ENDORSEMENT**

We next tested for regions that in older adults, compared to younger adults, activated more for stereotype words that were non-endorsed ("no") than for stereotyped words that were endorsed ("yes") relative to control words [(SN-SY) > (CN-CY), Older >Younger Adults<sup>3</sup> ]. Thus, regions that for older adults responded more for rejected stereotype words than endorsed stereotype words, relative to endorsed versus rejected control words. Regions of activation surviving this contrast can be seen in **Table 4A**. Activations included posterior midline regions, including bilateral precuneus (BA 5) and right mid-cingulate (BA 23), as well as left amygdala. **Figure 1** depicts the response for the right mid-cingulate, and left precuneus. The left precuneus showed differential activation across age, particularly for "no" stereotype words, with younger adults showing decreased activity and older adults showing increased recruitment. Similar effects were evident in the mid-cingulate and the amygdala (data not shown). We also tested for regions that emerged in the opposite contrast, with older adults showing higher activation for the "yes" stereotype words than the younger adults, but no significant activations were found (**Table 4B**).

#### **AGE** × **THREAT/RESILIENCY**

We next examined activity during "threatening" trials (which we define as either "no" to stereotype positive words or "yes" to stereotype negative words) compared to resilience trials (defined

<sup>3</sup>Note that the contrast of [(SN-SY) > (CN-CY), Old >Young] is equivalent to the contrast of [(SY-SN) > (CY-CN), Young > Old Adults].

#### **Table 3 | Age** × **stereotypicality.**


No surviving voxels

Regions are listed in order from highest to lowest t-value. Only one peak voxel is listed per cluster. BA, Brodmann's area.



Regions are listed in order from highest to lowest t-value. Only one peak voxel is listed per cluster. BA, Brodmann's area.

as either "yes" to stereotype positive words or "no" to stereotype negative words) for older adults compared to younger adults (see Materials and Methods for explanation of trial groupings)<sup>4</sup> . Principal regions emerging from the analysis again included posterior midline regions, such as left PCC (BA 23) and right precuneus (BA 17,7), as well as left hippocampus and left parahippocampal gyrus (BA 30) and are illustrated in **Figure 2** and listed in **Table 5A**. The effect in the precuneus was driven by increased activation in older adults for threatening trials and decreased activation for resilience trials. The activation in PCC is centered in white matter

<sup>4</sup>Note that the contrast of (Old >Young) (Threat > Resiliency) is equivalent to the contrast of (Young > Old) (Resiliency > Threat).



Regions are listed in order from highest to lowest t-value. Only one peak voxel is listed per cluster. BA, Brodmann's area.

so we cannot definitively say that it is related to recruitment of the PCC during the judgment task rather than an artifact. The effects in the hippocampus (data not shown) and the parahippocampal gyrus were driven by increased activation during threatening trials compared to resilience trials in older adults. Younger adults were generally insensitive to trial type, showing similar activation in these regions regardless of trial type, although they exhibited reduced activity in the precuneus in the threat condition. An examination of regions showing higher activation for resilience trials than for threatening trials (**Table 5B**) produced no significant effects.

# **DISCUSSION**

This study used a self-referencing paradigm in order to investigate the neural regions involved at the intersection of thinking about oneself and age-related stereotypes. Given that older age represents one of the few stereotyped groups in which one transitions from an out-group member to an in-group member over the course of one's life, this domain represents an opportunity in which to study how thinking about oneself is impacted by membership in a stereotyped group. In addition, the study explored the neural basis of stereotype threat and resiliency across age groups, suggesting that the processing of stereotyped information is impacted by the implications of endorsing it as self-relevant (e.g., reflecting a positive or negative self-view). Our first finding was that judgments of age-related stereotype words led to higher activations of posterior midline regions implicated in self-related processing, including precuneus and lingual gyrus, for older compared to younger adults. Second, older adults exhibited higher activity in precuneus, mid-cingulate, and amygdala for non-endorsed (nonself-relevant) stereotype words versus endorsed stereotyped words, compared to younger adults. Third, we showed that threat (i.e., denial of positive and endorsement of negative age-related stereotypes as self-relevant) relative to resilient responses (i.e., denial of negative and endorsement of positive age-related stereotypes as self-relevant) elicited increased precuneus, PCC, hippocampus, and parahippocampal gyrus activity. These findings converge in implicating changes to the posterior midline regions with age, suggesting that age groups may differ in thinking about the self in a highly contextualized manner during the processing of stereotyped information, particularly when information may be threatening to the self.

We predicted that midline cortical activity, indicative of selfreferential processing, would be increased among older adults relative to young, in judging the self-descriptiveness of stereotyped versus control trait adjectives. We found age differences in posterior cortical midline regions (precuneus, lingual gyrus) that have been implicated in self-reflection, self-relevant memory, and other types of self-judgments (Johnson et al., 2006; Northoff et al., 2006; Gutchess et al., 2007; Mitchell et al., 2009). In particular, PCC activity increases as a function of self-relatedness (Moran et al., 2006) and posterior regions respond to thinking about duties and obligations (Johnson et al., 2006; Mitchell et al., 2009). Interestingly, stereotyping research with young adults also shows that the precuneus is more engaged for stereotype than control conditions (Quadflieg et al., 2009), though this has not been the focus of the literature thus far. We find that the effect in posterior regions emerges for older more than younger adults. While it was surprising to not identify effects in anterior midline regions (e.g., mPFC) given prior work, previous studies reporting frontal midline activation for self-referential processes (e.g.,Kelley et al., 2002; Gutchess et al., 2007, among others) used experimental designs that included trials in which participants made non-self-referential judgments (e.g., judgments of other people or semantic judgments). This likely gave them more sensitivity to detect self-specific regions of activation. A possible explanation for why we did not see more activation of regions typically seen in self-referencing studies is that our experimental paradigm required participants to make decisions only in reference to the self, and so there was no other or semantic condition with which to compare. While the present study focused on midline cortical regions, it is worth noting that regions of superior temporal gyrus, located near the temporoparietal junction, also exhibited age differences for stereotyped words, in comparison to control words (see **Table 3**, as well as **Table 4**). This region has previously been implicated in mentalizing and theory of mind (Van Overwalle and Baetens, 2009), suggesting that stereotyped words differently evoked processes involving in thinking about, and possibly empathizing with others, for older versus younger adults.

Our second hypothesis was that judgments of stereotype trait adjectives would necessitate a more outward social-comparison focus in self-referencing for older adults, due to the relevance of age-related stereotypes. We therefore expected that older adults would recruit posterior midline regions for judgments about age-related stereotype words more than control words, particularly when words were endorsed. The results of the aging × stereotypicality × endorsement contrast indicate that some posterior midline regions are sensitive to the self-relevance judgment of stereotyped information, such that there is a heightened response when older adults reject stereotyped information as non-self-relevant. Given the salience of age for stereotyped words, judgments about the self may evoke processing of the self in a social context, and this may be most salient when the judgment about the self differs from the expectation for the group (i.e., a"no" response to a stereotype). This explanation converges with some of our prior work in which we found that older adults engage precuneus more than young adults during the processing of pictures of social affiliation, whereas the groups similarly engaged the region for pictures of isolation (Beadle et al., 2012). Thus, the increased precuneus activity in older adults may reflect the tendency for age-related stereotypes to evoke more social processing in older than younger adults when the concept of the self versus the group is activated. It is also possible that the response reflects the threatening nature of the non-endorsed stereotyped information, as such words represent a poor outcome of aging that could limit one's ability to perform duties and obligations. Such an interpretation would be consistent with the engagement of the amygdala and insula during this comparison, reflecting differential involvement of emotional processes across judgments.

Our third prediction was that threat responses would be subserved by activations in regions associated with emotional processing and emotional load, such as ventral anterior cingulate and amygdala, and that regions implicated in control processing and conflict resolution, including ACC and DLPFC, would underlie resilient responses for older adults (Gehring and Knight, 2000; Kim et al., 2010). Younger adults were expected to show no difference across response types. While we did not find any regions that were recruited significantly more for resilient responses over threat responses, we found that posterior midline and medial temporal regions (i.e., precuneus, parahippocampal gyrus, and hippocampus) showed increased activation for threat response trials compared to resilient responses for older adults relative to younger adults. This pattern is particularly interesting given that there were fewer threat trials compared to resilience trials and that old and young did not significantly differ in the numbers of trials per bin. However, the threat trials led to robust activation, particularly in the parahippocampal gyrus, for older adults. The engagement of parahippocampal gyrus during autobiographical memory tasks (Spreng et al., 2009; St. Jacques et al., 2011), taken together with the engagement of the hippocampus, could indicate older adults' recall of specific episodic memories or scenes during threatened responses. As previously mentioned, precuneus has been implicated in self-referencing, particularly when thinking about the self in an outward-focused manner. This pattern could reflect that thinking about the self in a highly contextualized manner serves some protective function during threatening situations. For example, thinking about times in which one behaved in a manner consistent with a stereotype of old age could be considered situation-dependent, rather than as something typical of oneself.

It is also possible that older adults are drawing on their richer store of autobiographical memories for times in which their behavior was stereotype-consistent. It is also interesting to consider whether the threat-related activity here reflects older adults' over-activation of default regions during tasks. Older adults experience more difficulty suppressing default regions during externally driven tasks (Persson et al., 2007; Park et al., 2010), and one reason might be because the experimental conditions activate stereotype threat, and hence more activity in these cortical midline regions. Such an effect would have implications for a number of studies in the field of cognitive aging<sup>5</sup> .

One of the largest limitations to our study was our inability to look at effects of valence due to the impoverished number of positive stereotype trials receiving a "no" response and negative stereotype trials receiving a "yes" response. While we combined across valences to create our measures of threat and resiliency, it would be helpful to separately examine the response to negative versus positive stimuli, particularly as negative stereotypes might be expected to drive the effects. Small bin sizes also prevented us from performing subsequent memory analyses to correlate brain activation during successful encoding, which would have allowed us to assess the effects of stereotypes on cognitive processes. Administering additional behavioral measures to substantiate the concepts of "threat" and "resiliency," as well as self and peer-perception measures pre- and post-task (see Pinquart, 2002), could be combined with fMRI data to further explicate the function served by brain regions recruited during resilient and threatened responses, and individual differences as a function of one's views of the self and aging.

In conclusion, we have shown that older adults process agerelated stereotype words in a qualitatively different manner from

<sup>5</sup>We thank Reviewer 2 for this insightful point.

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younger adults, with different conditions eliciting more or less activity in regions for each age group. Older adults exhibit a more social-comparison/contextual self-focus when making decisions about stereotyped information, particularly in response to threat, as reflected by increased modulation of posterior midline regions. We have shown the possibility of dissociating resiliency from threat responses to stereotype information at the level of brain activation, suggesting that older adults may differently harness cognitive resources as a result of one's personal views about the self and membership in a stereotyped group. This could indicate protective effects of seeing the self in a positive light, when compared to same age peers, which could impact cognitive function. Our data indicate that the neural regions engaged in response to stereotyped information can be influenced by the extent to which the information represents a threat or challenge to one's self-image. These results illustrate the effects of aging on posterior, but not anterior, cortical midline regions during self-referential thought, and highlight the importance of understanding the effects of aging across the domains of self-reference and stereotyping.

#### **ACKNOWLEDGMENTS**

This work was supported by the National Institute on Aging grant R21 AG032382 (to Angela H. Gutchess), National Institutes on Health grants T90 DA032435-02 (supporting Gabriel Colton) and T32 AG000204-21 (supporting Eric D. Leshikar). This research was carried out at the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital, using resources provided by the *Center for Functional Neuroimaging Technologies, P41RR14075,* a P41 Regional Resource supported by the Biomedical Technology Program of the National Center for Research Resources (NCRR), National Institutes of Health. We thank Brittany Cassidy and Don Katz for helpful suggestions and feedback on earlier drafts of this manuscript.

cognitive state of patients for clinician. *J. Psychiatr. Res.* 12, 189–198. doi:10.1016/0022- 3956(75)90026-6


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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 05 June 2013; accepted: 16 August 2013; published online: 06 September 2013.*

*Citation: Colton G, Leshikar ED and Gutchess AH (2013) Age differences in neural response to stereotype threat and resiliency for self-referenced information. Front. Hum. Neurosci. 7:537. doi: 10.3389/fnhum.2013.00537*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Colton, Leshikar and Gutchess. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# On the role of the ventromedial prefrontal cortex in self-processing: the valuation hypothesis

# **Arnaud D'Argembeau1,2\***

<sup>1</sup> Department of Psychology – Cognition and Behavior, University of Liège, Liège, Belgium

<sup>2</sup> Cyclotron Research Centre, University of Liège, Liège, Belgium

#### **Edited by:**

Georg Northoff, University of Ottawa, Canada

#### **Reviewed by:**

Agnes J. Jasinska, National Institute on Drug Abuse, USA Marika Berchicci, University of Rome "Foro Italico" – Rome, Italy

#### **\*Correspondence:**

Arnaud D'Argembeau, Department of Psychology – Cognition and Behavior, University of Liège, Boulevard du Rectorat 3 (B33), B-4000 Liège, Belgium e-mail: a.dargembeau@ulg.ac.be

With the development of functional neuroimaging, important progress has been made in identifying the brain regions involved in self-related processing. One of the most consistent findings has been that the ventromedial prefrontal cortex (vMPFC) is activated when people contemplate various aspects of themselves and their life, such their traits, experiences, preferences, abilities, and goals. Recent evidence suggests that this region may not support the act of self-reflection per se, but its precise function in self-processing remains unclear. In this article, I examine the hypothesis that the vMPFC may contribute to assign personal value or significance to self-related contents: stimuli and mental representations that refer or relate to the self tend to be assigned unique value or significance, and the function of the vMPFC may precisely be to evaluate or represent such significance. Although relatively few studies to date have directly tested this hypothesis, several lines of evidence converge to suggest that vMPFC activity during self-processing depends on the personal significance of self-related contents. First, increasing psychological distance from self-representations leads to decreased activation in the vMPFC. Second, the magnitude of vMPFC activation increases linearly with the personal importance attributed to self-representations. Third, the activity of the vMPFC is modulated by individual differences in the interest placed on self-reflection. Finally, the evidence shows that the vMPFC responds to outer aspects of self that have high personal value, such as possessions and close others. By assigning personal value to self-related contents, the vMPFC may play an important role in the construction, stabilization, and modification of self-representations, and ultimately in guiding our choices and decisions.

**Keywords: self, identity, value, significance, medial prefrontal cortex, ventromedial prefrontal cortex, fMRI**

# **INTRODUCTION**

AsJames (1890) pointed out in his insightful piece on the self, each of us inevitably makes a fundamental division of his or her subjective world into two halves, establishing a distinction between what is considered as "me" (or "mine") and what is considered as "not-me" (or "not-mine"). James further emphasized that the two sides of the division are far from being treated equally: "the altogether unique kind of interest which each human mind feels in those parts of creation which it can call *me* or *mine* may be a moral riddle, but it is a fundamental psychological fact" (p. 289). This idea that we attach unique significance to self-related contents may prove useful for interpreting one of the most consistent findings that has emerged from neuroimaging research on selfprocessing. Over the past decade, a growing number of studies have shown that the ventromedial prefrontal cortex (vMPFC) is activated when people contemplate various aspects of themselves and their life, such their traits, experiences, preferences, abilities, and goals (Northoff et al., 2006; Lieberman, 2010; D'Argembeau and Salmon, 2012; Wagner et al., 2012; Martinelli et al., 2013). However, while it is now common to see the vMPFC referenced as a "self region," the precise mental operations mediated by this area remain poorly understood. Currently, there is no consensus on what this region really does when people think about themselves

(for different views, see e.g.,Amodio and Frith, 2006; Schmitz and Johnson, 2007; Legrand and Ruby, 2009; Mitchell, 2009; Northoff et al., 2011; Lieberman, 2012).

In this article, I examine the hypothesis that the vMPFC may contribute to generating the "unique kind of interest" in selfrelated contents that William James emphasized. Many studies have shown that the vMPFC plays a key role in representing the affective significance or subjective value of various types of stimuli (for review, see Rangel and Hare, 2010; Levy and Glimcher, 2012; Roy et al., 2012). Most of these studies focused on the processing of stimuli from the external environment that, at first sight, have nothing to do with self-representations. Could it be, however, that the vMPFC plays a similar role in self-processing? In other words, could it be that the vMPFC contributes to assign value or significance to self-related contents? Before examining this hypothesis, I first specify what is meant by "self" in this context and then provide an overview of functional neuroimaging studies showing the involvement of the vMPFC in self-processing.

#### **THE MULTIFACETED SELF**

Any attempt at synthesizing the numerous definitions and conceptualizations of the self that have been proposed in various fields – including philosophy, anthropology, sociology, psychology, and psychiatry – can easily become a daunting task. Yet it is important to clarify what one means by "self" in order to avoid any misunderstanding about the implications of neuroimaging findings on this topic (Zahavi and Roepstorff, 2011). Although there is debate on how best to characterize different components of the self, there is some consensus on the idea that the self is not a single entity, but instead a construct that encompasses multiple facets that are supported by distinct processes (Neisser, 1988; Damasio, 1999; Gallagher, 2000; Leary and Tangney, 2003; Morin, 2006; Klein and Gangi, 2010).Within this multi-component framework, one can draw a broad distinction between two main aspects of self: the self as experiencing subject (i.e., the consciousness of oneself as an immediate subject of experience, which generates a sense of personal agency and ownership over behavioral actions and sensory representations) and the self as object of knowledge (i.e., the representation and evaluation of one's personal characteristics and experiences) (James, 1890; Damasio, 1999; Gallagher, 2000; Legrand, 2007; Klein, 2012; Prebble et al., 2013).

Most psychological and cognitive neuroscience investigations to date have focused on the self as object of knowledge (Legrand and Ruby, 2009; Christoff et al., 2011; Klein, 2012), and this is the aspect of self that is addressed in the current article. The self as object is itself composed of multiple systems or components, including the ability to recognize one's physical appearance (Devue and Brédart, 2011), representations of one's personality traits and other personal attributes (Klein and Lax, 2010), memories of one's past experiences and knowledge of facts about one's life (Conway, 2005; Renoult et al., 2012), representations of personal goals and projected future experiences (Markus and Nurius, 1986; D'Argembeau et al., 2012b). The self-as-object can also be conceived as including stimuli that are not, strictly speaking, part of the individual but that somehow relate or belong to the self, such as close others and possessions (James, 1890; Belk, 1988;Aron et al., 2004). Although under normal circumstances these different constituents of the self-as-object interact with each other, they are at least partly dissociable (i.e., one component can operate independently from another). For example, there is substantial evidence that knowledge of one's personality traits is functionally independent from memories of one's past experiences (for review, see Klein et al., 2008).

# **MEDIAL PREFRONTAL INVOLVEMENT IN PROCESSING SELF-RELATED CONTENTS**

The self and its different components are in all likelihood not "located" in a single place in the brain, but may instead depend on distributed neural systems that include both cortical and subcortical structures (Northoff and Panksepp, 2008; Damasio, 2010). Quite remarkably, however, there is growing evidence that the processing of various types of self-related contents – which form parts of the self-as-object – is commonly associated with activation of the medial portion of the prefrontal cortex (for recent reviews and meta-analyses, see Northoff et al., 2006; van der Meer et al., 2010; Qin and Northoff, 2011; Denny et al., 2012; D'Argembeau and Salmon, 2012; Murray et al., 2012; Wagner et al., 2012; Martinelli et al., 2013).

The representation of one's personality traits is the aspect of self that has been most frequently investigated in functional neuroimaging studies. In a typical study (see e.g., Kelley et al., 2002), the brain activity associated with evaluating the selfdescriptiveness of personality traits (e.g., polite, dependable, daring) is compared to the activity associated with making the same kind of judgments in reference to another person. Several dozen studies using this paradigm have been published to date, and two recent meta-analyses have shown that the medial prefrontal cortex (MPFC)<sup>1</sup> is the brain region that is most consistently activated during trait self-judgments (van derMeer et al.,2010;Murray et al., 2012). Activations in this region have been observed across different age groups, including children (Pfeifer et al., 2007), adolescents (Schneider et al., 2012), and young and older adults (Gutchess et al., 2007; Ruby et al., 2009). The evidence further suggests that the MPFC is involved in representing and evaluating a variety of different types of personal characteristics, not only one's personality traits but also one's attitudes, values, mental states, and physical attributes (e.g., Zysset et al., 2002; Jenkins and Mitchell, 2011; Brosch et al., 2012).

The neural basis of autobiographical memory – memories of one's past experiences and knowledge of facts about one's life – has also received extensive attention (for review, see Maguire, 2001; Cabeza and St Jacques, 2007; Piolino et al., 2009). In many studies, memories of specific personal experiences (i.e., events that happened at a particular place and time in an individual's life) are compared with the retrieval of non-personal information (e.g., non-personal semantic knowledge or stimuli that have been learned in the laboratory before the scanning session). Several meta-analyses have shown that the MPFC is one of the brain regions most commonly activated during autobiographical memory retrieval, along with medial and lateral temporal cortices, the posterior cingulate/retrosplenial cortex, and the inferior parietal lobe (Gilboa, 2004; Svoboda et al., 2006; McDermott et al., 2009; Spreng et al., 2009; Kim, 2012; Martinelli et al., 2013). Of particular interest, a recent meta-analysis has further revealed that the MPFC is the only brain region that is consistently activated when thinking about one's traits, retrieving specific experiences from one's past, and accessing knowledge of facts about one's life, with both common and distinct MPFC activations across these three kinds of self-related information (Martinelli et al., 2013).

Besides memories and knowledge of one's past, an important part of self-representation refers to one's personal goals and projected future experiences (Markus and Nurius, 1986; Schacter et al., 2008; Szpunar, 2010; Rathbone et al., 2011; D'Argembeau et al., 2012b). In this regard, a number of studies have shown that the MPFC is activated when people think about goal states such as their hopes and aspirations (Johnson et al., 2006, 2009; Mitchell et al., 2009; Packer and Cunningham, 2009). In recent years, there has also been a growing interest in the concept of episodic future thought – the ability to imagine or simulate specific

<sup>1</sup> It should be noted that the designation of different portions of medial prefrontal cortex varies somewhat across studies. In this article, I use the term medial prefrontal cortex (MPFC) to refer to the entire central portion of the prefrontal cortex, including the anterior cingulate gyrus. The label ventromedial prefrontal cortex (vMPFC) is used to refer to a broad area in the lower central portion of the prefrontal cortex, encompassing medial sections of Brodmann's areas (BA) 10, 11, and lower BA 32, whereas the label dorsomedial prefrontal cortex (dMPFC) refers to the higher portion of MPFC, encompassing medial sections of BAs 8, 9, and higher BA 32.

events that might occur in one's personal future (Schacter et al., 2008; Szpunar, 2010) – and there is now substantial evidence that episodic remembering and future thinking largely depend on the same core network of brain regions, among which the MPFC is a key player (e.g.,Addis et al., 2007; Sharot et al., 2007; Szpunar et al., 2007; Botzung et al., 2008; for review, see Schacter et al., 2012). Of interest is the finding that the MPFC is more activated when thinking about one's personal past and future than when contemplating the non-personal past and future (Abraham et al., 2008). Furthermore, it has been shown that envisioning events in one's personal future and reflecting on one's personality traits are associated with overlapping activation in the MPFC (D'Argembeau et al., 2010a), which provides additional evidence that this region is involved in processing different types of self-related information.

A question that has been debated is whether the MPFC is specifically recruited for processing self-related information or whether this region is also involved in processing information about other individuals (Gillihan and Farah, 2005; Legrand and Ruby, 2009; Wagner et al., 2012). There is evidence that self- and other-related judgments are associated with overlapping activation in theMPFC, suggesting that this region may play a broad role in social cognition (see e.g., Van Overwalle, 2009; Denny et al., 2012). Yet, when the two kinds of judgments are directly compared to each other, self-related judgments generally lead to greater activation than other-related judgments, especially in the vMPFC. For example, two recent quantitative meta-analyses have shown that the evaluation of one's own personality traits is associated with greater vMPFC activation compared to the evaluation of the traits of another person (van der Meer et al., 2010; Murray et al., 2012). In fact, there seems to be a ventral-dorsal gradient in MPFC such that increasingly ventral regions of MPFC are more strongly associated with making judgments about the self, whereas increasingly dorsal regions of MPFC are more strongly involved in making judgments about others (Denny et al., 2012).

A key dimension that influences vMPFC activity when thinking about others is the closeness of the person to oneself;for example,it has been shown that the vMPFC responds more strongly to friends than strangers (Krienen et al., 2010). Studies that have directly compared self-referential judgments with judgments about close others have yielded somewhat inconsistent findings, with some studies observing greater vMPFC activation for self relative to close others (Heatherton et al., 2006; D'Argembeau et al., 2007, 2008; Benoit et al., 2010; Krienen et al., 2010), whereas other studies found comparable levels of activation (Ochsner et al., 2005; Vanderwal et al., 2008). One possible interpretation of these divergent findings is that the differential activation of the vMPFC during self- and other-processing depends on the degree of inclusion of the close other in one's sense of self. As briefly mentioned above, people's identities not only include elements that are unambiguously part of them (e.g., their body and mental states) but also outer aspects of their lives, such as their family, friends, and possessions (James, 1890; Belk, 1988). Notably, research has shown that people tend to treat the resources, perspectives, and identities of close others as their own, and that these effects depend on the extent to which the person is included in their sense of self (Aron et al., 2004). Interestingly, it has been found that the strength of activation of the vMPFC when making judgments about the self

versus one's best friend depends on perceived self-other similarity: participants who perceived themselves as more similar to their friend exhibited less differential activation between the two kinds of judgments (Benoit et al., 2010). This finding suggests that the degree of inclusion of close others in the self is an important determinant of the vMPFC response during self- and other-processing (see also Zhu et al., 2007).

Outer aspects of self such as one's group membership and possessions have also been associated with increased activation in the vMPFC. Morrison et al. (2012) compared the neural activity associated with categorizing in-group and out-group words (i.e., groups participants felt they belonged to vs. groups they felt they did not belong to) to identify the brain regions that responded to one's group membership. They found that the vMPFC showed increased activity in response to in-group words compared to out-group words (see also Volz et al., 2009, for evidence that more dorsal regions of MPFC also contribute to social identity processes). Kim and Johnson (2012)investigated the brain regions supporting the incorporation of external objects in the self. Participants saw pictures of objects (e.g., clothing, electronic articles) that were either assigned to themselves or to another person. Objects were presented on the screen and participants were cued to place each object either in a basket labeled "mine" or in a basket labeled with the name of another person ("Alex"), and they were asked to imagine owning the objects that were assigned to the self. When contrasting the two kinds of objects, the authors found greater activation in the vMPFC for objects assigned to the self compared to objects assigned to the other person. Furthermore, the vMPFC region that was responsive to self-related objects was also more activated when participants evaluated their own personality traits (compared with the traits of another person) in a separate task. These findings suggest that external objects that have been associated with the self modulate activity in the same vMPFC region as do internal self-representations (see also Kim and Johnson, in press).

In summary, the studies reviewed in this section show that the medial portion of the prefrontal cortex, and especially the vMPFC, is commonly activated when people process a variety of different kinds of self-related information – their traits, attitudes, values, physical attributes, goals, memories, future thoughts, close others, social groups, and possessions. One should note that I focused on the vMPFC because this is the region that has been most consistently associated with elements of the self-as-object, but of course this is not the only brain area involved in processing self-related contents. Other regions that are commonly recruited include the dMPFC, posterior cingulate cortex (PCC), inferior frontal cortex, insula, and regions in medial and lateral temporal cortices (van der Meer et al., 2010; Denny et al., 2012; Murray et al., 2012; Martinelli et al.,2013). The vMPFC is structurally andfunctionally connected to multiple brain regions (Buckner et al., 2008), and likely interacts with distinct areas and networks depending on the type of self-related information that is processed at a given moment (see e.g., Andrews-Hanna et al., 2010b; Martinelli et al., 2013).

#### **WHAT IS THE ROLE OF THE vMPFC IN SELF-PROCESSING?**

While there is substantial evidence that the vMPFC is activated when people contemplate self-related contents, the precise role of this region in self-processing is not well understood and remains controversial (see e.g., Legrand and Ruby, 2009). Recent findings suggest that the act of self-reflection in itself may not depend on the vMPFC. Indeed, the vMPFC responds to self-related contents even in the absence of explicit self-referential judgments (Moran et al., 2009; Rameson et al., 2010; Kim and Johnson, in press), and a recent case study has shown that a patient with extensive brain damage to the vMPFC has a largely preserved self-concept and intact introspective and metacognitive abilities (Philippi et al., 2012). Such evidence suggests that while the vMPFC participates in the processing of self-related contents (as shown by the neuroimaging studies reviewed in the previous section), this region may not support the formation of self-representations *per se*. So what might be the function of the vMPFC during self-processing?

#### **THE VALUATION HYPOTHESIS**

Activity changes in the vMPFC are not restricted to tasks requiring the processing of self-related contents. Indeed, the vMPFC appears to play a broad role in affective and value-based processing (Phan et al., 2002; Bechara and Damasio, 2005; Kringelbach, 2005; Wallis, 2007; Peters and Buchel, 2010; Rangel and Hare, 2010; Levy and Glimcher, 2012; Roy et al., 2012). Most notably, research suggests that vMPFC activity encodes the subjective values of various types of rewards (for review, see Peters and Buchel, 2010; Rangel and Hare, 2010; Levy and Glimcher, 2012; Sescousse et al., 2013). For example, neuroeconomic studies have shown that the vMPFC tracks the magnitude of monetary rewards and the idiosyncratic values subjects place on those rewards; activity in this area correlates with monetary reward outcome (Knutson et al., 2003), the subject-specific valuations of gains and losses (Tom et al., 2007), and subject-specific discounted reward value (Kable and Glimcher, 2007). vMPFC activity reflects the subjective value that an individual assigns to other types of stimuli as well, including primary rewards (e.g., food) and various types of goods and social rewards (O'Doherty et al., 2003; Chib et al., 2009; FitzGerald et al., 2009; Hare et al., 2009, 2010; Lin et al., 2012). Furthermore, it has been shown that damage to the vMPFC results in disturbances of subjective valuation (Moretti et al., 2009; Sellitto et al., 2010; Glascher et al., 2012). Together, these and related findings have led to the view that the vMPFC integrates information from multiple sources to represent the significance or value of stimuli (Wallis, 2007; Peters and Buchel, 2010; Rangel and Hare, 2010; Levy and Glimcher, 2012; Sescousse et al., 2013).

Although the medial prefrontal activations that have been related to value-based processing are sometimes confined to the most ventral part of the vMPFC (i.e., the medial orbitofrontal cortex), many neuroeconomic studies have reported activations that strikingly overlap with the vMPFC areas that are commonly detected in self-processing studies (see e.g., Kable and Glimcher, 2007; Chib et al., 2009; Hare et al., 2009). Neuroeconomic studies focused on the role of the vMPFC in the subjective valuation of stimuli from the external environment that are only loosely, if at all, related to self-representations. Yet the findings raise the possibility that vMPFC responses when processing self-related contents could reflect a similar valuation mechanism. Indeed, self-related contents are rarely considered in a dispassionate way: stimuli and mental representations that refer or relate to the self are assigned

unique value and are associated with strong affective investments (James, 1890; Pelham, 1991; Leary, 2004). The function of the vMPFC during self-processing may precisely be to appraise or represent the personal value or significance<sup>2</sup> of self-related contents, an idea that is here referred to as the "valuation hypothesis" (see **Figure 1**).

The idea that the vMPFC might signal the personal significance of self-related contents has been echoed by several researchers. Schmitz and Johnson (2007) have proposed that the vMPFC instantiates supramodal processes that contribute to detect the self-relevance of various types of stimuli. Northoff and Hayes (2011) discussed several ways in which self-relevance and valuebased processing could be related, and argued that although the two processes may not be reducible to one other, they clearly interact and involve common neural substrates. The evidence reviewed by these authors, however, mainly focused on the self-relevance of external stimuli, such as pictures of emotional scenes or rewarding stimuli (e.g., Phan et al., 2004; de Greck et al., 2008; Enzi et al., 2009). Other researchers have proposed and provided more direct evidence that the vMPFC may also signal the personal significance of self-related mental contents, such as memories, prospective thoughts, and representations of one's personality traits (Andrews-Hanna et al., 2010b; D'Argembeau et al., 2010a, 2012a). Finally, a

<sup>2</sup>By personal value or significance, I simply mean the worth or importance of something for a particular individual.

significance is processed along a continuum, such that stimuli and mental

contents are assigned degrees of significance.

recent meta-analysis has revealed the broad involvement of the vMPFC across studies of memory, self-representation, social cognition, emotion, reward, pain, and autonomic regulation (Roy et al., 2012). In an effort to unravel the common denominator to these seemingly disparate functions, Roy et al. argued that the vMPFC may integrate various sources of information to conceive the meaning of events for one's well-being and future prospects.

A common theme across several proposals is therefore that the vMPFC encodes personal value or significance. This valuation mechanism may be applied to different kinds of information, not only stimuli from the external environment but also internally generated mental contents. From this perspective, the function of the vMPFC during self-processing may be to appraise or represent the significance of self-related information. To date, however, the extent to which activity changes in the vMPFC during selfprocessing tasks actually reflect the personal value that is assigned to self-related contents has not been examined in detail. In the next section, I discuss several lines of research that provide support for this hypothesis.

## **EVIDENCE FOR THE VALUATION HYPOTHESIS**

If the vMPFC contributes to assign personal value to self-related information, then the activity of this region should vary with the importance that an individual attaches to particular self-related contents at a given moment. Several lines of evidence suggest that this is indeed the case.

#### **Taking distance from self-representations**

One way to test the valuation hypothesis would be to experimentally manipulate the value that is assigned to self-representations and to examine whether the processing of these representations is associated with corresponding changes in vMPFC activity. Several studies have done this by investigating the effects of temporal distance on the neural correlates of self-processing. There is evidence that people value their current self to a greater extent than temporally distant selves (Wilson and Ross, 2001, 2003), such that they tend to treat their past and future selves as they would treat other individuals (Pronin and Ross, 2006; Pronin et al., 2008). If the vMPFC is involved in assigning value to self-representations, the activity of this region should be sensitive to these effects of temporal distance. In one fMRI study, we tested this hypothesis by comparing the neural correlates of making trait judgments about the present self versus a past self (D'Argembeau et al., 2008). Participants were instructed to reflect on their own traits and those of a close other, for both their present life period and a past life period (i.e., 5 years ago). We found that the degree of activity in the vMPFC varied significantly according to the target of reflection. Specifically, the vMPFC was more active when participants thought about their present self than when they thought about their past self or about the other person; thinking about the past self and thinking about the other person were associated with similar levels of activity. In a subsequent study (D'Argembeau et al., 2010b), we found that this effect of temporal distance was symmetrical between the past and the future: participants showed higher activity in the vMPFC when making trait judgments about their present self than when making trait judgments about themselves 5 years ago or 5 years from now (with no difference between

past and future selves). These findings suggest that reducing the personal significance of self-representations (by increasing temporal distance) leads to corresponding decreases in vMPFC activity during self-referential thinking.

Other studies have shown that the magnitude of the differential activity in the vMPFC when thinking about present versus future selves correlates with individual differences in the propensity to devalue future rewards. During fMRI scanning, Ersner-Hershfield et al. (2009) asked participants to judge personality traits in reference to the self or another person for both the present and the future (i.e., 10 years from now). Approximately 1 week after the scanning session, participants returned to the laboratory to complete a temporal discounting task in which they had to make a series of binary choices between an immediate monetary gain and a delayed (but usually larger) gain. In line with the above-mentioned findings, a region of the vMPFC showed greater activation for present self trials than for future self and other trials. Furthermore, a measure of differences in neural activation in this region between present and future self trials correlated positively with individual estimates of temporal discounting. In other words, participants who displayed greater activity in the vMPFC when thinking about present versus future selves showed a greater propensity to devalue future rewards. Related findings have been reported in a study in which participants were scanned while they predicted how much they would enjoy engaging in each of a series of activities (e.g., spending the afternoon in a modern art museum) either in the present or in the future (a year later) (Mitchell et al., 2011). It was found that the vMPFC was more activated when predicting present compared to future enjoyment. Furthermore, differences in vMPFC activity between predictions of present and future enjoyment correlated positively with individual differences in the tendency to discount future monetary rewards, as assessed by intertemporal choice tasks. Thus, there is converging evidence that people who display greater reduction in vMPFC activity when thinking about future compared to present selves have a higher tendency to devalue future rewards. A plausible interpretation of this finding is that the vMPFC provides a signal reflecting the value that is placed on self-related contents for different time periods.

#### **Psychological investment in self-representations**

Perhaps the most direct evidence for the role of the vMPFC in representing the value of self-related information comes from a recent study that investigated the neural correlates of psychological investments in self-representations (D'Argembeau et al., 2012a). People have many different ideas and beliefs about who they are and what they are like, but they do not treat all self-views the same. Research has shown that we place more or less importance on particular self-views (our emotive investment) and hold different self-views with more or less confidence (our epistemic investment) (Pelham, 1991). For example, someone might attach much importance in being honest (high emotive investment), while considering that punctuality is not a particularly important trait for her to possess (low emotive investment); and for both traits, this person might feel more or less confident that she truly possesses these attributes (her epistemic investment). If the vMPFC represents the personal significance of self-related information, then the degree of neural activity in this region should correlate with one's investments in self-representations, and in particular with emotive investments.

To test this hypothesis, we asked participants to make selfdescriptiveness judgments regarding a variety of traits (e.g., honest, shy, punctual) while their brain activity was measured using fMRI (D'Argembeau et al., 2012a). Immediately after the scanning session, participants were presented again with the same set of traits and were instructed to rate the certainty of their selfrepresentation regarding each trait (i.e., "how certain are you that you possess or do not possess this trait?"; from 1 = not at all, to 4 = completely), and the importance they attach to this selfrepresentation (i.e., "how important is it for you to possess or not possess this trait?"; from 1 = not at all important, to 4 = very important). These ratings thus provided indexes of participants' epistemic and emotive investments in each self-representation that had been processed during scanning. We then correlated the fMRI signal obtained during the self-descriptiveness judgments with the ratings of certainty and importance, which allowed us to identify the brain regions that responded to epistemic and emotive investments in self-representations on a trial-by-trial basis. The results showed that ratings of certainty and importance were correlated with neural activity in the MPFC, in both common and distinct MPFC areas. When looking at the brain regions that were specifically related to each kind of investment, we found that a region of the dMPFC responded specifically to the certainty of self-views, whereas a region of the vMPFC responded specifically to the importance of self-views. In other words, the level of activity of the vMPFC when participants contemplated their personal traits depended on their emotive investment in the particular selfrepresentation under consideration: the higher the value attached to a self-representation, the stronger the response of the vMPFC. It should be reminded that participants did not explicitly reflect on the importance attached to their self-representations during scanning, such that the observed activity in the vMPFC is unlikely to reflect the engagement of explicit evaluation processes. Instead, the vMPFC might automatically confer degrees of value to the conceptions of the self that we form in our minds when we think about ourselves.

Other evidence suggests that the vMPFC is also involved in assigning personal significance to mental representations of events and facts from one's life. In one fMRI study, we asked participants to imagine future events that were related to their personal goals (e.g., getting married next summer) and future events that were plausible and could be vividly imagined but were unrelated to their personal goals (e.g., taking a pottery lesson next summer), as determined by individualized pre-scan interviews (D'Argembeau et al., 2010a). We found that the vMPFC (as well as the PCC) showed greater activation when participants imaged future events that were related to their goals compared to future events that were unrelated to their goals. Importantly, these two types of future events were matched for vividness and temporal distance, suggesting that the observed differences in brain activation cannot be accounted by these factors. Instead, a plausible interpretation is that the increased activation of the vMPFC reflects the greater personal significance of events that are related to one's goals. This interpretation receives some support from another study that analyzed the component processes subserved by different brain regions when people engaged in self-referential thinking. Andrews-Hanna et al. (2010b) found that the vMPFC and PCC were more activated when participants answered questions about various issues and events in their personal life (e.g., "Think about the major issues in your life at this moment. Which of these issues concerns you the most: health, education, or finance?") than when they answered questions requiring the retrieval of general semantic knowledge (e.g., "At this moment there is a leading candidate in the Republican Party for President. Which of the following candidates is that candidate: Mitt Romney, Senator John McCain, or Rudy Giuliani?"). Additionally, various component processes that could be engaged when answering these different questions (e.g., mental imagery, recall of past experiences, affective processing, and so on) were assessed by an independent group of participants. This showed that three components were recruited to a greater extent when answering questions about the self: personal significance, evoked emotion, and introspection about one's preferences, feelings, and emotions. When these three variables were combined into a composite score of "affective self-relevance," this composite variable was found to account for a large portion of the trial-bytrial variance in activity within the vMPFC–PCC. The authors concluded that the vMPFC (along with the PCC) participates in evaluating aspects of personal significance.

#### **Individual differences in valuing self-reflection**

People differ in the extent to which they attach importance and manifest interest in introspecting about the self and their life (Trapnell and Campbell, 1999). In one study, we found that such individual differences modulate the activity of the vMPFC when people reflect on significant personal experiences (D'Argembeau et al., in press). Participants were asked to approach a set of personally significant memories in two different ways: on some trials, they remembered the concrete content of the events (e.g., what happened, where, when, with whom, and so on), whereas on other trials they reflected on the broader meaning and implications of their memories for the self (e.g., they thought about what the event says about their personality, how they have changed following this event, what they have learned, and so on). Individual differences in interest in this kind of self-reflection were assessed using a validated questionnaire that included items such as "I love exploring my inner self" (Trapnell and Campbell, 1999). We found that a number of brain regions (including the dMPFC, inferior frontal gyrus, middle temporal gyrus, and angular gyrus) were more activated when participants reflected on the meaning of their past experiences compared to when they remembered the concrete content of these experiences. The vMPFC was not consistently activated across participants but, interestingly, there was a positive correlation between the activity of the vMPFC and scores on the questionnaire assessing one's interest in self-reflection. That is, the vMPFC showed increased activity when reflecting on the meaning of past experiences only for participants who have greater interest and willingness to introspect about the self.

#### **Valuing outer aspects of self**

As mentioned above, the vMPFC has been found to be more activated in response to objects that have been assigned to the self compared with objects that have been assigned to another person (Kim and Johnson, 2012, in press). Of particular interest, Kim and Johnson also found that the vMPFC was more activated in response to objects that were more preferred by the participants (as determined by post-scan ratings), but only for objects that had been assigned to the self. Furthermore, the participants' willingness to trade their own objects for the other person's objects was negatively correlated with vMPFC activity. These findings strongly suggest that the vMPFC represents the subjective value of self-related objects. Other studies have shown that the vMPFC responds to the self-relatedness of emotional or rewarding stimuli. Phan et al. (2004) found that the activation of the vMPFC in response to pictures of emotional scenes correlated with the extent to which participants associated to the pictures, especially (but not exclusively) when they explicitly reflected on the selfrelatedness of the stimuli (see also Northoff et al., 2009). Related findings have been reported by de Greck et al. (2008) who found that the response of the vMPFC to pictures of rewarding stimuli (e.g., food items) was greater when the stimuli were judged to be high (compared to low) in self-relatedness (see also Enzi et al., 2009). As noted earlier, there is also evidence that the vMPFC is activated when thinking about persons that tend to be included in one's sense of self, such as close others. From this finding, Krienen et al. (2010) concluded that the vMPFC contributes to "evaluate or provide a signal reflecting the personal significance of close others" (p. 13911). Taken together, these different studies suggest that the vMPFC represents the personal significance of a variety of outer self-related contents.

#### **Summary**

Although relatively few studies to date have directly tested the valuation hypothesis, several lines of evidence converge to suggest that vMPFC activity during self-processing depends on the personal significance of self-related contents. First, increasing psychological distance (in particular, temporal distance) from selfrepresentations leads to decreased activity in the vMPFC during self-reflective thinking. Second, vMPFC activity increases linearly with the personal importance of the self-representations under consideration. Third, individual differences in the interest placed on self-reflection modulate the activity of the vMPFC during selfreflective thinking. Finally, the vMPFC responds to outer aspects of self that have high personal value, such as possessions and close others. Taken together, these findings provide support to the view that the vMPFC contributes to assign personal value to self-related information.

## **PERSONAL SIGNIFICANCE AND PSYCHOLOGICAL HEALTH**

Assigning personal value to self-related contents may be essential for constructing and stabilizing coherent self-representations (Markus, 1977; Pelham, 1991). Indeed, it has been suggested that disturbance in the brain's systems that assign personal significance may contribute to the alterations of self boundaries that are observed in some psychiatric disorders (Feinberg, 2011). In addition, an excessive investment in, and identification with, rigid and dysfunctional self-views may also play an important role in depression and anxiety (Clark and Beck, 2010). It is therefore interesting to note that various forms of psychopathology are characterized by altered patterns of activity in the vMPFC during self-processing. For example, it has been found that the differential activity in the vMPFC when processing self-related compared to non-self-related contents is reduced in schizophrenia (Holt et al., 2011) and absent in autism (Lombardo et al., 2010); depression has been associated with both abnormal increases and decreases in vMPFC activity during self-processing (Lemogne et al., 2012); and patients with social anxiety disorder show atypical modulation of vMPFC activity in response to self-referential comments (Blair et al., 2011). An intriguing possibility is that these alterations in the functioning of the vMPFC may contribute to the abnormalities in the processing of personal significance that are observed in these different disorders.

Some interventions have proven their efficacy in addressing dysfunctional self-views and recent studies suggest that their effects may in part be mediated by a modulation of vMPFC activity during self-processing. Research has shown that the practice of mindfulness meditation – paying attention to one's current experience in a non-evaluative way – has beneficial effects across diverse psychological disorders as well as for well-being (for review, see Brown et al., 2007; Keng et al., 2011). These salutary effects are likely due to multiple mechanisms of actions and may, in part, involve a change in perspective on the self (Holzel et al., 2011). By closely observing the contents of consciousness in a non-judgmental way, practitioners learn to see their thoughts and emotions as transient mental events. Through this process, one adopts a more detached perspective on the self, which may foster a disidentification from, and modification of, rigid and dysfunctional self-views (Holzel et al., 2011; Vago and Silbersweig, 2012) and may lead to more accurate self-knowledge (Carlson, 2013).

Farb et al. (2007) specifically investigated the neural correlates of such change in perspective on the self following mindfulness practice (for a comprehensive review of the neurobiological changes promoted by mindfulness, see Vago and Silbersweig, 2012). Participants who completed mindfulness training were compared with participants who had not yet undergone training while they engaged in two modes of self-reference: in one condition, they were asked to think about the personal meaning and self-descriptiveness of trait adjectives (referred to as "narrative" focus), whereas in another condition they were instructed to monitor their moment-to-moment experience in response to the adjectives (referred to as "experiential" focus). In line with the neuroimaging studies of self-processing reviewed above, narrative self-focus induced activation in several brain regions, including the vMPFC, in both groups of participants. Interestingly, however, individuals who completed the mindfulness training showed larger reductions in vMPFC activity during the experiential (compared with the narrative) focus, along with increased engagement of the right lateral prefrontal cortex, right insula, secondary somatosensory cortex, and inferior parietal lobule. The authors interpreted these findings as representing a shift "toward more lateral prefrontal regions supporting a more self-detached and objective analysis of interoceptive (insula) and exteroceptive (somatosensory cortex) sensory events, rather than their affective or subjective self-referential value" (Farb et al., 2007, p. 319). Another study has shown that mindfulness practice influences functional connectivity between the vMPFC and other regions involved in self-processing, which may in part "reflect a reduction

in emotional appraisal during self-referent processes" (Taylor et al., 2013, p. 12). Although these results are compelling, it should be noted that a study in patients with social phobia failed to find significant changes in vMPFC activity during self-processing following mindfulness training (Goldin et al., 2012), so additional research (in both healthy individuals and in various psychological disorders) is needed to further examine the possible contribution of the vMPFC in mindfulness-induced changes in self-processing.

Other evidence suggests that modifications of patterns of vMPFC activity during self-processing may underlie the restructuration of dysfunctional self-views following cognitivebehavioral therapy in depression (Yoshimura et al., in press). A group of depressive patients underwent a cognitive-behavioral intervention program that involved, among other things, the identification and restructuration of negative self-views and the development of positive thinking about the self. The patients were scanned before and after the therapy while they made selfdescriptiveness judgments on positive and negative traits. Before therapy, the patients showed higher activity in the vMPFC when considering negative compared with positive aspects of the self (see also Lemogne et al., 2012, for a review of studies showing abnormalities of MPFC activity during self-processing in depression). From pre- to post-therapy, there was a decrease in vMPFC activity when thinking about negative aspects of the self and an increase in vMPFC activity when thinking about positive aspects of the self, such that following therapy the patients recruited the vMPFC to a greater extent when considering positive compared with negative aspects of themselves. This shift in patterns of vMPFC activity from pre- to post-therapy may result from a restructuration of the relative value that the patients placed on their positive versus negative self-views, such that positive conceptions of the self are assigned greater significance following treatment.

## **THE vMPFC AND SPONTANEOUS SELF-RELATED THOUGHTS**

The vMPFC is a central hub of the default network – a set of interacting brain regions that show increased activity during "resting" states compared with active, externally focused tasks (Shulman et al., 1997; Gusnard and Raichle, 2001; Mazoyer et al., 2001; Buckner et al., 2008). Although the exact function of this network remains somewhat controversial, a prominent hypothesis is that it supports internal mentation during rest and passive task conditions (Buckner et al., 2008; Andrews-Hanna, 2012). When our attention is not focused on a given task, we spontaneously experience all sorts of thoughts and mental images: we may, for example, revisit a past event or think about things to do in the future (Smallwood et al., 2009; Andrews-Hanna et al., 2010a; Stawarczyk et al., 2011a). In line with the internal mentation hypothesis, a number of studies have linked this kind of spontaneous mental activity to the default network (McKiernan et al., 2006; Mason et al., 2007; Christoff et al., 2009; Andrews-Hanna et al., 2010a; Stawarczyk et al., 2011b).

Recent findings further suggest that the default network comprises multiple subsystems that likely support distinct component processes involved in internal mentation (Andrews-Hanna et al., 2010b). Of particular interest here is the finding that the resting state and explicit self-processing are associated with shared activation in the vMPFC. In a pioneering study, Andreasen et al.

(1995) used positron emission tomography (PET) to investigate similarities and differences in neural activity between the explicit retrieval of autobiographical memories and a rest condition (i.e., lying quietly with no specific instructions about mental activity). They found that the vMPFC and precuneus showed greater activity during both autobiographical memory retrieval and rest compared to a semantic memory condition. Interviews with the participants indicated that they thought about a variety of things during the rest condition, but especially about self-related contents such as past experiences and future activities. The authors concluded that the psychological commonality between the rest and autobiographical memory conditions is that "both involve something personal and highly individual" (p. 1583).

Another PET study investigated the commonalities in brain activation between rest and the explicit reflection on one's personality traits (D'Argembeau et al., 2005). It was found that both conditions were associated with common activation in the vMPFC compared with conditions requiring participants to reflect on nonself-related contents (see also Whitfield-Gabrieli et al., 2011). Furthermore, an analysis of the content of mental activity (using verbal reports and rating scales obtained after each scan) showed that participants spontaneously experienced self-referential thoughts during the rest condition and that the amount of self-referential processing correlated specifically with the activity of the vMPFC. A recent quantitative meta-analysis has confirmed that the resting state and explicit self-processing are associated with common activations in the vMPFC. Qin and Northoff (2011) compared the location of activations in studies on the default network (i.e., brain regions showing stronger activation during the resting state compared to active tasks) with the location of activations associated with various self-related tasks (e.g., trait judgments, autobiographical memory, face recognition, and name perception). These authors found that the resting state and self-related tasks showed overlapping activations in a region of the vMPFC.

Overall, these findings suggest that the vMPFC is engaged in both intentional (in explicit self-referential tasks) and spontaneous (in the resting state) self-processing. In light of the valuation hypothesis, an intriguing possibility is that the activation of the vMPFC during the resting state may signal the personal significance of spontaneous cognitions – be they memories, future thoughts, or other reflections on self-related contents. In this way, the vMPFC might contribute to highlight and select, among the many thoughts and mental images that spontaneously populate our minds in daily life, representations that are likely to have some relevance for guiding our decisions and behavior.

#### **CONCLUDING REMARKS AND FUTURE DIRECTIONS**

Despite extensive evidence that the vMPFC is involved in processing self-related contents, the precise function of this region is still elusive. Here I have suggested that a key dimension that may shed light on this issue is the notion of personal significance. Stimuli and mental representations that refer or relate to the self tend to be assigned unique value, and the function of the vMPFC may precisely be to evaluate or represent such significance. The notion of personal significance should be conceived as a continuum, such that some self-related contents are assigned more value than others. Furthermore, the personal value of a given content is probably not fixed once for all, but may instead vary according to the context and evolve across time. By flexibly assigning degrees of value to self-related contents, the vMPFC may play an important role in the construction, stabilization, and modification of self-representations, and ultimately in guiding our choices and decisions. Although this is certainly not the sole ingredient of our sense of self, the representation of personal significance in the vMPFC may contribute to establish the fundamental distinction between self and non-self that each of us subjectively experiences.

While the evidence reviewed in this article provides support to the valuation hypothesis, many questions remain and this hypothesis clearly requires further investigation. First, the notion of personal significance is admittedly quite vague and requires further refinement. The relevance of something can be considered at numerous levels – from basic physiological needs to higherorder goals, motives, and values – and it will be important in future work to dissect the precise dimensional features of relevance that may be represented in the vMPFC. A related question is whether personal significance can be entirely reduced to valuation, as defined in the neuroeconomic literature, or whether they represent (at least partly) dissociable processes (see Northoff and Hayes, 2011, for further discussion of this issue). Recent findings suggest that different dimensions of value (i.e., economic vs. core value) can be dissociated in the MPFC (Brosch et al., 2012) and that the vMPFC can process value independently of self-relevance (Nicolle et al., 2012). Thus, it remains to be determined whether the same valuation scale is applied to self-related versus non-selfrelated contents or whether the two types of contents are processed along qualitatively different dimensions of value. From this perspective, it will also be important to investigate whether and how different value dimensions are processed by the vMPFC and other brain structures that have been associated with relevance detection, such as the amygdala and ventral striatum (see e.g., Sander et al., 2003;Adolphs, 2010). Interestingly,it has been found that the vMPFC is functionally coupled to the amygdala and ventral striatum when processing self-related contents (Schmitz and Johnson, 2006), but the specific contribution of each of these areas remains to be determined.

Another question relates to the functional specialization within the vMPFC. In this article, I have considered the vMPFC as a whole but this is of course a fairly large area that comprises multiple subregions (Ongur et al., 2003). Activations in some neuroimaging studies of self-processing are quite extensive, encompassing multiple vMPFC subregions (e.g.,D'Argembeau et al., 2010b),whereas other studies have reported activations in specific subregions, such as the rostral anterior cingulate cortex (e.g., Ersner-Hershfield et al., 2009), the rostral vMPFC (BA 10) (e.g., Benoit et al., 2010), or the medial orbitofrontal cortex (e.g., Hughes and Beer, 2012).

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Finally, the role of automatic and controlled processes in the assignment of personal significance deserves further attention. The processing of personal significance is not necessarily conscious and deliberate, and in fact it likely operates outside of awareness most of the time (Bargh and Morsella, 2008). As already noted, current evidence suggests that the vMPFC may automatically confer degrees of value to self-related contents (D'Argembeau et al., 2012a), but of course this does not mean that this process cannot be modulated by conscious awareness; indeed, the research reviewed above suggests that mindfulness practice can lead to significant changes in how one approaches self-related contents. Identifying the exact conditions under which the processing of personal significance can be influenced by conscious monitoring processes, and the role of the vMPFC in this respect, is an important avenue for future research that could potentially deepen our understanding of healthy and unhealthy ways of relating to oneself.

#### **ACKNOWLEDGMENTS**

Arnaud D'Argembeau is a Research Associate of the Fonds de la Recherche Scientifique-FNRS (www.frs-fnrs.be).

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 26 April 2013; accepted: 27 June 2013; published online: 10 July 2013. Citation: D'Argembeau A (2013) On the role of the ventromedial prefrontal cortex in self-processing: the valuation hypothesis. Front. Hum. Neurosci. 7:372. doi: 10.3389/fnhum.2013.00372 Copyright © 2013 D'Argembeau. This is an open-access article distributed under the terms of the Creative Commons Attri-*

*bution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.*

# The world according to me: personal relevance and the medial prefrontal cortex

# **Anna Abraham1,2\***

<sup>1</sup> Department of Community Medicine and Behavioural Sciences, Faculty of Medicine, Kuwait University, Safat, Kuwait

<sup>2</sup> Department of Clinical Psychology, Justus Liebig University Giessen, Giessen, Germany

#### **Edited by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada

#### **Reviewed by:**

Athena Demertzi, University of Liège, Belgium Francesca Garbarini, University of Turin, Italy

#### **\*Correspondence:**

Anna Abraham, Department of Community Medicine and Behavioural Sciences, Faculty of Medicine, Kuwait University, P. O. Box 24923, Safat 13110, Kuwait e-mail: annaabr@gmail.com

More than a decade of neuroimaging research has established that anterior and posterior cortical midline regions are consistently recruited during self-referential thinking. These regions are engaged under conditions of directed cognition, such as during explicit selfreference tasks, as well as during spontaneous cognition, such as under conditions of rest. One of the many issues that remain to be clarified regarding the relationship between self-referential thinking and cortical midline activity is the functional specificity of these regions with regard to the nature of self-representation and processing.The functional profile associated with the medial prefrontal cortex (mPFC) is the focus of the current article. What is specifically explored is the idea that personal relevance or personal significance is a central factor that impacts how brain activity is modulated within this cortical midline region. The proactive, imaginative, and predictive nature of function in the mPFC is examined by evaluating studies of spontaneously directed cognition, which is triggered by stimulus-associated personal relevance.

#### **Keywords: self-referential thinking, spontaneous cognition, reality-fiction distinction, default mode network, self relevance**

*"Reality leaves a lot to the imagination."*

(John Lennon)

More than a decade has passed since the publication of the first neuroimaging study of self-referential thinking (Kircher et al., 2000). The original finding of the involvement of cortical midline structures (CMS), such as medial prefrontal and posterior cingulate areas, have been corroborated numerous times since then (Northoff and Bermpohl, 2004; Qin and Northoff, 2011).

The CMS are part of a larger network of areas, commonly referred to as the default mode network (DMN),which are engaged not only during self-referential thought but also during mental state reasoning, autobiographical memory retrieval, episodic future thinking, and moral decision making (Buckner et al., 2008). This has led to several (sometimes overlapping) hypotheses regarding the function of this network as involving either self-projection (Buckner and Carroll, 2007), scene construction (Hassabis and Maguire, 2009), constructive episodic simulation (Schacter et al., 2008), or self-relatedness evaluation (Legrand and Ruby, 2009).

Among the many unanswered questions in this research domain is the functional specificity of each of these regions vis-à-vis the self, given the wide range of social and selfrelevant contexts in which this network is activated. The objective in this article is explore the potential role of the ventral (including anterior) aspects of the medial prefrontal cortex (mPFC; dominantly corresponding to Brodmann Areas 10, 32, 11, and 12) in coding for personal relevance or significance, which can be triggered either externally (explicitly or

implicitly stimulus-associated) and/or internally (such as during stimulus-independent thought)<sup>1</sup> .

# **SELF-RELATEDNESS AND THE mPFC**

The idea that the mPFC is responsive as a function of the degree of self-relatedness is not new. In general, the closer the similarity between oneself and another person, the stronger the activation in the mPFC when processing information related to these protagonists, as well as the more ventral the engagement of the mPFC (Mitchell et al., 2006). This pattern of findings has been reported across a range of contexts in which explicit evaluations concerning self and others are made (van der Meer et al., 2010; Murray et al., 2012).

Much of the discourse in the field focuses on parallels and distinctions between neurocognition underlying such kinds of "explicit self-reference" in comparison to "default mode selfreference" (Whitfield-Gabrieli et al., 2011). The latter occurs under conditions of rest or low cognitive demand. However, the ventral mPFC is also selectively engaged in other contexts that are implicit in nature, and in which no explicit self-relatedness judgments are required (Moran et al., 2009; Seitz et al., 2009; Rameson et al., 2010). For instance, the mPFC was responsive to angry body expressions only when a stranger's body was directly facing oneself, but not when it was turned away (Grèzes et al., 2012). Research on reputation processing has revealed enhanced activity in the mPFC during self-referential thinking in the presence of observers

<sup>1</sup>The focus of this paper is limited to frontal cortical midline structures as evidence showing that activity in posterior midline regions, such as the precuneus, posterior cingulate, and retrosplenial cortices, are modulated by self-relatedness, self-relevance, personal relevance, and/or personal significance is not as clear-cut.

compared to when the participants were unobserved (Izuma et al., 2010). Findings from the ERP literature have also demonstrated that the degree of self-relevance (low, moderate, high, non-self) associated with names of persons or places that were presented to participants, modulated P2 activity, which indexes enhanced attentional recruitment, and P3 activity, which indexes increased cognitive processing (Chen et al., 2011). Moreover, P3 activity, that was elicited when hearing one's own name, was found to be positively correlated with the degree of brain activity in the mPFC (Perrin et al., 2005).

Such implicit contexts are not equivalent to those of explicit self-reference and default mode self-reference. This is because they involve stimulus-induced self-reference which leads to spontaneous cognition that is not necessarily task-relevant (in that it is not necessary to process the stimuli in a self-referential manner in order to successfully perform the task). As such contexts are broader than those involving "self-relatedness," the term "selfrelevance" is commonly adopted as it more accurately captures the function associated with ventral mPFC activity. Indeed, this fits with dominant ideas in the field regarding the function of this brain region as mediating the "identification and appraisal of *stimulus-induced* self relevance" (author's italics) (Schmitz and Johnson, 2006, 2007). In contrast, dorsal regions of the mPFC are held to mediate "cognitive control in the generation of explicitly self-referential decisions" (Schmitz and Johnson, 2007).

One question that arises in this context is whether such identification and appraisal processes that trigger spontaneous cognition are also recruited when evaluating contexts that may be personally significant but where the "self" is not directly involved. How does the concept of self-relevance differ from that of personal relevance?

## **THE CASE FOR PERSONAL RELEVANCE**

The word "self" is immediately suggestive of a strong link to one's subjective or personal identity, such as the knowledge of one's abilities and skills, personality attributes, preferences, and so on. The object in question in such cases is the "self as I" or the "self as me" (James, 1891). For instance, answering the question "Would you describe yourself as ambitious?" would more actively require you to evaluate this statement in terms of your own self concept than questions such as "Would you describe Barack Obama as ambitious?" or "Would you describe Cinderella as ambitious?"

The concepts of "self-relatedness" or "self-relevance"may apply *prima facie* in contexts related to highly similar or related others (e.g., one's mother) as such entities are obviously relevant with regard to one's own self-identity. However, there are several situations in which the applicability or generalizability of such concepts are not as clear-cut. For instance, my favorite coffee mug may be personally relevant to me, but not necessarily self-relevant in the strict sense of being part of my core self-identity. So the concept of "personal relevance" is not entirely synonymous with that of "selfrelevance" as it can be applied to a wider range of situations. So what is evidence is there for the modulation of the ventral mPFC as a function of personal relevance?

Investigations of how we make reality-fiction distinctions provide some insight into this question. In the first of these studies (Abraham et al., 2008), participants were presented with sentences in which a real person engaged with either a known real entity (e.g., George Bush) or a fictional entity (e.g., Cinderella) in informative (e.g., heard about) or interactive contexts (e.g., spoke to). Following this, subjects had to determine whether this scenario was possible or not given the constraints of our real world. Processing information about real people led to activations in two brain regions, the anterior mPFC and the posterior cingulate cortex (PCC).

The findings from this explorative study were interpreted in terms of the functional profile associated with these brain regions. Their engagement was postulated to reflect the stimulus-induced spontaneous access and integration of many different kinds of internally generated information (episodic, self-referential, visceral, etc.). Even in the absence of an externally directed behavioral goal that imposes such demands, this information is *automatically* accessed with the introduction of a familiar entity into one's stream of consciousness. The greater the familiarity, the higher the personal relevance. Activity in these brain regions was therefore held to be spontaneously modulated by the degree of stimulus-associated personal relevance.

The basic premise was that reality (relative to fiction) is processed in terms of subjectively coded representations in the brain. This was attributed to the fact that, among the major differences between familiar famous people and fictional characters, is the amount of information that we can readily draw upon in reference to them and the frequency with which we encounter information regarding them in our daily lives. For instance, we are regularly bombarded with information concerning famous people through the media. Even if we are not likely to encounter these people in reality, they nevertheless occupy a significant space in our social world, unlike fictional characters.

Moreover, although we can arrive at quite a detailed understanding of a fictional world (such as that of Cinderella), we still have, relatively speaking, very limited information about her world in comparison to what we know about our own world. With a famous real entity, such as George Bush, one has access to different types of information about him: the degree of perceived attractiveness, his position in the social hierarchy, the degree of influence his politics has had on one's own life and that of others, what moral values he stands for, one's personal feelings toward him (e.g., like/dislike, respect/irreverence), the last time one saw him on television or read about him in the newspaper, etc. So reading about a familiar entity, via stimulus-induction, leads to the spontaneous access, integration, and coordination of many different kinds of information (e.g., semantic, episodic, emotional, self-referential, evaluative, interoceptive), even if this information is unnecessary for the task at hand. In fact, the role of the mPFC has been documented in research on salience processing and valuation, particularly in the presence of personal involvement (Somerville et al., 2010; Roy et al., 2012).

These *ad hoc* speculations were corroborated in a follow-up fMRI study (Abraham and von Cramon, 2009). Familiar individuals within our sociocultural world, such as celebrities or cultural icons, would be expected to be more relevant to us compared to fictional characters because they occupy a real space in our shared social world. But individuals who are part of our intimate circle of family and friends would be even more personally significant as their actions have a direct bearing on our lives. If the mPFC codes for personal relevance, the activation profile seen in this brain region when processing information concerning friends (high relevance), famous people (medium relevance) and fictional characters (low relevance) should vary accordingly. The fMRI results confirmed these expectations as the anterior and ventral mPFC was most strongly engaged during high relevance contexts (e.g., involving one's mother), moderately engaged in medium relevance contexts (e.g., involving George Bush) and least engaged in low relevance contexts (e.g., involving Cinderella) (Abraham and von Cramon, 2009).

This ties in well with other work that has shown that ventral aspects of the mPFC are engaged when making judgments about others who are similar to us in terms of sociopolitical views (Mitchell et al., 2006), and who are socially relevant to us (Krienen et al., 2010). Merely considering the perspectives of one's own preferred candidate relative to that of the opponent prior to the 2008 US presidential elections was reflected in a greater mPFC activity (Falk et al., 2012). Moreover, research in the field of cultural neuroscience has revealed that compared to participants of Western origin, the mPFC was more strongly engaged in Chinese participants, not only during self-referential processing, but also during information processing related to one's mother (Zhu et al., 2007). The rationale offered for this pattern of findings was that China represents an interdependent culture where the conceptual representations of close others are more personally significant than in the case of independent cultures, such as that of Western Europe. Conceptual representations of close others are hence more tightly coupled to conceptual representations of oneself within the semantic networks of people from interdependent cultures relative to those from independent cultures.

While each of the aforementioned investigations tapped some form of explicit self-reference (self-relatedness or self-relevance based), the reality-fiction distinction studies were implicit investigations of personal relevance (Abraham et al., 2008; Abraham and von Cramon, 2009). This is because neither self-referential nor close-other-referential judgments with reference to one's self concept were necessary for task completion, and the self concept was not passively or indirectly evoked (through one's own name or through egocentric perspective taking).

As such, the findings revealed that the anterior ventral mPFC is spontaneously modulated by the degree of stimulus-associated personal relevance. Indeed, this fits with the functional profile associated with this region as the constructive processes

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orchestrated by anterior regions of the ventral mPFC have been highlighted as ". . . one of combining elemental units of information – from sensory systems, interoceptive cues, long-term memory – into a gestalt representation of how an organism is situated in its environment, which then drives predictions about future events" (Roy et al., 2012).

A powerful demonstration of this principle was reported in a recent article where the influence of personal significance on perception was investigated by having participants tag neutral shapes (e.g., triangle) with labels for themselves, their best friend, or an unfamiliar other (Sui et al., 2013). Self-tagged responses were associated with greater activity in the ventral mPFC and conferred significant behavioral advantages in terms of response speed. This finding of ventral mPFC involvement even in the context of a novel and arbitrary association between neutral stimuli and personal significance builds on previous work where enhanced memory effects (Cunningham et al., 2011) as well as greater mPFC engagement (Kim and Johnson, 2012) were observed for even transitory selfobject associations. Together, these findings correspond well to the idea that personal significance is automatically encoded in the brain and modulates information processing accordingly (Roye et al., 2007).

## **CONCLUSION**

The central proposal of this article is that the ventral mPFC is responsive as a function of personal relevance. One of the critical factors to note here is that although the engagement of this brain region is "stimulus-induced," its function cannot be merely explained in terms of explicit self-relevant or self-related task demands. The ventral mPFC is not only involved in explicit contexts, where subjects generate conscious evaluations of oneself or close others, but also in implicit contexts, where, although selfrelevant stimuli are presented, no self-referential judgments need to be made (Abraham and von Cramon, 2009; Moran et al., 2009). This illustrates not only the proactive and predictive nature of information processing in the brain (Bar, 2009; Bubic et al., 2010), but also the fact that stimulus-induced spontaneous modulations of the brain can be used to understand such dynamic facets of neurocognitive function.

#### **ACKNOWLEDGMENTS**

This work was supported by the German Research Foundation (DFG; Grant AB 390/2-2 awarded to the author).

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 30 April 2013; accepted: 17 June 2013; published online: 02 July 2013.*

*Citation: Abraham A (2013) The world according to me: personal relevance and the medial prefrontal cortex. Front. Hum. Neurosci. 7:341. doi: 10.3389/fnhum.2013.00341*

*Copyright © 2013 Abraham. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.*

# What about the "self" is processed in the posterior cingulate cortex?

# **Judson A. Brewer <sup>1</sup>\*, Kathleen A. Garrison<sup>1</sup> and Susan Whitfield-Gabrieli <sup>2</sup>**

<sup>1</sup> Department of Psychiatry, Yale University, New Haven, CT, USA

<sup>2</sup> Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

#### **Edited by:**

Pengmin Qin, University of Ottawa, Canada

#### **Reviewed by:**

Pawel Tacikowski, Karolinska Institute, Sweden Robert Leech, Imperial College London, UK

#### **\*Correspondence:**

Judson A. Brewer, Department of Psychiatry, Yale Therapeutic Neuroscience Clinic, Yale University School of Medicine, 300 George Street, Suite 901, New Haven, CT 06511, USA e-mail: judson.brewer@yale.edu

In the past decade, neuroimaging research has begun to identify key brain regions involved in self-referential processing, most consistently midline structures such as the posterior cingulate cortex (PCC). The majority of studies have employed cognitive tasks such as judgment about trait adjectives or mind wandering, that have been associated with increased PCC activity. Conversely, tasks that share an element of present-centered attention (being "on task"), ranging from working memory to meditation, have been associated with decreased PCC activity. Given the complexity of cognitive processes that likely contribute to these tasks, the specific contribution of the PCC to self-related processes still remains unknown. Building on this prior literature, recent studies have employed sampling methods that more precisely link subjective experience to brain activity, such as real-time fMRI neurofeedback. This recent work suggests that PCC activity may represent a sub-component cognitive process of self-reference – "getting caught up in" one's experience. For example, getting caught up in a drug craving or a particular viewpoint. In this paper, we will review evidence across a number of different domains of cognitive neuroscience that converges in activation and deactivation of the PCC including recent neurophenomenological studies of PCC activity using real-time fMRI neurofeedback.

**Keywords: default mode network, real-time fMRI, meditation, posterior cingulate cortex, self-referential processing, mind wandering, resting state, craving**

# **INTRODUCTION**

Over a decade ago, using the simple task instruction of "lie still and don't do anything in particular," Raichle et al. (2001) discovered that the posterior cingulate cortex (PCC) was functionally coupled with other brain regions now considered the default mode network (DMN). Numerous studies have since implicated the PCC in a host of functions ranging from those that elicit activation such as mind wandering, social cognition, and drug craving, to those that elicit deactivation such as focused attention and meditation. Many of these studies have interpreted the findings in terms of the PCC being involved in self-related aspects of cognitive processing. However, it is still unclear what aspects of the "self" are processed in the PCC. Given the growing body of evidence on PCC function from different domains, including self-related processing, social cognition, and addiction, among others, it may now be possible to identify potential phenomenological descriptors that are common across domains. In this paper, we propose that PCC activity may be related to a cognitive process of being "attached to" or "caught up" in one's experience. We will describe being "caught up" in experience, and then discuss evidence from cognitive and clinical neuroscience that provides a basis for this hypothesis. We will first discuss findings that PCC activation is related to being "caught up in" experience, including self-related and social cognitive processing, disruption of attention, and craving. We will then discuss findings that PCC deactivation is related to not being "caught up in" experience, including present-centered awareness or attention. For the purpose of this review, we will

focus on a specific functionally defined sub-region of the PCC most associated with the DMN (Leech et al., 2012), though this brain region likely supports other cognitive functions as well. Additionally, we will focus our discussion on studies measuring activity rather than functional connectivity; though the latter is related in an important way, it is beyond the scope of this paper and has been recently reviewed elsewhere (e.g.,Whitfield-Gabrieli and Ford, 2012). Finally, we will explore PCC activity as a possible marker of getting "caught up in" experience, pointing to a likely larger network of brain regions involved in this cognitive process.

#### **WHAT DOES IT MEAN TO BE "CAUGHT UP IN" EXPERIENCE?**

We have all been caught up in experience – whether positive or negative. This can happen when we have a disagreement with a loved one or colleague that goes on and on to the point where we don't even remember what we were arguing about – we get attached to a certain viewpoint, or even just "being right" and can't let go no matter how ridiculous the argument becomes. We can also get caught up in something by being pulled into our experience; for example, we start an internet search for something, get distracted by something else that looks interesting, then something else, and on and on until we find that we are on some random website and don't remember how we got there. Though there are likely differences between getting caught up in positive or negative experiences, there may be a shared experiential component; we will include both of these in the broader category of getting caught up in experience as a first pass at identifying neural correlates therein. In fact, there is precedent for brain regions subserving oppositely valenced affective experience, as has been seen in previous studies of appetitive and aversive stimuli (Carlezon and Thomas, 2009).

Being caught up in experience can be noticeable; for instance we notice that we contract when someone is yelling at us. At other times, the experience of being caught up may be subtle, or we may be so engrossed – as is with the case of daydreaming – that we aren't aware that we are caught up until after the experience has passed. Though being caught up in experience may be common from an experiential standpoint,from a neuroscientific framework, it likely involves a number of overlapping cognitive processes, including self-referential/internally oriented networks, emotion processing, social cognition, and evaluative/judgment systems among others. As each of these systems in turn involves complex networks of brain regions, it may be helpful to look across multiple cognitive domains to identify a common experiential element. Is the PCC a good candidate brain region to begin this exploration? In the following sections, we will give brief experiential examples of being caught up in one's experience, and explore related cognitive domains and their convergence in neural activation patterns.

# **PCC ACTIVATION IS RELATED TO BEING CAUGHT UP IN MENTAL CONTENT**

# **PCC ACTIVITY IS ASSOCIATED WITH SELF-RELATED PROCESSING What is it like if someone asks if you think you're "outgoing," "patient," or "nosy"? Are we attached to certain concepts of ourselves? Do we get caught up in these evaluations? What is this experience like and how does this map onto our brain activity?**

Aside from studies of the resting state, perhaps the best-studied category of cognitive tasks that activate the PCC are those involving self-related processing. Early work by Kelley et al. (2002) used a simple task of presenting trait adjectives to subjects during fMRI and asking "Does the adjective describe you?" ("self" condition), or for comparison, "Does the adjective describe current U.S. President George Bush?" ("other" condition). Relatively greater PCC activity was found for the "self" as compared to the "other" condition (Kelley et al., 2002). These findings have been since replicated (e.g., Heatherton et al., 2006) and extended using other sensory modalities such as aural presentation of adjectives (Johnson et al., 2002) or reflective self-awareness of personality and physical appearance (Kjaer et al., 2002). A meta-analysis performed by Northoff et al. (2006) concluded that midline structures including the PCC and medial prefrontal cortex (mPFC) comprise a "core," "mental," or "minimal" self (Northoff et al., 2006).

In this meta-analysis (Northoff et al., 2006), Northoff also speculated that overlap between self-referential and resting state processing should include predominantly interoceptive stimuli. This assertion has gained empirical support in recent years. For example, studies using experience sampling have found that close to 50% of waking life is spent mind wandering to past and future events (Killingsworth and Gilbert, 2010). Mind wandering has been shown to activate the PCC (Weissman et al., 2006; Mason et al., 2007) as do cognitive tasks that elicit future oriented thinking (Andrews-Hanna et al., 2010). These findings suggest that there is an experiential default mode (mind wandering) associated with PCC activity. Bringing these findings together, Whitfield-Gabrieli et al. (2011) directly compared task-independent resting state with task-dependent self-related processing during evaluation of trait adjectives and found a distinct convergence of brain activations in the PCC and mPFC.

Most studies of self-related processing find activations in both the PCC and mPFC, brain regions that have also been shown to be tightly functionally coupled (Fox et al., 2005; Andrews-Hanna et al., 2010). Anatomical and functional studies have begun to distinguish the roles of the PCC and mPFC in self-related processing. For example, the mPFC appears to integrating information gathered from the internal and external environment and relay it to the PCC (Ongur and Price, 2000; Ongur et al., 2003). Functional imaging studies of the classic hallucinogen psilocybin have found that psilocybin leads to decreased functional coupling of the PCC and mPFC and increased coupling between the mPFC and task-positive brain regions such as the dorsolateral prefrontal cortex (dlPFC) (Carhart-Harris et al., 2012). Psilocybin ingestion is reported to induce an "egoless" or "selfless" state where the boundary between self and other is blurred. One interpretation of these findings is that decreased coupling between the PCC and mPFC with psilocybin corresponds with the subjective experience of a less egoic state, or less "self."

However, recent meta-analyses by Legrand and Ruby (2009) and Qin and Northoff (2011) have suggested that a more subtle process than just the subjective experience of "self" may be occurring in the PCC. Legrand and Ruby suggested that familiarity with an object might drive PCC activation rather than self-reference. Qin directly tested this by comparing results from imaging studies of self, familiarity, other, and rest. Interestingly, all four categories showed PCC activation!When contrasted, the self category showed robust mPFC activation relative to familiarity, other, and rest, suggesting that there may be a specific cognitive aspect of selfreferential processing that is mediated by the mPFC. So what do these four task categories have in common? Agreeing with Legrand and Ruby, Qin suggested that regions such as the PCC may serve as a general evaluation or judgment system.

Consistent with this interpretation, additional self-related processing tasks that may tap into the construct of evaluation or judgment have been found to elicit PCC activity. For example, Johnson et al. (2006) compared reflection on promotion goals (make good things happen) and prevention goals (keep bad things from happening) and found that the PCC was activated by both conditions, but more so by prevention goals. In a related study, Strauman et al. (2012) found that prevention goal priming was specifically associated with PCC activity irrespective of the degree of negative valence of the prompt. If not negative valence, what is it about prevention goals that preferentially activates the PCC? Johnson speculated that PCC activity may be more related to differences in social significance, representational context, or aspects of subjective experience of self, among others. Another study used a self-evaluation task in which individuals chose between two music CDs that they had previously rated as equivalent, and then reported on how much they liked the chosen CD (a phenomenon termed "choice justification"). PCC activity was associated with an

increase in liking for chosen CDs, but not a decrease in liking for rejected CDs (Salmoirago-Blotcher et al., 2013). Again, the valence of self-related processing did not specifically relate to PCC activity.

Together these studies support Legrand and Ruby and Qin's suggestions that evaluation or judgment of experience may be represented in PCC activation – "ought to" goals are often more evaluative than promotion goals, and this may be similar to choice justification, where we get caught up in defending our choices, even to ourselves. If evaluation or judgment overlaps with being caught up in experience, it may provide a parsimonious explanation for how these findings line up with the decreased functional coupling found with psilocybin – the mPFC may subserve more cognitive elements of self, while the PCC functions to evaluate or judge how one *relates* to one's experience: how much they are caught up in it. If this is the case, this relational aspect should find overlap with other domains of experience.

## **PCC ACTIVITY IS ASSOCIATED WITH SOCIAL COGNITIVE PROCESSING What is it like when we see a co-worker take credit for another's work? What is it like when someone asks us for spare change on the street? Is there a common social cognitive process whereby we get caught up in moral dilemmas?**

Recent work in cognitive neuroscience has demonstrated a role for the PCC in social processing, such as mentalizing, evaluative judgments, and sensitivity to moral issues, among others. A recent meta-analysis of neuroimaging studies in social cognition (Sperduti et al., 2012) found consistent PCC activation related to internal and external agency attribution, perspective taking, observing social interactions, self-related thinking, and causal attribution of social events. For example, a study by van Veen et al. (2009) used an induced compliance procedure in which subjects made a series of false statements to mislead an innocent person to generate cognitive dissonance, and found activity in the dorsal anterior cingulate, anterior insula, and PCC, possibly representing cognitive conflict, negative emotional arousal, and self-related processing, respectively. In another fMRI study (Arsenault et al., 2013), PCC activity correlated with attributional evaluation processing of valenced sentences describing socially relevant everyday situations, more so in the right PCC for positive sentences, and more so in the left PCC for negative sentences. These findings suggest that PCC activity is related to social evaluation.

Another aspect of social cognitive processing shown to engage the PCC is moral dilemma, which may be distinguished as issues related to care, such as benevolence, compassion, and the desire to liberate others from need, or related to justice, such as fairness, impartiality, and the desire to liberate others from injustice. Caceda et al. (2011) presented story segments designed to evoke moral dilemma and found partial neural segregation between care, justice, and neutral issues. The PCC, among other regions, was implicated in processing of both care and justice issues relative to neutral issues. The authors suggested that the purported role of the PCC in autobiographical memory is that interpretive awareness of care issues in moral conflict may be informed by memories of past moral situations, decisions, and outcomes, as well as selfawareness, personal beliefs, and positive emotions. Relatedly, for justice issues, the PCC may modulate predictive social perceptions. Morey et al. (2012) studied guilt and social consequence, and

found that the PCC, among other regions, was more strongly activated for actions leading to harm to others relative to oneself, and suggest that actions involving guilt may lead to greater preoccupation with self-actions rather than thoughts about harm caused to others.

These studies suggest that the PCC plays a role in a range of social situations. What is common between moral dilemmas, justice issues, and guilt, among others? What is the experience like when we are faced with moral issues regarding ourselves or others, or guilt that may come as a consequence of our actions? Perhaps similar to self-related processing, there is an element of mental clenching around or being caught up in the experience. It is interesting to note that this appears to occur even for imagined scenarios, such as those in the fMRI studies discussed here.

#### **PCC ACTIVITY IS ASSOCIATED WITH DISRUPTION OF ATTENTION What is it like to be interrupted by a text or email notification on your cell phone or computer?**

A general task-related decrease of PCC activity has been reported (e.g., Greicius et al., 2003), and task-related increases in PCC activity have been found during lapses of attention. For example, Eichele et al. (2008) found that PCC activity predicts response errors in flanker tasks, and Esposito et al. (2006) found a signal increase and spatial decrease of the PCC activation with working memory load.

Relatedly, PCC activity has been associated with poorer task performance (Wen et al., 2013). For example, increased PCC activity has been associated with lapses in attention that affect task performance, such as in trials preceding errors in a go/no-go task (Li et al., 2007) or with increased reaction time in a demanding task (Weissman et al., 2006; Hinds et al., 2013). In these studies, PCC activity leading to distraction from task performance may reflect mind wandering (Mason et al., 2007). Weissman et al., found that just prior to lapses in attention, the PCC showed increased activity, possibly indicating a shift from the external world to internal mentation. Using real-time fMRI, Hinds et al., found that presenting stimuli during relatively increased DMN activation resulted in significantly slower reaction time compared to presentation during greater activation in the supplementary motor cortex. Another study by Otten and Rugg (2001) used an incidental learning task to study unsuccessful memory encoding, and found greater activation in the PCC and other regions during subsequently forgotten words.

These studies provide evidence for a correlation between increased PCC activity and poorer task performance. With regard to the actual subjective experience of mind wandering or lapses in attention, it is possible that when attention is pulled away from a task, this may manifest as being caught up in the experience, with associated increases in PCC activity.

#### **PCC ACTIVITY IS ASSOCIATED WITH CRAVING What is it like to crave a piece of chocolate?**

Craving, perhaps one of the most obvious experiences of being caught up in experience, is described clinically and experimentally in terms of desire, urge, want, and need (Tiffany and Wray, 2012); it has been associated with PCC activity in smoking and drug addiction. For example, Brody et al. (2007) showed that

smokers resisting cue-induced craving strongly engage the PCC. Similarly, preferential processing of smoking cessation messages highly tailored to the smoker was associated with PCC activity (Chua et al., 2009), possibly in part because the messages were self-related and/or personally meaningful (which also may be more effective at inducing craving). In a case study, a lesion to the PCC led to a disruption of the individual's nicotine addiction, reported as an immediate loss of cigarette craving, with no urge to smoke at all (Jarraya et al., 2010). Related to this, a larger lesion study (Naqvi et al., 2007) found that smokers with damage to the insula were more likely to quit smoking, associated with loss of urge to smoke, and another study found that increased connectivity between the PCC and the insula in smokers may be attenuated by anti-smoking medications (Carim-Todd et al., 2013).

The relationship between PCC activity and craving has also been reported in studies of drug addiction. In a study by Garavan et al. (2000), cocaine users and cocaine-naïve individuals watched videos of two men smoking crack cocaine to induce cocaine craving during fMRI, leading to activations in the PCC among other regions in cocaine users but not controls. PCC activation was also found in response to watching an evocative sexual video, but not in response to watching a nature video, suggesting that the normal endogenous drive state or craving response may be seated in the PCC (Garavan et al., 2000).

Related to our introductory example of chocolate craving, Yokum and Stice (2013) found reduced activity in the PCC when individuals were asked to think about the long term costs or benefits of eating or not eating and attempt to suppress food cravings, though in this paradigm, it may be difficult to distinguish contributions of the PCC to being "on task" vs. suppressing cravings. Overall, the PCC appears to be involved in aspects of craving, as shown by functional neuroimaging and lesion studies in a number of contexts including smoking, drug addiction, food, and sex. As craving has been specifically described as being caught up in an experience, it may provide the most direct evidence for how being caught up may activate the PCC. With all of these cognitive domains converging in PCC activation, are there opposing cognitive domains that deactivate the PCC, providing complementary evidence for its role in getting caught up in experience?

# **PCC DEACTIVATION IS RELATED TO PRESENT-CENTERED AWARENESS OR ATTENTION**

#### **What is it like to be mindful of the present moment, to allow thoughts to arise without getting caught up in them?**

The previous sections have laid out a number of different cognitive experiences that modulate PCC activity. We now turn to studies that show PCC deactivation related to present-centered awareness or attention. In addition to general task-related PCC deactivation, a role for the PCC in getting caught up in experience is supported by the deactivation of this brain region during tasks specifically designed to "not get caught up" such as focused attention or meditation. For example, McKiernan et al. (2003) found that the magnitude of task-induced PCC deactivation increased with task difficulty. Similarly, Wen et al. (2013) found that mean PCC BOLD signal is negatively correlated with accuracy in a spatial visual attention task. Meditation, operationalized for the fMRI setting, may be considered a form of focused attention toward the present moment and away from mind wandering and self-related thinking. In work from our research group, we have found that three types of meditation practices specifically deactivate the PCC in experienced meditators as compared to novices (Brewer et al., 2011). In this study, meditators also reported less mind wandering during meditation than novices. Based on these earlier findings, we have conducted real-time fMRI neurofeedback studies in which we have found that real-time feedback from the PCC corresponds to the subjective experience of mind wandering (increased PCC activity) and focused attention (decreased PCC activity) in meditators and novices, and that meditators are able to volitionally decrease a feedback graph representing PCC activity (Garrison et al., 2013b). Pagnoni (2012) also reported less mind wandering in meditators, as well as a lower relative incidence of elevated PCC activity and better performance on a visual attention task.

A particular advantage of real-time fMRI neurofeedback over standard offline analysis is that it captures variability within blocks of time that would traditionally be regressed to a mean. As cognitive states fluctuate significantly over the course of a 1–3 min block, these transient changes can now be more precisely linked to brain activity to improve characterization therein. We have begun to test the specific hypothesis that the PCC is involved in getting caught up in mental content, using neurophenomenological studies of real-time feedback from the PCC in experienced meditators. In a recent study (Garrison et al., 2013a) meditators were asked to meditate for short (1 min) real-time fMRI runs with feedback from the PCC and immediately report their experience during the meditation. Meditators performed focused attention on the breath meditation while viewing a dynamic feedback graph representing percent signal change in the PCC relative to a baseline task, and were asked to describe their experience during the meditation after each run. Feedback graphs paired with self-reports were analyzed using grounded theory to derive specific testable hypotheses about how PCC activity corresponds to the subjective experience of meditation. Overall, we found that the subjective experience of "undistracted awareness" and "effortless doing" corresponded with PCC deactivation, and "distracted awareness" and "controlling" corresponded with PCC activation. Specifically related to the current review, in many cases meditators reported instances of mind wandering that did not lead to PCC activity, suggesting that the PCC may be involved in something more than the thoughts themselves, such as getting caught up in experience, as suggested by the studies described above.

For example, during a real-time feedback run in which a meditator was asked to increase a feedback graph representing PCC activity, the meditator described being unable to elicit PCC activity by mind wandering: "I was trying to envision that I had a lot of work to do today . . . It didn't work" (**Figure 1A**). Another meditator when trying to activate her PCC reported: "I decided to picture wedding plans and so I started off thinking about my wedding and how I wanted to look good and then it just started to go blue. I switched to babies and I thought, 'I want babies' and I think that might correlate with a little red blip but then I couldn't sustain it . . . I'm wondering if I'm focusing so much that it's just going blue because I'm focusing but I can't get, I can't get the self to kick in when I'm told to" (**Figure 1B**). In another run, the same meditator reported: "I tried to think about what

was the thing that agitated me most and I thought it was [a certain person] and so I started thinking about her and I, at first it was just the name and I dropped into blue and so and then I started conjuring up images of [my boyfriend] with her and it super spiked [red] and then it just took a lot of effort so then I had to drop it. And I just kept trying to pick it up a little bit which I think correlates with the kind of like final two spikes, the kind of final two points in the red. Although, it was just so much energy, I couldn't sustain it, which was why I couldn't keep that really high spike going . . . I couldn't sustain it and so that kind of correlates with not being able to hold on to that throughout" (**Figure 1C**).

As highlighted by these examples, a common theme that emerged from this study was that getting caught up in experience (e.g., "hold on") rather than the content of experience itself increases PCC activity whereas present-centered awareness of mental content decreases PCC activity. Taken together, attention tasks when externally focused, studies of various types of meditation, and even a mindful stance toward an object (Taylor et al., 2011) suggest more precisely that PCC activity decreases when one becomes less caught up in ones experience, providing complementary evidence to studies showing its increase with tasks that elicit the opposite.

# **SUMMARY**

The PCC seems to be involved in a number of modes of experience – for example, it is activated with evident experiences of getting caught up such as craving, and more subtle experiences of getting caught up, such as identifying with or being attached to attributes of ourselves. This hypothesized role for the PCC is also supported by data showing that the PCC decreases in activity when we are not caught up in experience, whether being focused on a task or meditating. Though we have brought together data from many realms of cognitive neuroscience to support this hypothesis, we by no means offer it as a definitive explanation, but instead an invitation for exploration and dialog; still no studies to our knowledge exist that directly test a role for the PCC in getting caught up in experience.

Given the growing evidence for the interconnected network nature of the brain, the PCC likely serves as a sentinel marker or as a node within a network of brain regions that together support or represent getting caught up in experience, for example, as a sub-component process of the DMN, rather than functioning in isolation. Such markers are helpful for then identifying and characterizing the networks that they represent. Studies using direct intracranial EEG recording have already begun to provide complementary neurophysiological data linking DMN activity to gamma frequency ranges (Jerbi et al., 2010; Dastjerdi et al., 2011; Ossandon et al., 2011; Foster et al., 2012). These and other modalities such as neurophenomenological methods are needed to directly assess how the being caught up in experience relates to PCC activity, to confirm and/or refine this and other plausible hypotheses that link PCC activity to cognitive processes and ultimately behavior.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 24 June 2013; accepted: 17 September 2013; published online: 02 October 2013.*

*Citation: Brewer JA, Garrison KA and Whitfield-Gabrieli S (2013) What about the "self" is processed in the posterior cingulate cortex? Front. Hum. Neurosci. 7:647. doi: 10.3389/fnhum.2013.00647 This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Brewer, Garrison and Whitfield-Gabrieli. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# HUMAN NEUROSCIENCE

# Self-processing and the default mode network: interactions with the mirror neuron system

# **Istvan Molnar-Szakacs 1,2 and Lucina Q. Uddin3,4\***

<sup>1</sup> Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA

<sup>2</sup> Tennenbaum Center for the Biology of Creativity, University of California, Los Angeles, CA, USA

<sup>3</sup> Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA

<sup>4</sup> Department of Psychology, University of Miami, Coral Gables, FL, USA

#### **Edited by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada

#### **Reviewed by:**

Sören Krach, Philipps-University Marburg, Germany Alessandra Ghinato Mainieri, RWTH Aachen University, Germany

#### **\*Correspondence:**

Lucina Q. Uddin, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA 94305-5719, USA e-mail: lucina@stanford.edu

Recent evidence for the fractionation of the default mode network (DMN) into functionally distinguishable subdivisions with unique patterns of connectivity calls for a reconceptualization of the relationship between this network and self-referential processing. Advances in resting-state functional connectivity analyses are beginning to reveal increasingly complex patterns of organization within the key nodes of the DMN – medial prefrontal cortex and posterior cingulate cortex – as well as between these nodes and other brain systems. Here we review recent examinations of the relationships between the DMN and various aspects of self-relevant and social-cognitive processing in light of emerging evidence for heterogeneity within this network. Drawing from a rapidly evolving social-cognitive neuroscience literature, we propose that embodied simulation and mentalizing are processes which allow us to gain insight into another's physical and mental state by providing privileged access to our own physical and mental states. Embodiment implies that the same neural systems are engaged for self- and other-understanding through a simulation mechanism, while mentalizing refers to the use of high-level conceptual information to make inferences about the mental states of self and others. These mechanisms work together to provide a coherent representation of the self and by extension, of others. Nodes of the DMN selectively interact with brain systems for embodiment and mentalizing, including the mirror neuron system, to produce appropriate mappings in the service of social-cognitive demands.

**Keywords: functional connectivity, embodiment, mentalizing, autobiographical memory, medial prefrontal cortex, posterior cingulate cortex**

#### **INTRODUCTION**

## **DEFINING THE SELF AND BRAIN NETWORKS FOR SELF-RELATED PROCESSING**

The importance of self-knowledge has been asserted by philosophers, religious leaders, and thinkers cross-culturally. The Chinese philosopher Lao-Tzu claimed: "*He who knows others is wise; He who knows himself is enlightened*." The English cleric C. C. Colton wrote, "*He that knows himself knows others, [*. . .*]*," emphasizing the importance of self-knowledge for the sake of understanding others, as did Gandhi, who wrote, "*He who knows himself, knows God and all others*" (Gandhi, 1955). Throughout history, several examples exist of thinkers who have realized that representations of the self and others are intimately intertwined – that the self is a social stimulus. Current psychological theories suggest that the self may be considered a "special" stimulus, but also imply that it has similarities to other familiar and non-familiar stimuli that can be considered on a continuum of "familiarity" (e.g., kin recognition; Platek and Kemp, 2009) and "knowledge" (e.g., self-knowledge; Klein et al., 2002). For example, simulation theory proposes that in order to understand others we look inside ourselves to mentally simulate how we might act in given social situations (Gordon, 1986). Conversely, Gallotti and Frith (2013)

have recently suggested that in order to understand ourselves, we pay close attention to the social behavior of others.

One major and useful distinction that has guided research on the neural representation of the self is that between the physical and psychological aspects of the self (Gillihan and Farah, 2005). Physical aspects of the self are typically examined in studies of selfface recognition, body recognition, agency, and perspective taking. Psychological aspects of the self tend to be operationalized with studies examining autobiographical memory and self-knowledge or self-referential processing (SRP) of personality traits. This conceptual distinction bears out in neuroimaging work, which suggests that physical or embodied self-related processes and psychological or evaluative self-related processes rely on distinct yet interacting large-scale brain networks (Lieberman, 2007; Uddin et al., 2007; Molnar-Szakacs and Arzy, 2009; Molnar-Szakacs and Uddin, 2012). For the purposes of the current review, the principal neural networks we will consider are the default mode network (DMN) and the human mirror neuron system (MNS).

The repeated observation that the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), lateral parietal cortices, and medial temporal lobes paradoxically exhibit high levels of activity during resting baseline and decreases in activity during externally oriented cognitive tasks led to the initial characterization of these regions as belonging to a "default mode" of human brain function (Shulman et al., 1997; Gusnard and Raichle, 2001; Raichle et al., 2001; McKiernan et al., 2003; Fransson, 2006). This set of regions is more active when individuals rest than when they are engaged in goal-directed tasks. Importantly, these cortical regions tend to fluctuate in a coherent manner – a phenomenon termed functional connectivity – which further supports the notion that they constitute a network of functionally related processing areas (Greicius et al., 2003; Fox et al., 2005; Golland et al., 2008). This network has also been referred to as the "task-negative network" (Fox et al., 2005), or the "cortical midline structures" (Northoff et al., 2006), and was originally proposed as a system for evaluating "information broadly arising in the external and internal milieu" (Raichle et al., 2001). The DMN has been posited to underlie a variety of general functions such as stimulus-independent (Mason et al., 2007) or task-unrelated thought (McKiernan et al., 2006), as well as socialcognitive or self-related processes, including episodic memory (Greicius and Menon, 2004), memory consolidation (Miall and Robertson, 2006), social processing (Iacoboni et al., 2004; Uddin et al., 2005), and various forms of self-related processing (Gusnard et al., 2001; Wicker et al., 2003b; Buckner and Carroll, 2007). More specifically, the DMN's involvement is observed most consistently during the psychological task of reflecting on one's own personality and characteristics (SRP), rather than during physical self-recognition (Qin and Northoff, 2011).

The MNS was first identified in non-human primates. Mirror neurons are active when an agent performs an action, and when it observes that same action being performed, in essence, creating an agent-independent connection between actor and observer (Rizzolatti and Sinigaglia, 2010). Based on the property of mirror neurons to internally simulate actions performed by others, it has been proposed that the MNS may provide the link between the physical representation of the self as related to the physical representation of others (Uddin et al., 2005, 2006, 2007). That is, when we see *another's hand* grasping an object, we activate the regions of *our brain* that control grasping; when we hear sounds associated with *someone else's action*, we activate the appropriate movement regions of *our brain*; and by extension, when we observe the *emotional states of others*,*we can feel the same emotion* in empathy (Carr et al., 2003; Gazzola et al., 2006; Molnar-Szakacs et al., 2006). These mirror-like processes are influenced by the observer's perspective and the goal of the action itself, which appears to be even more important than the way in which an action is performed (Gazzola et al., 2007). The brain regions involved in creating these interpersonal links include the MNS and its associated regions – the inferior frontal gyrus (IFG)/premotor cortex (PMC), the anterior insula (AI), primary sensory and primary motor cortices, the inferior parietal lobule (IPL), and the superior temporal sulcus (STS).

The physical/psychological distinction, while perhaps simplistic, has facilitated the study of the neural networks underlying self-related processes. As the face is the most identifiable marker of the physical aspect of the self, it has been the subject of extensive study at the behavioral and neural levels. In particular, in our own work, we observed that the pattern of signal increases in the right IFG and right IPL were related to the amount of self-face presented in morphed stimuli (morphed with the face of a familiar other). In other words, the greater amount of "self" present in the stimulus, the greater the activation in right fronto-parietal regions (Uddin et al., 2005). These regions overlap the human MNS, whose role is to map the actions of others onto one's own motor repertoire via a simulation mechanism (Rizzolatti et al., 1996). Similar findings have since been published (Sugiura et al., 2005; Platek et al., 2006; Uddin et al., 2006), supporting the role of the human MNS in physical self-recognition.

Psychological aspects of the self, such as those accessed through personality traits, likely evoke a representation of the self predominantly through linguistic aspects of the self-schema (Faust et al., 2004; Molnar-Szakacs et al., 2005b; Moran et al., 2006). Selfschemata are cognitive representations of the self that are derived from past social interactions and experiences and promote the elaboration of memories that may be used to guide future behavior (Markus, 1977). In one of the first neuroimaging studies on the subject, Kelley and colleagues used a trait adjective judgment task to compare processing of self-, other-, and case-referential adjectives. Results showed that the MPFC was selectively engaged in the self-related condition, while relevance judgments (i.e., "Does this adjective describe you/U.S. President George Bush?"), when compared to case judgments (i.e., "Is this adjective in lowercase letters?"), were accompanied by activation of the left IFG and the anterior cingulate cortex (ACC) (Kelley et al., 2002). This initial finding has since been replicated (Moran et al., 2009; Feyers et al., 2010), underscoring the role of MPFC in self-processing (Moran et al., 2013). Additionally, two recent meta-analyses have parcellated MPFC into ventral and dorsal aspects (Denny et al., 2012; Wagner et al., 2012), showing that ventral MPFC (VMPFC) responds more to self, and dorsal MPFC (DMPFC) responds more to others. Earlier work showed a similar dissociation along the lines of mentalizing about similar others (engaging VMPFC) and metalizing about dissimilar others (engaging DMPFC) (Mitchell et al., 2006).

Self-reference and self-relevance – whether by visual self-face recognition or through the enhanced memory for trait adjectives – invoke autobiographical memory processes (Molnar-Szakacs and Arzy, 2009). Memory is vital to the survival of the self, as we use our memory for past events to predict the future and update action plans in a flexible, goal-oriented manner (for reviews, see Schacter et al., 2007, 2008). Recently, neuroimaging studies have started to investigate the neural networks subserving self-projection in time (Addis et al., 2007; Buckner and Carroll, 2007; Szpunar et al., 2007; Arzy et al., 2008). Arzy and colleagues used a paradigm that involved participants making mental self-projections to both past and future events, and found an effect of self, whereby participants responded significantly faster to self-relevant (personal) events than to non-self-relevant (world) events. Self-location in time was shown to recruit a distributed neural network – including anterior temporal, occipito-temporal, and temporo-parietal regions – that partly overlaps the DMN (Arzy et al., 2008). These brain regions were also recruited in studies of visuo-spatial perspective taking and spatial self-location (Vogeley and Fink, 2003; Blanke et al., 2005; Arzy et al., 2006). In one of the first descriptions of the DMN,Raichle et al. (2001) proposed a domain-general

role for the PCC in providing complex visual representations to consciousness.

Taking into consideration the many facets of self-relevant processing such as self-face recognition, personality trait judgments, and autobiographical memory, it is not surprising that these processes recruit a vast network of brain regions. These include the human MNS for physical aspects of self-relevant processing, as well as the MPFC node of the DMN during SRP and the PCC/precuneus node of the DMN for self-location in time and space. In order to bridge the gaps between these neural and psychological levels of analysis, we need to correlate cognitive and affective experiences of self with the underlying neural processes supporting them. Inspired by current and historical psychological theories (Gordon, 1986; Gallotti and Frith, 2013) and extending upon our previous work (Molnar-Szakacs et al., 2005b; Uddin et al., 2005, 2006; Molnar-Szakacs and Uddin, 2012), we propose that many of the same neural systems are engaged for self- and other-understanding. Thus, having privileged access to our own physical and mental states allows us to gain insight into others' physical and mental states through the processes of embodiment and mentalizing. These cognitive processes are supported at the neural level by two large-scale, interacting networks – the MNS and the DMN, respectively. A more in-depth understanding of the functionally relevant nodes of each network, and the interactions between them, will help us advance toward a more complete theory of self-representation. By bringing together recent work on the fractionation of these complex networks, we aim to contribute to a more complete understanding of the self.

#### **NEURAL PROCESSES GIVING RISE TO THE SELF**

Preston and de Waal (2002) formalized a theory of emotionalmotor resonance in the Perception–Action Model, which holds that perception of a behavior performed by another automatically activates one's own representations for the behavior, and output from this shared representation automatically proceeds to motor areas of the brain where responses are prepared and executed. Emotional-motor resonance may also be called emotional empathy or embodied simulation – processes related to the same bottom-up, automatic, and evolutionarily early mechanism. Embodied simulation implies transforming perceived actions and emotions into our own inner representations of those actions and emotions. This process, supported by interactions between the MNS and the limbic system, is fast, automatic, and precognitive, and is thought to support our ability to empathize emotionally ("I feel what you feel") (Preston and de Waal, 2002). Current evolutionary evidence suggests that embodied simulation is a phylogenetically early system for empathy, and that there is also a more advanced cognitive perspective-taking (or theory of mind, ToM/mentalizing) system mediating empathic responses in humans (de Waal, 2008).

Higher-level cognitive empathy requires that we actively think about, or reflect on others' actions and emotional states, including perspective taking or ToM/mentalizing (de Waal, 2008). Mentalizing refers to the process of understanding another person's perspective, and appears to depend upon higher cognitive functions such as cognitive flexibility (Decety and Jackson, 2004). Singer (2006) has proposed that mentalizing allows us to *understand* mental states such as intentions, goals, and beliefs, while embodied simulation allows us to *share* the feelings of others. Low-level embodied processes and higher-level mentalizing processes integrate their signals such that stimuli are "mapped" onto internal representations and combined with information from memory to plan future behavior, select a response, and act. Neuroimaging studies have implicated distinct neural networks subserving embodiment and mentalizing processes (Shamay-Tsoory et al., 2004; Singer, 2006; Vollm et al., 2006; Hooker et al., 2008). Mentalizing processes appear to be centered on the MPFC node of the DMN, while embodied simulation processes are implemented by the MNS – limbic system network (Preston and de Waal, 2002; Gallese, 2005; Iacoboni and Dapretto, 2006; Iacoboni, 2009).

As previously discussed, the human MNS supports a simulation-based, motor resonance mechanism, whereby we understand the actions and emotions of others by "embodying" them ourselves. It has been suggested that mirror neurons are a kind of "neural wi-fi" that monitors what is happening in others. This system tracks others' emotions, what movements they're making, and what they intend, and activates in our brains precisely the same areas that are active in theirs. This puts us on the same wavelength and it does so "automatically, instantaneously and unconsciously" (Goleman, 2006). Neuroimaging studies have provided evidence in support of this notion, showing common neural signatures while experiencing disgust (Wicker et al., 2003a), touch (Keysers et al., 2004), or pain (Singer et al., 2004; Jackson et al., 2006) in oneself, and when perceiving the same feelings in others. Between-brain analyses have also provided evidence for neural resonance between individuals during social interactions (Schippers et al., 2010).

In thinking about the self and others, mentalizing representations (Barsalou, 1999, 2008) and embodied representations (Goldman and de Vignemont, 2009) serve as the foundations for making inferences about our own mind as well as others' minds. Recent work has suggested that higher-level inference-based mentalizing processes are grounded in their interactions with lowerlevel embodied simulation-based processes (Barsalou, 1999, 2008; Goldman, 2006; Keysers and Gazzola, 2007; Goldman and de Vignemont, 2009). This predicts that brain regions involved in high-level inference-based mentalizing are integrating their signals with lower-level simulation-based systems (Keysers and Gazzola, 2007; Uddin et al., 2007), implying DMN–MNS interactions during self-relevant processing (Sandrone, 2013). In a recent study, Schippers and Keysers have shown using Granger causal analyses that rather than simply being a feed-forward system in which visual representations are transformed into motor programs through a temporal→parietal→premotor flow of information, the MNS acts as a dynamic feedback control system, and that during gestural communication there is information flow within the system from premotor to parietal and temporal cortices (Schippers and Keysers, 2011). Their findings lend strong support to the notion of dynamic interactions between the MNS and the DMN.

Here we expand on recent theories linking embodiment and mentalizing systems (Keysers and Gazzola, 2007;Uddin et al., 2007; Molnar-Szakacs and Arzy, 2009; Paulus et al., 2013; Sandrone, 2013), and propose that the MNS and the DMN are functionally connected and dynamically interact during social-cognitive

processing. Simulation-based representations serve to scaffold conceptual representations that allow us to understand the self in its social context. By virtue of their differential patterns of connectivity, subdivisions of the DMN can interact with the appropriate brain systems, including the MNS, in the service of self-related and social-cognitive demands. In light of recent work fractionating the DMN (Uddin et al., 2009; Andrews-Hanna et al., 2010), we will discuss some examples of how these low- and high-level mechanisms critical for representing the self are subserved by dissociable subdivisions of this network. In addition, we will highlight brain regions that may serve as key hubs mediating interactions between the DMN and MNS.

#### **DIFFERENT ASPECTS OF SELF-RELATED PROCESSING SELF-RELATED PROCESSING IN THE PHYSICAL DOMAIN**

One of the most important ways to identify one's own person is to recognize one's face and distinguish it from other persons' faces. Among the first to study the neural correlates of self-recognition in neurotypical adults, Keenan and colleagues provided behavioral (Keenan et al., 2000) and neural (Keenan et al., 2001) evidence for a right hemisphere bias in self-face processing. Subsequent functional Magnetic Resonance Imaging (fMRI) studies of self-face recognition described activations in lateral prefrontal cortex and parietal cortices during self-face recognition (Kircher et al., 2001; Platek et al., 2004, 2006; Sugiura et al., 2005). A recent review has highlighted the common finding of right frontal and parietal activations accompanying self-face viewing, especially when compared to other familiar faces (Devue and Bredart, 2011). Furthermore, a meta-analysis of studies of self-face recognition found that in addition to right fronto-parietal regions which overlap the human MNS, the right precuneus is a region that is also associated with this task (Platek et al., 2008). In our own work (Uddin et al., 2005), we provide clear evidence for a right hemisphere network including the IFG, IPL, superior parietal lobule, and inferior occipital gyrus activated by recognition of the self-face. The pattern of signal increases we observed in these areas as the stimuli contain more "self" suggest that these areas comprise a unique system extending beyond mere recognition of faces and play a particular role in self-face recognition. Perception of the self-face appears to involve a simulation-like mechanism that recruits right hemisphere MNS matching the face stimulus to an internal representation of the self. We proposed earlier that mirror areas may be more active for stimuli containing more "self" because their role is to establish communication between individuals via a simulation mechanism that maps actions of others onto one's own motor repertoire, thereby making others "like me" (Meltzoff and Brooks, 2001). Thus, when one sees one's own image, these mirror areas are more strongly activated because of the ease with which one can map oneself onto one's own motor system (Uddin et al., 2005). Interestingly, we also observed similar brain activation patterns distinguishing the self-voice from other voices, suggesting that the right hemisphere MNS may contribute to multimodal abstract self-representation (Kaplan et al., 2008).

Our results also demonstrated decreased activity within the DMN (precuneus, MPFC, and posterior superior temporal gyrus) only during processing of "self" stimuli (Uddin et al., 2005). This pattern of results led us to propose that the"familiar other" stimuli

triggered social representations, and thus the task-related deactivation was compensated during viewing of the"other" by an increase in activity due to social processing. Thus, the overall result is lack of deactivation for"other,"not a true activation. It is possible that during viewing of the "familiar other," with whom the subjects have a positive social relationship, the subjects automatically activate social representations to a greater extent than when viewing the "self." In summary, the generalized signal decrease in these DMN areas due to the task demands is offset in the "other" condition by triggering social-cognitive processing, which previously has been shown to engage these regions (Iacoboni et al., 2004). Thus, recognition of familiar others seems to also recruit midline structures that have previously been implicated in social processing (Saxe, 2006). Taken together, these results emphasize the importance of dynamic interactions between the MNS and the DMN during the processing of self-relevant information. The MNS appears to play an important role in physical self-recognition, while the DMN participates in situating the self in its social context relative to familiar others.

#### **SELF-REFERENTIAL PROCESSING IN THE VERBAL DOMAIN**

The self-reference effect (Symons and Johnson, 1997) is a unique encoding phenomenon, whereby memory for previously presented trait adjectives (e.g., happy) is better if they had been processed with reference to the self (e.g., "does happy describe you?") than if they had been processed only for their general meaning (e.g., "does happy mean the same as optimistic?"). In other words, as traits are incorporated into the self-schema, subsequent memory for these trait words is increased (Rogers et al., 1977). Several studies have used the self-reference effect to investigate SRP in the verbal domain. Using statements delivered through the auditory domain, Johnson and colleagues compared judgments about one's own abilities, traits, and attitudes (such as "I can be trusted") to a semantic judgment task. The self-referential condition was associated with activation in the MPFC and the PCC relative to the control condition (Johnson et al., 2002). Using a slightly different paradigm, Kjaer and colleagues asked participants to mentally induce thoughts reflecting on one's own personality traits and physical appearance. Once again, self-referential conditions induced activation in midline DMN regions including the MPFC and precuneus when compared to the non-self-referential conditions (Kjaer et al., 2002). They also observed increased functional connectivity between frontal and parietal midline regions during self-referential conditions. As evidenced by these studies, SRP in the verbal domain appears to recruit midline components of the DMN.

To tease apart the role of different subdivisions of the DMN in verbal SRP, Lou and colleagues used a combined PET-TMS approach. In the PET study, they used visually presented personality trait adjectives that were either related to the self, to the participants' best friend, or to the Danish Queen (Lou et al., 2004). Retrieval of self-related adjectives induced activation in the DMPFC, the PCC/precuneus, the right and left IPL, the left ventrolateral prefrontal cortex, and the middle temporal cortex including the hippocampus. As in previous studies, analysis of functional connectivity revealed significant interaction between anterior (DMPFC) and posterior (PCC, precuneus) midline regions

of the DMN. Transcranial magnetic stimulation over the medial parietal region caused a decrease in the efficiency of retrieval of previous judgments of the mental self as compared to retrieval of judgments of others, confirming that this region may be a nodal structure in self-representation, mediating interactions between the DMN and other lateral cortical regions (Lou et al., 2004).

#### **SELF-REFERENTIAL PROCESSING IN THE MEMORY DOMAIN**

Self-referential processing in memory depends on the individual's life history and involves the recollection of past experiences, as the retrieved episodic information is unique to an individual and is tied to a specific personal context (Ingvar, 1985; Craik et al., 1999). Episodic memory retrieval (EMR), on the other hand, also includes the retrieval of events that are characterized by low selfrelevance. Behaviorally, the link between SRP and EMR is reflected in the so-called self-reference effect of memory, as discussed above (Rogers et al., 1977; Symons and Johnson, 1997). Further support for this link comes from neuroimaging investigations. EMR studies report activations in brain regions that are also identified by SRP tasks, including the MPFC, as well as the medial and lateral parietal cortex (Donaldson et al., 2001) (for reviews, see Cavanna and Trimble, 2006; Legrand and Ruby, 2009). Because these brain areas also show high neural activity during resting states, both SRP and EMR have been considered possible functions of the DMN (Buckner et al., 2008).

In a study designed to explore the similarity and dissociability of SRP and EMR, Sajonz and colleagues found that self-referential stimuli specifically activate the PCC/anterior precuneus, the MPFC, and an inferior division of the IPL. In contrast, EMR success specifically involves the posterior precuneus, the anterior prefrontal cortex, and a superior division of the IPL extending into the intraparietal sulcus and the superior parietal lobule. Overlapping activations can be found in intermediate zones in the precuneus and the IPL but not in the prefrontal cortex (Sajonz et al., 2010). These findings clearly demonstrate that distinct subdivisions of the DMN are recruited during SRP as compared with more general EMR. This is of particular interest in light of earlier studies associating the MPFC with autobiographical memory retrieval (Gilboa, 2004; Svoboda et al., 2006), retrieval of self-referential episodes (Zysset et al., 2002), retrieval of selfgenerated versus externally presented words (Vinogradov et al., 2008), and the self-reference effect of memory (Macrae et al., 2004). These processes have in common that they involve selfreferential and memory components at the same time. The data of Sajonz and colleagues seem to suggest that the self-referential component particularly contributes to activations of the medial prefrontal node of the DMN observed in these studies.

A functional connectivity analysis performed on the data suggests a functional segregation within the PCC/precuneus for SRP and EMR, respectively. Activity in the SRP-related seed in the PCC/anterior precuneus correlated with the MPFC, dorsal ACC, fusiform gyrus, and superior parietal lobule during SRP. In contrast, activity in the EMR-related seed in the posterior precuneus was associated with the responsiveness in a distinct region in the dorsal anterior paracingulate cortex during EMR (Sajonz et al., 2010). Taken together, these findings shed light on the parcellation of nodes within the DMN, and suggest that there is a functional

segregation within the precuneus during SRP and EMR. Activity in anterior precuneus appears to be associated with SRP, a more self-directed process, whereas activity in posterior precuneus is associated with EMR, a more social and outward-directed process. This anterior/posterior functional parcellation within the precuneus mirrors the dorsal/ventral subdivision of the MPFC, as discussed above.

# **NEURAL NETWORKS, FUNCTIONAL CONNECTIVITY, AND THE SELF**

#### **FINDINGS FROM RESTING-STATE fMRI**

The past several years have witnessed a resurgence in the use of fMRI to study not only regional activation patterns in response to specific stimuli, but also functional connectivity between-brain regions both during task performance and during resting states. This focus on brain connectivity has emerged as a natural consequence of recent advances in methods for acquiring and analyzing resting-state fMRI data, as well as efforts such as the Human Connectome project (http://www. humanconnectomeproject.org/). Functional connectivity measured from fMRI data is defined as"temporal correlations between remote neurophysiological events" (Friston, 1994), and is typically quantified by conducting correlation analyses between regional timeseries (Cole et al., 2010). Since the initial demonstration that coherent low-frequency fluctuations in blood-oxygen-leveldependent (BOLD) signal index functionally significant brain systems (Biswal et al., 1995), the use of resting-state fMRI to characterize brain functional organization has sky-rocketed. This approach has been used to understand how the DMN might be further divided into functional subsystems.

It is often difficult to ascertain the functional roles of brain regions from their selective activation during processing of specific stimuli or associated with specific cognitive demands. Restingstate connectivity approaches, unconfounded by ceiling and floor effects in task performance, can provide complementary information regarding the functional roles of brain regions. It has been known since the initial study by Greicius et al. (2003) that brain areas comprising the DMN (PCC, MPFC, lateral parietal cortices), show coherent low-frequency fluctuations. Several recent studies examining the resting-state or intrinsic functional connectivity of the DMN have provided evidence for considerable heterogeneity between distinct nodes of the network. For example, the PCC has been shown to have stronger negative correlations with anterior cingulate and insular cortices, whereas the MPFC shows stronger negative correlations with posterior parietal cortices (Uddin et al., 2009). Several previous studies have demonstrated default mode suppression during goal-oriented task performance, with failure to suppress default mode activity being linked to decreased activity in task-relevant regions and attentional lapses, or decrements in performance (Weissman et al., 2006). Heterogeneity of DMN nodes in terms of their functional connectivity suggests that different avenues may exist for communicating with other brain systems critical for self-related processing.

While the MPFC and PCC are considered core "hubs" of the DMN, some have suggested that the network can be fractionated into subcomponents. Recently, Salomon et al. (2013) have proposed that the inferior and posterior parietal aspects of the DMN can be further subdivided such that some show greater involvement in self-referential judgments than others. Andrews-Hannah and colleagues found that one subsystem including DMPFC, temporo-parietal junction (TPJ), lateral temporal cortex, and temporal pole, is more engaged when individuals make self-referential judgments about their present situation or mental states, whereas a different subsystem comprised of VMPFC, medial temporal lobes, IPL, and retrosplenial cortex is more active during episodic judgments about the personal future (Andrews-Hanna et al., 2010). Others have subdivided the PCC into ventral and dorsal subdivisions. Leech et al. (2011) found that as difficulty increases during an N-back task, ventral PCC shows reduced integration within the DMN, whereas dorsal PCC shows increased integration with the DMN as well as attention networks. Taken together, these studies suggest that the concept of the DMN as a homogenous network should be refined and updated to account for heterogeneous patterns of activation and connectivity observed within the regions comprising it. This reconceptualization of the DMN as consisting of multiple interacting subsystems has clear implications for theories of the network's role in self-related cognition. In particular, the identification of possible"nodes of association"creating functional links enabling communication between the DMN and MNS are now beginning to be revealed. It has recently been demonstrated that certain brain regions constitute a "rich club" of organization in that they are highly connected hubs that are connected to other highly connected hubs (van den Heuvel and Sporns, 2011). We propose that such highly connected brain regions, including the PCC/precuneus and AI, may play a role in orchestrating dynamic interactions between the DMN and MNS.

#### **FUNCTIONS AND FUNCTIONAL CONNECTIVITY OF DMN NODES**

Although the precise functional properties of the DMN are not yet established, a growing number of studies implicate this network in various aspects of self-related processing. For example, the DMN is implicated during self-related evaluations (Northoff et al., 2006; Buckner and Carroll, 2007) voluntary actions (Goldberg et al., 2008), episodic memory (Spreng et al., 2009; Sestieri et al., 2011), and planning. Previous studies have revealed functional subdivisions within the DMN (Uddin et al., 2009; Andrews-Hanna et al., 2010; Sestieri et al., 2011) using either data driven parcellation methods (e.g., ICA, graph-analysis), or using specific tasks such as EMR. Within-region functional subdivisions in the DMN are also starting to be described as related to various neural processes including SRP and EMR (Andrews-Hanna et al., 2010; Sajonz et al., 2010; Kim, 2012) and cognitive control (Leech et al., 2011). In the following sections, we will describe some relevant studies that used a connectivity approach to explore DMN function and connectivity with the MNS and other brain regions during self-relevant processing.

Due to the overlap between brain regions involved in selfprocessing and regions that constitute the DMN (D'Argembeau et al., 2005; Schneider et al., 2008), some speak of a so-called "default self," arguing that the self may be more or less identical with the resting-state activity observed in DMN regions (Gusnard et al., 2001;Wicker et al., 2003b;Beer, 2007). A recent meta-analysis of 87 self-related studies has lent further support to this idea (Qin and Northoff, 2011). In their meta-analysis, Qin and Northoff asked a two-part question – is neural activity in the DMN selfspecific, and is self-specific activity related to resting-state activity? The specificity of the self (e.g., hearing one's own name, seeing one's own face) in the DMN was tested and compared across familiar (using stimuli from personally known people) and other (strangers and widely known figures) conditions. A large MPFC regions was recruited for the self condition when compared to the familiarity and other conditions. Concerning other midline regions, there was either regional overlap of activations between the self and familiarity conditions in the MPFC, or between the familiarity and other condition in the PCC (Qin and Northoff, 2011). This finding is in accordance with previous studies finding both self-specific and non-specific regions within the DMN during self-relevant processing (Gusnard et al., 2001; D'Argembeau et al., 2005; Schneider et al., 2008).

An interesting finding to emerge from the meta-analysis by Qin and Northoff (2011) was the recruitment of the right IFG, as well as the left AI during self-specific conditions. The role of the IFG as one of the anchors of the MNS and its role in self-relevant processing are well established (Molnar-Szakacs et al., 2005a; Uddin et al., 2005). As we have previously discussed, the right IFG seems to be responsive to self-face stimuli as well as one's own voice (Uddin et al., 2005; Kaplan et al., 2008). The insula has also been associated with self-specific stimuli in recent studies (Enzi et al., 2009; Modinos et al., 2009), and forms an integral part of the neural network important for emotional empathy, embodiment, and simulation (Carr et al., 2003; Singer et al., 2004). As the insula is heavily involved in interoceptive stimulus processing (Craig, 2003), one may suggest that the co-activation between insula and the DMN may be crucial in constituting the self and assigning self-specificity to stimuli. It has recently been demonstrated that the right AI plays a causal role in switching between the DMN and executive control networks (Sridharan et al., 2008). It has been suggested that the AI serves to detect events that are salient to the individual and mobilize neural resources in the service of appropriate behavioral responses (Menon and Uddin, 2010). That self-related stimuli should invoke activation of the insula is not surprising in light of these findings. Pre-reflective representations of visceral states of the self, for instance, seem linked to activations in the posterior and/or middle insula. By contrast, midline structures become active when subjects are asked to introspect, reflect, and report these states (e.g., heartbeat) (Critchley and Harrison, 2013). The AI seems crucial in linking the more posterior insula with these midline structures. Thus, interactions between the DMN and the MNS through the functional connectivity of midline structures and the AI could mediate the ability to represent one's bodily states to enable conscious reflection on those states (Keysers and Gazzola, 2007).

#### **INTERACTIONS BETWEEN THE DMN AND MNS**

The integration of function between the DMN and the MNS have been the focus of several recent proposals on the neural bases of self-related cognition (Keysers and Gazzola, 2007; Uddin et al., 2007; Molnar-Szakacs and Arzy, 2009; Molnar-Szakacs and Uddin, 2012; Paulus et al., 2013; Sandrone, 2013). The results of Qin and Northoff (2011) also lend support to the notion that the self emerges from the interaction of these two neural networks. Their

meta-analysis showed recruitment of DMN regions, including the MPFC and PCC, as well as MNS regions, including the IFG and AI, both during self-relevant processing.

Lombardo et al. (2010) used a functional connectivity approach to investigate the nature of the interaction between high-level mentalizing systems and embodied simulation-based representations during mentalizing and physical judgments about the self and others. The areas of overlap of activation between self and other consisted of the MPFC, PCC, and bilateral TPJ as well as the left anterior temporal lobe along the middle temporal gyrus, left primary sensorimotor cortex, and cerebellum. With a factorial design, they were able to test the interaction effect of whether mentalizing or physical representations recruit distinct functional circuits for the self or other. Similar patterns of functional connectivity between self and other conditions suggested that mentalizing representations are distributed across similar neural systems with respect to self and other. Conjunction analyses revealed a self–other distinction within the neural circuitry for mentalizing whereby the MPFC was biased for SRP, and the PCC and the TPJ were biased for other-referential processing, as has previously been shown (Ruby and Decety, 2001; Saxe et al., 2006; Pfeifer et al., 2007). As opposed to the previous within-region functional subdivisions we have discussed for the dorsal/ventral MPFC or the anterior/posterior precuneus, self–other distinction in this study mapped onto fronto-parietal DMN regions. Taken together, the results of these studies show that in addition to broad cross-regional functional specializations, region-specific functional specializations exist within nodes of the DMN.

A particularly interesting result of the study was that several MNS regions, including IFG/PMC, primary somatosensory cortex, and the AI were sensitive to processing of both self and other. The role of somatosensory cortex in low-level shared representations of touch (Keysers et al., 2004; Blakemore et al., 2005), self-experienced pain (Singer et al., 2004), and action–perception mirroring (Gazzola et al., 2006; Nanetti et al., 2009) is well established. Thus, the observation that primary somatosensory cortex is also recruited for mentalizing about self and other suggests that low-level embodied simulative representations computed by this region are also important for the processes underlying higher-level inference-based mentalizing when compared with reflecting on physical characteristics (Lombardo et al., 2010). In fact, connectivity analyses revealed that these two systems were specifically linked during mentalizing more than during physical judgments, and this pattern of connectivity was apparent for both self and other conditions. Taken together, these results provide strong evidence of the integration of function between the DMN and the MNS. The authors conclude that "the tight link between high-level inference-based mentalizing systems and lowlevel embodied/simulation-based systems suggests that these two neural systems for social cognition are integrated in a task-specific manner for mentalizing about both self and other" (Lombardo et al., 2010).

The studies reviewed here suggest that interactions between the DMN and MNS during self-relevant processing may occur through several associated brain regions. **Figure 1** depicts some of the possible neuroanatomical loci and functional connections underlying such interactions.

# **CONCLUSION**

Historically, scholars have pitted high-level inference-based mentalizing accounts and low-level embodied simulation-based accounts as opposites of each other (Gopnik and Wellman, 1992; Gordon, 1992). However, recent theories related to different aspects of self-representation have been focused on the possible integration of function between the DMN and the MNS (Keysers and Gazzola, 2007; Uddin et al., 2007; Molnar-Szakacs and Arzy, 2009; Molnar-Szakacs and Uddin, 2012; Paulus et al., 2013; Sandrone, 2013). Furthermore, interpretations of disturbances in self-relevant processing often invoke explanations that are based either in deficits of the DMN, the human MNS, or both. For example, theories of how we understand other minds have implicated both the DMN (Spreng and Grady, 2009) and the MNS (Gallese and Goldman, 1998); theories about moral cognition have been linked to both the DMN (Harrison et al., 2008) and the MNS (Molnar-Szakacs, 2011); and both the DMN and the MNS have been implicated in theories of physical self-representation (Uddin et al., 2007; Molnar-Szakacs and Arzy, 2009; Molnar-Szakacs and Uddin, 2012). In the realm of psychiatric or neurological disorders, both the DMN (Cherkassky et al., 2006; Uddin, 2011) and the MNS (Iacoboni and Dapretto, 2006; Molnar-Szakacs et al., 2009; Enticott et al., 2012) have been implicated in autism spectrum disorders and aberrant DMN connectivity and MNS dysfunction have been observed in schizophrenia (Garrity et al., 2007; Mehta et al., 2012). Taken together, this evidence from both the healthy and the atypical brain suggests that the human MNS and the DMN are functionally connected and are together profoundly implicated in social cognition that forms the basis of understanding the self. In the context of situations requiring understanding of others' mental and physical states, such interactions facilitate the self–other mappings at the core of both embodiment and mentalizing processes.

Findings of functional specialization within the DMN are beginning to shed light on the ability of the network to support self-related processes as seemingly unrelated as autobiographical memory and verbal SRP. The findings reviewed here argue against viewing the DMN as a unitary system, and are compatible with the notion that the network consists of distinct, functionally specialized subsystems. It is becoming increasingly clear that great attention to anatomy can reveal subtle differences in circuitry of neighboring cortical regions of the DMN (Margulies et al., 2009). For example, we have seen that broad cross-regional functional specializations exist across regions of the DMN, such that the frontal MPFC node is more involved in self-related processing and the posterior PCC node is more involved in other-related processing. Additionally, region-specific functional specializations exist within nodes of the DMN, such that the VMPFC responds more

#### **REFERENCES**


to self and the DMPFC responds more to others. Furthermore, emerging findings from the functional connectivity literature can greatly inform theories of DMN involvement in self-related cognition. In particular, they highlight possible avenues for interactions between the DMN and MNS, and indicate how brain networks for mentalizing and embodiment might communicate. Indeed, the studies discussed above suggest that the DMN and MNS may interact at certain "rich-club" nodes, including the AI and the PCC. Through this interaction, embodied simulation-based representations serve to scaffold mentalizing-based representations. These representations allow the brain to construct a dynamic self, continuous through time, and able to plan for the future. A more in-depth understanding of the functionally relevant nodes of each network, and the interactions between them, will help us advance toward a more complete theory of self-representation in the brain.

#### **ACKNOWLEDGMENTS**

This work was supported by a National Institute of Mental Health Career Development Award (K01MH092288) to Lucina Q. Uddin. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIMH or the NIH.


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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 24 May 2013; accepted: 26 August 2013; published online: 11 September 2013.*

*Citation: Molnar-Szakacs I and Uddin LQ (2013) Self-processing and the default mode network: interactions with the mirror neuron system. Front. Hum. Neurosci. 7:571. doi: 10.3389/fnhum.2013.00571*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Molnar-Szakacs and Uddin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Three ways in which midline regions contribute to self-evaluation

# **Taru Flagan and Jennifer S. Beer \***

Department of Psychology, University of Texas at Austin, Austin, TX, USA

#### **Edited by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada

#### **Reviewed by:**

Arnaud D'Argembeau, University of Liege, Belgium Pawel Tacikowski, Karolinska Institute, Sweden

#### **\*Correspondence:**

Jennifer S. Beer, Department of Psychology, The University of Texas at Austin, 108 E. Dean Keeton Stop A8000, Austin, TX 78712-1043, USA e-mail: beer@mail.utexas.edu

An integration of existing research and newly conducted psychophysiological interaction (PPI) connectivity analyses suggest a new framework for understanding the contribution of midline regions to social cognition. Recent meta-analyses suggest that there are no midline regions that are exclusively associated with self-processing. Whereas medial prefrontal cortex (MPFC) is broadly modulated by self-processing, subdivisions within MPFC are differentially modulated by the evaluation of close others (ventral MPFC: BA 10/32) and the evaluation of other social targets (dorsal MPFC: BA 9/32). The role of DMPFC in social cognition may also be less uniquely social than previously thought; it may be better characterized as a region that indexes certainty about evaluation rather than previously considered social mechanisms (i.e., correction of self-projection). VMPFC, a region often described as an important mediator of socioemotional significance, may instead perform a more cognitive role by reflecting the type of information brought to bear on evaluations of people we know well. Furthermore, the new framework moves beyond MPFC and hypothesizes that two other midline regions, ventral anterior cingulate cortex (VACC: BA 25) and medial orbitofrontal cortex (MOFC: BA 11), aid motivational influences on social cognition. Despite the central role of motivation in psychological models of self-perception, neural models have largely ignored the topic. Positive connectivity between VACC and MOFC may mediate bottom-up sensitivity to information based on its potential for helping us evaluate ourselves or others the way we want. As connectivity becomes more positive with striatum and less positive with middle frontal gyrus (BA 9/44), MOFC mediates topdown motivational influences by adjusting the standards we bring to bear on evaluations of ourselves and other people.

**Keywords: self, optimistic bias, social cognition, frontal lobe, self-projection, motivation, person perception**

# **INTRODUCTION**

The speculation that some midline regions contribute to selfprocessing stems from research conducted over a decade ago (Beer et al., 2006b). What have we learned since those initial studies found that medial prefrontal cortex (MPFC) is modulated by encoding and remembering information in relation to the self (e.g., Kelley et al., 2002; Macrae et al., 2004; Ochsner et al., 2005)? This article draws on existing research and newly conducted psychophysiological interaction (PPI) analyses to describe a new framework for the contribution of how a subportion of midline regions to social cognition (see **Figure 1**). The new framework builds on previous discussions by (a) positing a new role for the MPFC in social cognition and (b) moving past the MPFC to consider the importance of ventral anterior cingulate (VACC: BA 25) and medial orbitofrontal cortex (MOFC: BA 11) in aiding motivational influences on social cognition. Recent meta-analyses suggests that there are no midline regions that are exclusively associated with self-processing. For example, meta-analyses of studies of social evaluation (i.e., traits, personal abilities, etc.) find that the MPFC likely mediates psychological processes that are brought to bear on self-evaluation but also evaluations of other kinds of people (e.g., close others vs. non-close-others:Ochsner et al.,2005;Qin

and Northoff, 2011; Murray et al., 2012; Roy et al., 2012). Whereas it was once thought that regions within VMPFC (BA 10/32) and DMPFC (BA 9/32) mediated person evaluation through the correction of self-projection, there are a number of issues that must be addressed before strong conclusions can be drawn. For example, current research provides more consistent evidence for the role DMPFC in certainty about self-evaluation even during tasks that require evaluations of other people. Furthermore, recent research suggests that VACC and MOFC are just as importantly involved in social cognition as the MPFC. Neural models of social cognition have not incorporated motivated processing which is a fundamental element of psychological models of the self (Beer, 2007). A growing body of research suggests that motivational influences on self- and other-evaluation are mediated by VACC and MOFC. VACC may mediate bottom-up sensitivity to information based on its potential for helping us evaluate ourselves or others the way we want (Beer, 2012a). MOFC may mediate top-down motivational influences on self-evaluation. Taken together, the new framework highlights the progress that has been made over the past decade: MPFC is involved in social cognition but does not mediate "selfspecific" processes and two additional regions, VACC and MOFC, play an important role in motivated self- and other-evaluation.

**FIGURE 1 | A framework of cortical midline structures implicated in self-evaluation**. DMPFC, dorsomedial prefrontal cortex (BA 9, 32); VMPFC, ventromedial prefrontal cortex (BA 10, 32); VACC, ventral anterior cingulate cortex (BA 25); MOFC, medial orbitofrontal cortex (BA 11, 12).

# **A NEW CONCEPTUALIZATION OF THE ROLE OF MPFC IN SOCIAL COGNITION: CERTAINTY IN EVALUATION?**

While much has been learned about the role of MPFC in social cognition in the past decade,much more remains to be known.A series of studies in the early 2000s found that MPFC (BA 9/10/32) was modulated by both self-evaluation and evaluations of a political figure but modulation was greatest for self-evaluation (e.g., Kelley et al., 2002; Macrae et al., 2004; Ochsner et al., 2005). This research sparked interest in testing the possibility that functional MPFC subdivisions distinguished self-processing from the evaluation of other people. In contrast to this possibility, recent meta-analyses have shown that MPFC (BA 9/10/32) modulation is not exclusive to self; this region is modulated by both self-processing and processing about other people (Ochsner et al.,2005;Qin and Northoff, 2011;Murray et al., 2012;Roy et al., 2012). Instead of a self vs. other distinction,meta-analyses suggest a close other vs. non-close-other distinction. A ventral subdivision of this MPFC region (BA: 10/32, see **Figure 1**) is associated with self-processing and evaluations of close others (Ochsner et al., 2005; Qin and Northoff, 2011; Murray et al., 2012). A more dorsal subdivision (BA 9/32, see **Figure 1**) is associated with self-processing and evaluations of non-close-others (Ochsner et al., 2005; Qin and Northoff, 2011; Murray et al.,2012). Therefore, the next step toward understanding the contribution of MPFC to social cognition should be focused on understanding the psychological significance of MPFC's broad association with self-processing in combination with the ventral to dorsal differentiation of processing about other people.

## **DMPFC: CORRECTING SELF-PROJECTION OR CERTAINTY IN (SOCIAL) JUDGMENT?**

The correction of self-projection was one of the first psychological processes hypothesized to explain DMPFC's association with both self-processing and processing of non-close-others. Psychological models suggest that one way we evaluate a new person is through the correction of self-projection, that is, by drawing on self-representation to the extent it is perceived as applicable to the new person (i.e., assumed similarity: Nickerson, 1999; Epley et al., 2004; Srivastava et al., 2010). Does DMPFC modulation reflect the corrective adjustment processes that are engaged to the extent that a new person is evaluated as dissimilar to the self? A different

mechanism is suggested by an examination of the broader role of DMPFC in evaluation (including non-social evaluation) and psychological models of the interrelation between self-evaluation and evaluation of non-similar others. Specifically, DMPFC is associated with evaluation outside the social domain (Krain et al., 2006) and has been implicated in greater certainty about an evaluation (e.g., Krain et al., 2006; Bhanji et al., 2010). In contrast to the correction of self-projection hypothesis,it may be that certainty about self-evaluation explains why MPFC is modulated by the degree to which novel others are evaluated as different than the self.

# **Dissimilarity between the self and a novel person positively modulates DMPFC activation**

Studies have consistently found that DMPFC (BA 9/32) activation parametrically increases to the extent that a novel person is evaluated as dissimilar to the self (Mitchell et al., 2005; Tamir and Mitchell, 2010). For example, these studies ask participants to report their own preferences (e.g.,"how much do you look forward to going home for Thanksgiving?") and to evaluate the preferences of strangers. The strangers are often manipulated to vary in their dissimilarity to the participant (e.g., have a different or similar political orientation, gender, or race). When neural activation is measured during the evaluation of strangers' preferences, DMPFC (BA 9/32) is parametrically modulated by the dissimilarity between the participant's own preferences and the preferences they assign to the strangers (Mitchell et al., 2005; Tamir and Mitchell, 2010). In other words, the more participants evaluate the strangers as dissimilar to themselves, the more DMPFC activation increases when participants are evaluating the stranger's preferences.

The robust association between DMPFC modulation and dissimilarity between self and others has been theorized to reflect the role of DMPFC (BA 9/32) in correcting, that is, adjusting one's own self-representation to estimate the experience of a stranger. This explanation stems from psychological models of person evaluation which suggest that people use themselves as a starting point and correct as needed to evaluate unknown others (Nickerson, 1999; Epley et al., 2004; Srivastava et al., 2010). So if you encounter someone who shares your political orientation and you have to evaluate their position on a particular issue, you are likely to use your own experience to evaluate the person's position. However, if a new person does not share your political orientation, then you cannot simply use your own experience and your evaluation will likely correct for the extent to which the person differs in political orientation (e.g., a liberal may feel that a self-representation might partially apply to a stranger who is a moderate but not apply at all to someone who is conservative).

Does MPFC modulation reflect a correction of self-projection in social evaluation or is there another explanation that warrants examination before a strong conclusion can be drawn? There are a number of findings which raise the possibility that DMPFC modulation may instead reflect greater certainty in evaluation rather than correction of self-projection. For example, the previous studies have looked at DMPFC modulation during the evaluation of others. How does this compare to DMPFC modulation during self-evaluation and is it consistent with a correction of selfprojection explanation? Meta-analyses find that DMPFC (DMPFC is a label that is used in various ways in previous literature; the present article draws on published meta-analyses and uses the term DMPFC as label for relevant portions of BA 9/32. Within BA 9,*z* ranges from 20 to 42 in MNI coordinates, see **Figure 1**) is activated by both self-processing and evaluations of other people not personally known by the participant. In direction comparisons, some meta-analyses find that this activation is relatively greater for unknown others while other meta-analyses find no difference in this region's activation for self-processing and evaluation of unknown others (Self vs. Other comparison: Ochsner et al., 2005; Qin and Northoff, 2011; Roy et al., 2012). If the DMPFC reflects a correction of self-projection that occurs while evaluating another person, then it is puzzling why DMPFC is modulated by self-evaluation to the same degree as the evaluation of a person who is not personally known but assumed to be dissimilar to the self. If this region of DMPFC indexes correction away from a self-representation, why would this correction be engaged when evaluating oneself?

#### **An alternate conceptualization of why DMPFC is modulated by self-other dissimilarity: certainty about the evaluation**

Although it has not received much empirical attention, there is an alternate mechanism which could explain the pattern of DMPFC modulation found in these studies of self-evaluation and evaluation of strangers. Research on evaluation in non-social domains finds an association between DMPFC activation and greater certainty in evaluation (e.g., Krain et al., 2006; Bhanji et al., 2010; Eldaief et al., 2012). An integration of the psychological research on the interplay between self- and other-evaluation with the established association between DMPFC and evaluation certainty suggests that the DMPFC modulation found in paradigms involving self-evaluation and evaluation of strangers is tracking certainty in self-evaluation.

It has already been shown that certainty about one's selfevaluation modulates DMPFC activation (D'Argembeau et al., 2012). Studies on self-referent processing ask participants to rate the self-descriptiveness of personality traits and find that MPFC activation (extending into the DMPFC) is increased to the extent the traits are evaluated as self-descriptive (e.g., Moran et al., 2006; D'Argembeau et al., 2012). A personality trait may be evaluated as self-descriptive because people are certain about their association with the trait or they may be motivated to see themselves as characterized by that trait. One study delved further into these underlying reasons and found that a region within DMPFC was modulated by degree of certainty that the trait applied to self (D'Argembeau et al., 2012).

DMPFC is associated with certainty about evaluation both for non-social tasks and self-evaluation; but how can an increase in certainty explain why DMPFC activation increases to the extent we evaluate people who are dissimilar to the self? Wouldn't we be feeling uncertain when evaluating people we presume do not share our own qualities? Psychological research finds that evaluations of dissimilar others elicits a spontaneous self-evaluation and ironically solidifies our certainty about our own opinions and attitudes. In fact, certainty about our own preferences increases to the extent that the we perceive the target of our evaluation to be dissimilar to ourselves (Holtz and Miller, 2001; Holtz and Nihiser, 2008). In other words, this research suggests that rather than using the self as an anchor for evaluating other people (i.e., self-projection), the evaluation of other people triggers a spontaneous self-evaluation. And the more we evaluate someone to be different from us, the more we feel certain about where we stand on that attribute. Therefore, the increasing DMPFC activation found during a task that requires the evaluations of others could also be indexing an aspect of concomitant, spontaneous self-evaluations. Specifically, DMPFC activation may be modulated by increased certainty about the self to the extent that the target of evaluation is perceived as dissimilar to the self.

## **Implications of an association between DMPFC and certainty about self-evaluation**

If DMPFC modulation does reflect certainty in self-evaluation, then a reconceptualization of self-evaluation localizer tasks may be warranted. Some studies have used a self-referent processing task (i.e., asking participants to rate their own personality traits compared to rating the personality traits of a political figure) as a way of localizing neural regions associated with self-processing for subsequent tasks. Future research is needed to understand whether this task identifies regions within DMPFC that index the intended rich psychological aspects of self or simply certainty in evaluation (i.e., on average, we are likely more certain about self-evaluation than evaluation of a political figure only seen in the news).

#### **VMPFC: SOCIOEMOTIONAL CONNECTION OR FIRSTHAND EXPERIENCE?**

The correction of self-projection or certainty might explain the contribution of DMPFC to social cognition but what about the more ventral subdivision of MPFC (VMPFC) that is associated with evaluations of self and intimate others (VMPFC is a label that is used in various ways in previous literature; the present article draws on published meta-analyses and uses the term VMPFC as label for relevant portions of BA 10/32; *z* range −2 to 8, see **Figure 1**, Ochsner et al., 2005; Qin and Northoff, 2011; Murray et al., 2012; Roy et al., 2012)? Two different hypotheses have been proposed: the correction of self-projection (Mitchell et al., 2005; Tamir and Mitchell, 2010) and self-relatedness (Northoff et al., 2006; Krienen et al., 2010; Murray et al., 2012; Roy et al., 2012). Currently, there is only mixed support for the correction of self-projection perspective. The hypothesis that VMPFC may mediate self-relatedness is more consistent with the available data but more research is needed to unpack the psychological meaning of self-relatedness.

#### **VMPFC modulation and the correction of self-projection? current studies find inconsistent associations**

Unlike the DMPFC, VMPFC modulation has not shown a consistent pattern of association with evaluations of others as function of self-other dissimilarity (Mitchell et al., 2005; Krienen et al., 2010; Tamir and Mitchell, 2010). For example, an initial study asked participants to rate the preferences of unknown others (i.e., pleasure at having their photograph taken: Mitchell et al., 2005). VMPFC activation during the preference-evaluation task decreased to the extent that the unknown others were evaluated as dissimilar to the self in a post-scan procedure. Yet a follow-up analysis found a different pattern: VMPFC activation did not show a parametric association and it showed a positive (i.e., opposite) association to dissimilarity. VMPFC showed little change (in relation to baseline) during evaluations of other people who were evaluated (to any degree) as dissimilar from the self and a significant deactivation (in relation to baseline) when evaluating similar others (Tamir and Mitchell, 2011). It has been suggested that the different findings might indicate the existence of different neural mediation for computing global vs. specific dissimilarity. Dissimilarity was operationalized as a person's global political affiliation on the one hand (Mitchell et al., 2006) and trial-by-trial specific preferences on the other (i.e., Tamir and Mitchell, 2010). However, another series of studies found no association at all between VMPFC (BA 10) modulation and similarity between close others or strangers (Krienen et al., 2010). This research instead found that VMPFC shows increased activation for self-evaluations and evaluations of close others (regardless of similarity) and less activation for unknown others. Even if future research were to flesh out a robust association between VMPFC modulation and evaluations of dissimilar others, the correction of self-projection explanation still suffers from a parallel set of problems mentioned above in relation to DMPFC. Meta-analyses find that VMPFC activation is modulated by both self-evaluation and evaluation of intimate others (Ochsner et al., 2005; Qin and Northoff, 2011; Murray et al., 2012). It is unclear why people would need to correct the use of their self-representation when evaluating themselves or why they would use a self-projection process to evaluate someone they know well.

# **VMPFC modulation and self-relatedness of social evaluation: a socioemotional or cognitive mechanism?**

Another predominant hypothesis arising from current social evaluation research is that VMPFC marks "self-relatedness," that is, the socioemotional connection between the self and the person being evaluated (Northoff et al., 2006; Krienen et al., 2010; Murray et al., 2012; Roy et al., 2012). Self-relatedness is a socioemotional variable reflecting the extent to which the evaluation process draws on affectively rich, self-representations. Psychological models of social evaluation suggest that self-representations may be activated by evaluations of close others but not for the same reason as for unknown others. "Close others" are often defined by the extent to which representations of those people are associated with self-representations (Aron et al., 1992). It is not the case that the self-representation is theorized to serve as a starting point for evaluating the close other (i.e., a self-projection-like process which is then subject to correction). Instead, the evaluation of a close other draws on a representation of the close other that is emotionally charged because of its association with the self-representation. From this perspective, VMPFC is modulated by self-evaluation and evaluation of close others because those evaluations have a unique affective or socioemotional significance.

However, it may not be that VMPFC marks whether social evaluations are "self-like" in a socioemotional sense. In the existing research, socioemotional relation between the self and another person has always been confounded with the quality of information (e.g., cognitive representation) used to make an evaluation. We simply have a different class of information to draw on when we evaluate ourselves and people we actually know (e.g., greater complexity, abstraction, actual experience) compared to unknown others. A novel person and a romantic partner elicit different emotional reactions but they also elicit different cognitive representations. For both the self and romantic partners, there is a long history of storing person information which creates a more elaborated representation that includes both abstract and biographical information when compared to representations that could be used to evaluate someone who is relatively unknown (e.g., Sherman and Klein, 1994; Kihlstrom et al., 2003). A brain region that indexes one or more cognitive qualities that are emphasized in the representations of people we know well (i.e., self, close other) would also behave like the VMPFC across these social evaluation tasks as reviewed above (i.e., similar modulation across self-evaluation and evaluation of close others but less modulation for unknown others: Ochsner et al., 2005;Krienen et al., 2010; Qin and Northoff, 2011; Murray et al., 2012; Roy et al., 2012). This raises the possibility that the contribution of VMPFC to social cognition is more a cognitive (rather than affective) "self-relatedness." From this perspective,VMPFC may mediate a quality of the kind of information that feeds into self-evaluations that is also available for evaluations of people we actually know (but not as much for unknown others).

# **EXPANDING BEYOND MPFC (BA 9/10/32): VACC (BA 25) AND MOFC (BA 11) MEDIATE MOTIVATIONAL INFLUENCES ON BOTTOM-UP AND TOP-DOWN PROCESSING OF SOCIAL TARGETS**

Despite the heavy focus on MPFC (BA 9/10/32), an emerging body of literature suggests that at least two other midline regions are just as important for social cognitive processing: VACC (BA 25) and MOFC (BA 11) (see **Figure 1**). VACC and MOFC mediate motivational aspects of self-processing. Motivation has been ascribed a central role in psychological models of self-processing (Kunda, 1990; Robins and John, 1997). For example, self-evaluations tend to be positively tinged (also described as "self-serving,""the above average effect," "self-flattering," "self-enhanced" "optimistic bias": Alicke, 1985; Taylor and Brown, 1988; Dunning et al., 1989; Chambers and Windschitl, 2004). Self-evaluations are described as positively tinged to the extent that they are more positive than warranted by some other criterion and this positive slant may even be pre-potent, that is, the default mode of self-evaluation (Beer, 2007). Cognitive load makes self-evaluation even more positively tinged (Paulhus et al., 1989; Kruger, 1999; Koole and Dijksterhuis, 2001; Lench and Ditto, 2008; Beer and Hughes, 2010; Beer et al., 2013). Furthermore, the positive tinge of self-evaluation is not circumscribed to the lab (Dunning et al., 2004). People will wager money that their positively tinged views are accurate (Williams and Gilovich, 2008), expect that other people will share their positively tinged views (Hepper et al., 2011), and experience different life trajectories based on the extent of their positive slant (Robins and Beer, 2001). A positive tinge also pervades evaluations of close others but is less evident in evaluations of unknown others (Suls et al., 2002). A positive tinge may arise because people use incomplete information when making a social evaluation (e.g., using the first thing that comes to mind which happens to be positive: Chambers and Windschitl, 2004). However, a positive tinge can also arise from the motivation to cast oneself or a close other in a positive light (i.e., self-flattery: Taylor and Brown, 1988; Sedikides and Gregg, 2008). Despite the central role of motivation

in psychological models of self- and person evaluation, neural models of self-processing have paid little attention to motivation (Beer, 2007, 2012a). Recent research that addresses this gap suggests that (a) VACC may be modulated by opportunities that have the potential to accomplish a motivated self-evaluation (i.e., motivational influences on bottom-up processing) and (b) MOFC may be modulated by the extent to which the motivation to cast oneself in a positive light requires the adjustment of evaluation thresholds across contexts (i.e., top-down processing).

#### **VACC: MOTIVATIONAL INFLUENCES ON BOTTOM-UP PROCESSING**

VACC may mediate bottom-up sensitivity to opportunities that have the potential to affirm the way someone wants to evaluate themselves; however, it does not predict whether the opportunity will successfully lead to motivated self-evaluation (Moran et al., 2006; Sharot et al., 2007; Beer and Hughes, 2010; Hughes and Beer, 2012a). Social psychological theories of self- and otherevaluation often characterize these evaluations in terms of the contribution of bottom-up and top-down processes (e.g., Duncan, 1976; Shavelson and Bolus, 1982; Devine, 1989; Fiske and Neuberg, 1990; Brown et al., 2001; Beer, 2012b). "Top-down" and "bottom-up" are terms that are used widely, but somewhat differently across fields. In the case of motivated self-evaluation, these terms can be used to distinguish between subjective and objective construals of information. People may be motivated to see themselves in a particular way and, therefore, interpret information in a top-down, subjective manner that ensures the information can be used to accomplish a motivated self-evaluation. Or the motivation may affect the kind of information that is distinguished from other kinds of information (i.e., the influence of the motivation on relatively bottom-up processing: e.g., Brown et al., 2001).

The influence of motivation on relatively bottom-up processing of information can be illustrated by the example of people filling out an online dating profile who want to portray themselves as especially athletic compared to other people. If people scan the activities checklist with the goal of portraying themselves as especially athletic, then we predict that VACC will be modulated by activities on the checklist that objectively involve sports vs. activities that reflect poorly on athleticism (e.g., watching television). Similarly, someone with the goal of portraying themselves as artistic would show greater VACC activation when reading checklist activities that objectively involve artistic pursuits vs. all of the other options. In this way, VACC activation is implicated in the influence of motivation on bottom-up processing of the checklist because VACC modulation distinguishes between opportunities that are objectively consistent vs. inconsistent with the activated motivation. VACC is not implicated in purely top-down processing because research suggests that it would not predict the extent to which someone claims to be especially involved in each sport compared to other people (i.e., the success of the top-down goal of portraying oneself as particularly athletic). In other words, VACC modulation does not predict the extent to which the meaning or interpretation of the checklist activities are subjectively construed to fit with the activated motivation nor does it predict reported self-evaluation on those checklist activities. Instead, we hypothesize that VACC is modulated by a preliminary and relatively more bottom-up step of motivated evaluation: delineating the existence of opportunities that objectively have the potential to cast yourself in particular light.

## **VACC activation differentiates positive valence from negative valence, especially for social targets we want to see in a positive light**

The distinction between opportunity for motivated evaluation and success in motivated evaluation is important because they have been conflated in the current literature (Beer, 2007, 2012a). It is inappropriate to use the term "bias" (e.g., positively tinged) to label a self-endorsement of a positive trait or likelihood of a positive future event. There is no way to know whether someone has successfully achieved a positively tinged evaluation simply because they are rating positive traits or future events as particularly selfdescriptive. The person may truly possess high levels of that trait and be predisposed to a positive future or they may not. A response can be characterized as "biased" or positively tinged (rather than merely positive) when it is more positive than warranted by a benchmark criterion (Beer, 2007, 2012b).

For example, one way that positively tinged self-evaluation has been operationalized is the extent to which people inflate their own standing when comparing themselves to other people (Taylor and Brown, 1988; Chambers and Windschitl, 2004). This line of research often asks participants to make social-comparative judgments. That is, participants are asked to evaluate how much they possess personality traits in comparison to their average peer (i.e., much less, about the same or much more than someone of the same, age, community, education level, etc.). When participants' social-comparison evaluations are averaged across hundreds of personality traits, their average evaluation, by definition, should be somewhere near the average peer benchmark. However, the majority of people report having significantly higher levels of positive personality traits and significantly lower levels of negative traits than their average peer (Taylor and Brown, 1988; Chambers and Windschitl, 2004). In this social-comparison task, VACC is modulated by the condition that includes positive personality traits (compared to negative personality traits) but it does not predict the extent to which someone reports an overall significantly more desirable personality in comparison to their average peer (Beer and Hughes, 2010; Hughes and Beer, 2012a).

VACC has been implicated in the detection of emotionally significant, that is, valenced information in a variety of tasks (compared to non-valenced information: Bush et al., 2000). However, research on social cognition has shown that VACC modulation may differentiate between particular classes of valence depending on motivational state. When people evaluate well-liked social targets (e.g., the self, romantic partner, well-liked roommate), VACC activation differentiates trials where endorsement would portray the target in a positive light (i.e., desirable personality traits, likelihood of a positive future) from trials where endorsement would portray the target in a negative light (i.e., undesirable personality traits, likelihood of a negative future: Moran et al., 2006; Sharot et al., 2007; Beer and Hughes, 2010; Hughes and Beer, 2012a). However, when there is reduced motivation to portray the target in a positive light (i.e., personality traits that are not considered central to one's self-view: Sedikides and Gregg, 2008; a non-close other: Suls et al., 2002), VACC activation is less likely

to differentiate trials on the basis of how endorsement would portray the target (i.e., the self: Moran et al., 2006; an assigned college roommate: Hughes and Beer, 2012a). This research suggests that VACC is important for identifying opportunities to portray someone in a particular light but it does not predict whether the opportunity actually leads to successful motivated evaluation.

# **Bottom-up sensitivity to information based on its potential to affirm motivated self-evaluations: connectivity between VACC and MOFC**

Psychophysiological interaction connectivity analyses (Friston et al., 1997) conducted on previously published results (Beer and Hughes, 2010) further supports the hypothesis that VACC (BA 25) mediates a preliminary step but not the ultimate success of motivated evaluation (for the full set of results, see **Figure 2**; **Table 1**).

*Methods.* Whole-brain PPI analyses were conducted in order to investigate the functional connectivity of the VACC region that differentiated social-comparative evaluations made in the Positive condition from the social-comparative evaluations made in the Negative condition (Beer and Hughes, 2010). Specifically, participants rated how much they had desirable (Positive condition) and undesirable (Negative condition) personality traits in comparison to their average peer. Imaging data were preprocessed using the FSL software toolbox [Oxford Center for Functional Magnetic Resonance Imaging (FMRIB); Smith et al., 2004]. Functional images were motion corrected using MCFLRT (Jenkinson et al., 2002) and non-brain structures were stripped from functional and structural volumes using the Brain Extraction Tool (BET; Smith, 2002). Images were then smoothed (8 mm full-width half-maximum) and normalized to MNI-152 space during preprocessing. Parameters for normalization into a standard space were obtained by multiplying the transformation matrices across a two-step process in which the functional images were registered to the MP-RAGE

**FIGURE 2 | PPI connectivity analyses for the VACC seed associated with social comparisons about Positive (i.e., desirable) vs. Negative (i.e., undesirable) personality traits**. **(A)** Each participant's time series was extracted from the VACC seed (5 mm radius sphere around group peak: 14, 38, −4 from the Positive vs. Negative contrast, Beer and Hughes, 2010). **(B)** The VACC seed shows relatively more positive covariation with an MOFC region. This MOFC region overlaps with the MOFC region that regulates the extent to which social comparisons are positively tinged (red: MOFC region found in PPI analyses; blue: MOFC region found in Beer and Hughes, 2010; purple: overlap between MOFC region in connectivity and primary analyses).

(6 DOF affine transformation), and the MP-RAGE was registered to the MNI-152 template (12 DOF affine transformation).

Functional Magnetic Resonance Imaging analysis was performed using FSL's FEAT (FMRI Expert Analysis Tool version 5.98). A fixed-effects analysis modeled event related responses for each participant. Responses made in the Positive and Negative conditions were modeled as events using a canonical hemodynamic response function with a temporal derivative. Motion regressors were modeled as regressors of no interest. Each participant's time series was extracted from the VACC seed found in the group analyses of the Positive vs. Negative condition (5 mm radius sphere around group peak: 14, 38, −4 from the Positive vs. Negative contrast, Beer and Hughes, 2010). Two PPI regressors were created: the interaction of the time series of the VACC seed with (a) the time series of the Positive condition regressor and (b) the time series of the Negative condition regressor.

A subsequent fixed-effects analysis was conducted modeling the following regressors: (a) Positive condition regressor, (b) Negative condition regressor, (c) temporally filtered activity across the time course from the VACC seed region, (d) PPI regressor for the Positive condition, and (e) PPI regressor for the negative condition. The PPI regressors were contrasted in a GLM. A second-level analysis created contrast estimates for each participant by collapsing across the two runs, treating runs as a fixed effect. FEAT's FLAME module (FMRIB's Local Analysis of Mixed Effects; Smith et al., 2004) was used to preformed mixed effects analysis which created group average maps for contrasts of interest (*p* < 0.005, uncorrected). The significance threshold was chosen because it is the recommended threshold for striking an optimal balance between Type I and Type II error when reporting analyses of brain activation in relation to complex psychological processes; simulation studies show that other significance thresholds raise the possibility of Type II error beyond acceptable limits (Lieberman and Cunningham, 2009). As the first report of functional connectivity in relation to motivated self-evaluation, the goal was to be as inclusive as reasonably possible to avoid missing true effects.

*Results.* When people make social comparisons about desirable traits,VACC shows relatively more positive covariation with a portion of MOFC (BA 11) that was found to regulate the extent to which social-comparative evaluations are positively tinged in the primary analyses. Although directionality cannot be determined from PPI analyses, it is possible that VACC is involved in analyzing the opportunities afforded by the content of an evaluation (i.e., a desirable trait vs. an undesirable trait). That information may then be processed upstream by the MOFC before an evaluation is expressed.

#### **MOFC: MOTIVATIONAL INFLUENCES ON TOP-DOWN PROCESSING**

As mentioned above, the MOFC is implicated in self-evaluation. How should we conceptualize its role? Take the example mentioned earlier: people who view themselves as particularly athletic complete an activity checklist on an online dating profile. Their expectation may be met when they are able to endorse participation in numerous sports on the checklist. But if they find themselves able to only endorse involvement in just one or two of the numerous sports possibilities, they may have one of two


**Table 1 | PPI connectivity analyses with VACC seed from data published in Beer and Hughes (2010).**

possible reactions. If their self-esteem is not staked on their athletic ability, they might realize that they are not so different from other people in this regard. However,if the procedure threatens their selfesteem, they may react defensively by changing their evaluation threshold in such a way that they can evaluate themselves as having even more superior athleticism. For example, they may evaluate degree of athleticism based on the intensity of involvement in a particular sport, rather than on the number of sports activities they can endorse on the checklist. In one case, the initial expectation of portraying oneself as athletic is dismissed during activity endorsement (i.e., an initial top-down influence is controlled). In the case where self-esteem is threatened, motivation to portray oneself in a particular way exhibits a top-down influence on activity endorsement by biasing the standards with which the evaluation is made. MOFC modulation has been associated with both of the examples above: realizing the self is not as special as expected and defensive reactions when self-esteem is threatened. Connectivity analyses suggest that MOFC modulation likely reflects different psychological processes across these circumstances. In particular, a network involving MOFC and (a) relatively more positive covariation with striatum and (b) relatively less positive covariation with middle frontal gyrus may aid self-evaluations that protect the self in the face of self-esteem threat. However, MOFC activation found in association with dismissing the influence of a self-evaluation motivation does not show such connectivity. In this way, MOFC may mediate top-down motivational influences on social evaluation by supporting changes in evaluation standards to either facilitate or control an activated motivational state.

#### **When self-esteem is not at stake: OFC function is negatively associated with positively tinged social evaluations**

Both neuroimaging and lesion studies have shown that reduced MOFC function is associated with positively tinged social evaluations (i.e., self and close others: Beer et al., 2003; Beer et al., 2006a, 2010; Beer and Hughes, 2010; Hughes and Beer, 2012a). This relation holds across various operationalizations of self-flattery: the difference in the way you see yourself compared to how others view you, self-evaluation of task achievement compared to actual task performance on an unimportant task, and base rates of social comparisons.

A series of studies found that patients with OFC damage tend to view their social behavior in a positively tinged manner (Beer et al., 2003, 2006a). In one study, patients with OFC damage were socially disinhibited compared to healthy control participants yet they expressed greater pride in their social behavior (i.e., inappropriate teasing of strangers: Beer et al., 2003). Another study found that patients with OFC damage did not evaluate the appropriateness of their social behavior any differently than healthy control participants or participants with dorsolateral prefrontal cortex (DLPFC) damage. Yet outside observers, blind to participant status, rated the social behavior of the patients with OFC damage to be significantly more inappropriate than the other groups (i.e., too familiar for an interaction with a stranger: Beer et al., 2006a).

Neuroimaging results complement the lesion studies: reduced OFC activation (BA 11) is associated with positively tinged evaluations of one's task performance and personality (Beer and Hughes, 2010; Beer et al., 2010; Hughes and Beer, 2012a). In one study, participants estimated their confidence in their answers to a trivia task. Reduced OFC activation (BA 11) predicted the extent to which participants were overconfident about their incorrect trivia answers (Beer et al., 2010). Reduced OFC activation also predicts the extent to which people view themselves and their romantic partners to have significantly more desirable personalities than their peers. As mentioned above in the section on VACC function, these studies ask participants to compare themselves or their romantic partners to an average peer (i.e., a person who is the same gender, age, from the same community, university campus, etc.). When these socialcomparative judgments of personality traits are averaged across hundreds of traits, each participant (or their romantic partner) should, by definition, be evaluated as comparable to their average peer. Whereas VACC activation showed no relation, reduced OFC activation is associated with the extent to which people evaluate themselves (Beer and Hughes, 2010) or their romantic partners (Hughes and Beer, 2012a) to have significantly more positive traits and significantly fewer negative traits than their average peer. Taken together, these studies provide robust evidence that reduced OFC activation predicts positively tinged evaluations on a trial-by-trial, condition, and individual difference basis.

#### **The case of self-esteem defense: a positive association between OFC activation and self-protection**

There is an exception to the findings described above: increased MOFC (BA 11) activation predicts self-evaluations in situations where self-esteem comes under attack (Hughes and Beer, 2013). Self-esteem is typically threatened when people receive negative feedback about their personality, academic abilities, or skills (Baumeister et al., 1993; Leary et al., 1998; vanDellen et al., 2011). People cope with self-esteem threat by inflating the positively tinged nature of their self-evaluation (including social comparisons: Beer et al., 2013 and see vanDellen et al., 2011 for review). The lesion and fMRI research reviewed above did not include any manipulations to threaten self-esteem. What happens to the underlying neural modulation when social-comparison judgments are used to cope with self-esteem attack? In other words, what neural regions mediate self-evaluations that are selfflattering (e.g., positively tinged with the purpose of protecting the self against a self-esteem threat)? One fMRI study addressed this question by using the very same social-comparison evaluation as a previous study (Beer and Hughes, 2010) but added in a

self-esteem threat manipulation (Hughes and Beer, 2013). Participants learned that other students had found them either likable or unlikable and then evaluated how their personalities compared to their peers. Consistent with previous research, evaluations made after learning that others found them unlikable were even more self-flattering (compared to learning that others found them likable). The extent to which social comparisons became even more self-flattering as a function of self-esteem attack was positively associated with increased MOFC modulation (Hughes and Beer, 2013). Therefore, this study found that MOFC modulation predicted a change in self-evaluation but, in the case of self-esteem attack, it shows a positive association with self-protection.

Although the studies on social comparison (Beer and Hughes, 2010; Hughes and Beer, 2013) provided a rigorous test of the association between MOFC modulation and self-evaluation as a function of self-esteem threat, they were not designed to pinpoint the underlying psychological process that explained the association. One study has begun to address this issue by using Signal Detection Theory to investigate the neural associations of selfevaluations used to protect one's self-esteem (Hughes and Beer, 2012b). Just as people tend to inflate their social standing on personality traits, they tend to claim knowledge about concepts beyond what they actually know or could know (i.e., overclaim knowledge: Paulhus et al., 2003; Beer et al., 2010). However, when self-esteem is potentially at stake (i.e., their false claims could be discovered), people reduce the extent to which they overclaim knowledge (Paulhus et al., 2003) or inflate their social standing on personality traits (McKenna and Myers, 1997). In conditions where false claims would make them look foolish, people protect their self-esteem by adopting a different standard (i.e., decision threshold) for claiming knowledge which consequently reduces overclaiming. An fMRI study found that MOFC (BA 11) modulation was positively associated with the shift toward a more conservative standard in conditions where participants would look foolish if they were to make false claims of knowledge (i.e., they were warned that some concepts in the list did not exist: Hughes and Beer, 2012b).

# **A top-down role of MOFC in social evaluation**

Consistent with the hypothesis that self-evaluations used to cope with self-esteem threat are distinct from self-evaluations made in the absence of threat, a relatively consistent pattern of functional connectivity emerged in the studies that investigated the impact of self-esteem threat on self-evaluations (Hughes and Beer, 2012b, 2013) and was distinct from the pattern found in a parallel socialcomparison procedure that did not manipulate self-esteem threat (Beer and Hughes, 2010, see **Table 2**).

*Methods.* Whole-brain PPI analyses were conducted in order to investigate the functional connectivity of MOFC during social comparisons in the presence and absence of self-esteem threat from three previously published datasets (Dataset 1: Hughes and Beer, 2013; Dataset 2: Hughes and Beer, 2012a; Dataset 3: Beer and Hughes, 2010). For all three datasets, the preprocessing steps were the same as described earlier for the PPI analyses of theVACC seed. PPI analyses were conducted as follows. In Dataset 1 (Hughes and Beer, 2013), participants made social-comparative evaluations of


#### **Table 2 | PPI connectivity analyses with MOFC seed\*.**

\*No regions found for increased positive covariation in Beer and Hughes (2010).

their personality traits while the presence of self-esteem threat was manipulated. In other words, participants evaluated how their personality traits compared to an average peer after just learning that a majority of peers found them unlikable (Threat condition) or a majority of peers found them likable (No Threat condition). As previously published, increased MOFC activity is associated with positively tinged evaluations of one's personality in the Self-esteem Threat condition (both a main effect and individual differences in evaluations made in the Threat vs. No Threat condition: Hughes and Beer, 2013). Each participant's time series was extracted from the MOFC seed (group peak: −12, 54, −14 from the Threat vs. No Threat contrast, Hughes and Beer, 2012a). Two PPI regressors were created: interaction of the time series of the MOFC seed with (i) the time series of the Threat condition regressor and (ii) the time series of the No Threat condition regressor.

In Dataset 2 (Hughes and Beer, 2012b), participants evaluated their familiarity with blocks of information they believed would make them appear intelligent while their awareness of the exposure of fake claims was manipulated. Specifically, all blocks of information contained items that existed and items that do not exist but participants were only warned of the possibility of non-existent items in half of the blocks (Accountable condition vs. an Unaccountable condition where they were not warned that they might be claiming familiarity with something that does not exist). Increased MOFC activity was associated with the shift toward a more conservative standard for claiming knowledge in the Accountable condition. Each participant's time series was extracted from the MOFC seed (5 mm radius sphere around group peak: −6, 58, −20 from the Accountable vs. Not Accountable contrast; Hughes and Beer, 2012b). Two PPI regressors were created: interaction of the time series of the MOFC seed with (i) the time series of the Accountable condition regressor and (ii) the time series of the Not Accountable condition regressor.

In Dataset 3 (Beer and Hughes, 2010), participants made the same social-comparative evaluations of their personality traits as in Dataset 1 but self-esteem threat was not manipulated. Instead, the breadth of personality traits were manipulated such that they could either be broadly construed (i.e., Broad condition: trait has a wide variety of behavioral manifestations such as "capable") or more specifically construed (i.e., Specific condition: trait has few behavioral manifestations such as "talkative"). Reduced MOFC activity was associated with viewing the self as having more positive and fewer negative traits in comparison to the average peer (i.e., positively tinged evaluations of one's personality). Each participant's time series was extracted from the MOFC seed (5 mm radius sphere around group peak: −4, 46, −10 from the Specific vs. Broad contrast; Beer and Hughes, 2010). Two PPI regressors were created: interaction of the time series of the MOFC seed with (i) the time series of the Specific condition regressor and (ii) the time series of the Broad condition regressor.

After PPI regressors were created, all of the datasets were subjected to a subsequent fixed-effects analyses in the same manner as described earlier for the PPI analyses of the VACC seed. Specifically, the fixed-effects analyses to modeled condition of interest regressors (i.e., Dataset 1: Threat and No Threat conditions (Hughes and Beer, 2013; Dataset 2: Accountable and Unaccountable conditions (Hughes and Beer, 2012b; Dataset 3: Specific and Broad conditions (Beer and Hughes,2010), a temporal filter of activity across the time course from the MOFC seed region, and the PPI regressorsfor conditions of interest. The PPI regressors

were contrasted in a GLM. FEAT's FLAME module (FMRIB's Local Analysis of Mixed Effects; Smith et al., 2004) was used to preform mixed effects analyses for each dataset, which created group average maps for contrasts of interest (*p* < 0.005, uncorrected).

*Results.* PPI connectivity analyses (Friston et al., 1997) conducted on previously published results (Beer and Hughes, 2010; Hughes and Beer, 2012b, 2013) suggest that functional connectivity between MOFC, the striatum, and the middle frontal gyrus (BA 9) may support self-evaluations used to protect self-esteem in the face of threat (see **Figure 3**; **Table 2**). When self-esteem is at stake, the region of MOFC that is associated with self-evaluation shows relatively less positive covariation with middle frontal gyrus (BA 9) and relatively greater positive covariation with striatum. It is possible that functional connectivity between MOFC and striatal subregions reflects whether a shift to more conservative or liberal evaluation standards will be most rewarding in the face of selfesteem threat. For example, greater positive covariation between MOFC and caudate was found when liberal thresholds were advantageous for protecting self-esteem (Hughes and Beer, 2013) and between MOFC and putamen when conservative thresholds were advantageous for protecting self-esteem (Hughes and Beer, 2012b). Taken together, this research suggests that MOFC aids top-down influences on social cognition by adjusting evaluation standards as function of motivational state.

## **CONCLUSIONS AND FUTURE CONSIDERATIONS FOR RESEARCH ON THE ROLE OF MPFC, VACC, AND MOFC IN SELF-EVALUATION**

While much progress has been made since the discovery in the early 2000s that MPFC is associated with self-evaluation, several hypotheses have been tested and eliminated. The new hypotheses described here will benefit from future research guided by a number of questions. For example, even though MPFC has received the bulk of attention, there are still many questions that remain. It would be extremely useful (and feasible) to conduct connectivity analyses on the large, existing body of studies that have measured

MPFC modulation in relation to both self-evaluation and the evaluation of unknown others. One potential drawback of the "correction of self-projection" hypothesis for both VMPFC and DMPFC is that these regions are activated for evaluation of targets where correction of self-projection is unlikely (e.g., self and/or close others). If the functional connectivity of VMPFC and DMPFC is different during self-evaluation compared to evaluations of unknown others, those results would eliminate some concerns about the correction of self-projection hypothesis. Furthermore, more research is needed to decouple the affective vs. cognitive qualities shared by evaluation of the self and close others to more clearly delineate the role of VMPFC in social evaluation. If VMPFC is similarly modulated by the evaluation of another person where there is an emotional association with the self but no actual firsthand experience or basis for selfprojection, then that would be strong evidence that VMPFC indexes the emotional aspect of self-relatedness when evaluating other people.

Additionally, more research is needed to clarify the possibility that VACC is involved in detecting opportunities that might fulfill expectations about self-evaluation. Does VACC mediate sensitivity to motivationally consistent information or positively valenced information when it is motivationally consistent? This question is important because psychological models show that motivation to see oneself in a positive light is not the only motivation that impacts self-evaluation. For example, the relation between valence and motivation becomes uncoupled when self-verification, another motivation known to influence selfevaluation, is activated. People often want to feel that their selfevaluations are correct and are vigilant for opportunities that have the potential to verify their current self-evaluations. In fact, this research finds that people with negative self-evaluations desire chances to confirm these negative self-evaluations (Swann et al., 1989). In this situation, the evaluation of negative traits (rather than positive traits) would have the potential to affirm motivated self-evaluation. If VACC mediates sensitivity to motivationally consistent information, then it should be modulated by

**FIGURE 3 | PPI connectivity analyses for the MOFC seed associated with self-protection in the face of self-esteem threat**. **(A)** MOFC seed regions for connectivity analyses of previously published studies (5 mm radius spheres around group peak). Dark green seed: social comparisons while under Threat vs. No Threat contrast, group peak −12, 54, −14 (Dataset 1: Hughes and Beer, 2013). Light green seed: claims of knowledge while Accountable vs. Not Accountable contrast, group peak: −6, 58, −20 (Dataset 2: Hughes and Beer, 2012b). **(B)** When false claims of knowledge could be discovered, the MOFC seed associated with self-protection (i.e., less inflated claims) shows relatively more positive covariation with the right putamen (22, −10, 6) and less positive covariation with the left middle frontal gyrus (BA 9; −24, 52, 30). **(C)** When self-esteem was threatened, the MOFC seed associated with more self-flattering evaluations shows relatively more positive covariation with the right caudate (14, 16, −10) and less positive covariation with the middle frontal gyrus (BA 9).

opportunities to affirm a negative self-evaluation for people who are motivated to confirm a negative self-view. Furthermore, more research is needed to replicate and understand the psychological significance of the connectivity between VACC, MOFC and the other regions found in the PPI analyses.

Finally, more research is needed to replicate and elucidate the functional connectivity of MOFC in association with selfevaluations made in the presence and in the absence of self-esteem threat. While there is convergent evidence that more positive covariation with striatum and reduced covariation with middle frontal gyrus is associated with self-evaluation used to protect self-esteem, much less is understood about the significance of regions that covary with MOFC modulation associated with self-evaluations made in the absence of self-esteem threat.

In conclusion, a new framework is proposed to account for the contribution of MPFC, VACC, and MOFC to social cognition. MPFC is broadly implicated in self-evaluation but may be characterized by a ventral to dorsal division when evaluating others

#### **REFERENCES**


based on their intimacy. Certainty about evaluation may better characterize the contribution of DMPFC to social cognition than the correction of self-projection. The association between VMPFC and self-relatedness will be clearer once future research disentangles shared emotional and cognitive properties of evaluation of self and close others. Further, previous research has failed to take into account the fundamental role that motivation has in selfevaluations. As a result, the role of VACC and MOFC in social cognition has been obscured until recently. VACC may mediate bottom-up sensitivity to information based on its potential for helping us evaluate ourselves and others the way we want. MOFC may mediate top-down motivational influences on self-evaluation.

## **ACKNOWLEDGMENTS**

Funding for the article was supported by NSF Grant (NSF-BCS-1147776) to Jennifer S. Beer. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. (DGE-1110007).


*Psychol.* 44, 631–639. doi:10.1016/j. jesp.2007.02.011


the positivity of self-presentation. *Soc. Cogn. Affect. Neurosci.* 7, 389–400. doi:10.1521/soco.1989.7.4. 389


**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 01 May 2013; accepted: 21 July 2013; published online: 02 August 2013. Citation: Flagan T and Beer JS (2013) Three ways in which midline regions contribute to self-evaluation. Front. Hum. Neurosci. 7:450. doi: 10.3389/fnhum.2013.00450*

*Copyright © 2013 Flagan and Beer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Self-related processing and deactivation of cortical midline regions in disorders of consciousness

#### **Julia Sophia Crone1,2,3\*,Yvonne Höller <sup>3</sup> , Jürgen Bergmann1,2, Stefan Golaszewski <sup>3</sup> , Eugen Trinka<sup>3</sup> and Martin Kronbichler 1,2**

<sup>1</sup> Centre for Neurocognitive Research, Neuroscience Institute, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria

<sup>2</sup> Department of Psychology and Centre for Neurocognitive Research, University of Salzburg, Salzburg, Austria

<sup>3</sup> Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria

#### **Edited by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada

#### **Reviewed by:**

Lorina Naci, Western University, Canada Zirui Huang, University of Ottawa, Canada

#### **\*Correspondence:**

Julia Sophia Crone, Centre for Neurocognitive Research, Neuroscience Institute, Christian Doppler Klinik, Paracelsus Medical University, Ignaz-Harrer-Street 79, 5020 Salzburg, Austria e-mail: j.crone@neurocognition.org

Self-related stimuli activate anterior parts of cortical midline regions, which normally show task-induced deactivation. Deactivation in medial posterior and frontal regions is associated with the ability to focus attention on the demands of the task, and therefore, with consciousness. Studies investigating patients with impaired consciousness, that is, patients in minimally conscious state and patients with unresponsive wakefulness syndrome (formerly vegetative state), demonstrate that these patients show responses to self-related content in the anterior cingulate cortex. However, it remains unclear if these responses are an indication for conscious processing of stimuli or are due to automatic processing. To shed further light on this issue, we investigated responses of cortical midline regions to the own and another name in 27 patients with a disorder of consciousness and compared them to task-induced deactivation. While almost all of the control subjects responding to the own name demonstrated higher activation due to the self-related content in anterior midline regions and additional deactivation, none of the responding patients did so. Differences between groups showed a similar pattern of findings. Despite the relation between behavioral responsiveness in patients and activation in response to the own name, the findings of this study do not provide evidence for a direct association of activation in anterior midline regions and conscious processing.The deficits in processing of self-referential content in anterior midline regions may rather be due to general impairments in cognitive processing and not particularly linked to impaired consciousness.

**Keywords: consciousness, vegetative state, self, anterior cingulate, default network**

# **INTRODUCTION**

Self-related content is processed in several cortical midline regions (Kelley et al., 2002; Northoff and Bermpohl, 2004; Mitchell et al., 2005; Northoff et al., 2006; Uddin et al., 2007; Zhu et al., 2007; Platek et al., 2008; Yaoi et al., 2009; Herwig et al., 2012; Salomon et al., 2013). Most of these studies involve an evaluation of selfrelated in comparison to other content which is interpreted as a differentiation between both, and therefore, as conscious awareness of self. However, self-related stimuli, in contrast to only familiar and other stimuli, activate anterior parts of the default mode network (DMN) such as the anterior cingulate cortex (ACC) (Qin and Northoff, 2011). These regions normally show deactivation during tasks involving higher cognitive and attention-demanding processing of external stimuli (Shulman et al., 1997b; Greicius and Menon, 2004). It is postulated that deactivation corresponds to an interruption of internal ongoing processes to make resources available that are necessary to focus attention on the demands of the task (Gusnard et al., 2001; Raichle and Snyder, 2007; Anticevic et al., 2012). Focusing attention to solve cognitive tasks is a process that goes along with conscious awareness of the environment (Fransson, 2005). While other attention-demanding stimuli interrupt the activity in the ACC (Shulman et al., 1997a), self-related stimuli do not (Qin and Northoff, 2011). Qin and Northoff (2011)

speculate that self-related processing may be present not only during conscious awareness of external stimuli but during resting state itself.

Investigations of preserved brain responses to self-related stimuli such as the own name have been performed in subjects with reduced or impaired conscious awareness. Patients with unresponsive wakefulness syndrome (formerly vegetative state; VS/UWS) and in minimally conscious state (MCS), i.e., patients with a disorder of consciousness (DOC) after severe brain injury, are, by definition, not or only minimal consciously aware. Diagnosis in these patients is still very challenging (Schnakers et al., 2009), and thus, several attempts have been made to find additional diagnostic criteria linking brain responses to conscious behavior (e.g., Laureys et al., 2002; Boly et al., 2004; Owen et al., 2006; Monti et al., 2010; Schnakers et al., 2010; Fernandez-Espejo et al., 2011; Goldfine et al., 2011; Gosseries et al., 2011; Naci et al., 2012; Estraneo et al., 2013). Self-relatedness has been of particular interest because studies could demonstrate corresponding brain responses in these patients (Mazzini et al., 2001; Kotchoubey et al., 2004; Laureys et al., 2004; Perrin et al., 2006; Di et al., 2007; Schnakers et al., 2008). A single-subject study, for example, investigating responsiveness to the own name in a patient diagnosed as VS/UWS detected preserved activation in cortical midline

structures (Staffen et al., 2006). Another study in seven VS/UWS and four MCS patients demonstrates that the ACC in particular is responsive to self-related stimuli in patients diagnosed as unconscious or minimally conscious (Qin et al., 2010). Moreover, this responsiveness correlates with the level of behavioral responses the patient is able to perform. The authors propose that neural activity in the ACC during self-relatedness may be a diagnostic marker for the degree of consciousness in patients. Yet, the authors themselves emphasize that activation of the ACC may only reflect automatic processing of self-related stimuli rather than conscious processes. Since activity of the ACC is present during resting state and this region is normally suppressed in response to conscious processing of external stimuli, and since it is not known to which extent conscious awareness of external stimuli is reflected in the resting brain, activity of the ACC in response to self-related content does not necessarily reflect conscious processing. Moreover, self-related speech was not directly compared to non-self-related speech in the previous study. But especially for diagnostic criteria, it is essential to find evidence for conscious processing and to exclude the possibility that the association with the degree of behavioral responsiveness is rather due to a more general deficit in cognitive processing of association areas.

So far, previous studies whether performed in healthy subjects or in impaired consciousness could not sufficiently clarify the relationship between activation in anterior cortical midline regions in response to self-related stimuli and conscious processing. The aim of this study is twofold: first, we want to extend previous findings in patients with DOC by including a control condition for selfreferential processing and second, we want to take into account additional brain responses which may provide further indication for conscious processing of stimuli. A recent study in patients with DOC was able to show that listening to sentences induces deactivation in all healthy and thus conscious subjects but only in 9 out of 25 patients in regions of the DMN (Crone et al., 2011). Eight of these patients also showed activity in response to language in frontal regions associated with conscious processing. The conclusion is that deactivation of the DMN seems to reflect conscious and attention-involved processing of external stimuli.

Based on the study by Qin et al. (2010), we investigated activation in response to the own name in impaired consciousness with two important improvements: we included a control condition for self-relatedness to be able to associate findings specifically to selfrelated processing and we looked for deactivation in regions of the DMN during stimuli processing to identify possible indicator for conscious processing. First, we want to see if processing of the own name in the ACC in patients is related to the self-referential aspect of the own name tested with a control condition. Second, we want to search for other indications of conscious processing in patients showing responses to the self-related content. If responding to the own name compared to another goes along with deactivation and non-responding with no deactivation, this may support the assumption that activity in the ACC during self-relatedness can be associated with consciousness. If self-related content, though, is processed in DOC patients without a disruption of internal processes within the DMN while healthy controls show both, it remains questionable if responses of the ACC to self-related content are a valid marker for the degree of consciousness.

# **MATERIALS AND METHODS**

The study was approved by the Ethical Committee of Salzburg (Ethics Commission Salzburg/Ethikkommission Land Salzburg; number 415-E/952).

# **SUBJECTS**

In this study, 17 healthy subjects, 21 patients with VS/UWS, and 9 patients in MCS were investigated. Three patients had to be excluded from further analysis due to severe head motion (translation ≥2.5 mm; rotation ≥2.5°). The remaining 18 patients with VS/UWS (mean age = 50; 6 female) and 9 patients in MCS (mean age = 47; 5 female) were compared to 17 healthy subjects (mean age = 44; 10 female). Patients were clinically assessed once a week during in-patient stay using standardized scales, i.e., the Coma Recovery Scale-Revised (CRS-R) (Giacino et al., 2004). All patients participating in this study showed preserved auditory functioning, largely preserved brainstem reflexes, and a fairly preserved sleep-wake-cycle based on neurological examination. None of the patients were artificially ventilated or sedated at time of scanning. Additional information of the patients is listed in **Table 1**. Control subjects were recruited at the Paris Lodron University of Salzburg. Written informed consent was obtained from all healthy subjects and from the guardianship of all patients according to the Declaration of Helsinki.

#### **DATA ACQUISITION**

Control subjects and patients were scanned while listening to their own name or another name (e.g., Martin, hello Martin). Stimuli were recorded in German language with Cool Edit Pro 2.00 (1992–2000 Syntrillium Software Corporation) by two men and two women, none of which were familiar to the patient or knew his real first name. Two fMRI sessions were performed, each containing 30 stimuli of the own name and 30 stimuli of the other name, as well as 30 silent null events (duration = 2200 ms; ISI = 1800 ms). Stimuli were presented in an event-related design in pseudorandomized order. During each run, 180 functional images were acquired using a 3T Philips scanner (Philips Achieva; 21 slices with a thickness of 6 mm; matrix size = 64 × 64; FoV = 210 mm<sup>2</sup> ; TR = 2200 ms; TE = 45 ms; flip angle = 90°) and a 3T Siemens scanner (Siemens TIM TRIO; 21 slices with a thickness of 6 mm; matrix size = 80 × 80; FoV = 210 mm<sup>2</sup> ; TR = 2200 ms; TE = 30 ms; flip angle = 70°). Eight control subjects, five patients in MCS, and 11 patients with VS/UWS were investigated with the Philips Achieva and seven control subjects, four patients in MCS, and seven patients with VS/UWS were investigated with the Siemens TIM TRIO. In addition, high-resolution, T1-weighted MPRAGE sequences for anatomic information were acquired for each participant.

#### **DATA ANALYSES**

Functional data were preprocessed and analyzed using Statistical Parametric Mapping (version SPM8; Wellcome Department of Cognitive Neurology, London, UK)<sup>1</sup> . The first six functional scans were considered as dummy scans and were discarded. For

<sup>1</sup>http://www.fil.ion.ucl.ac.uk/spm/

**Table 1 | Patients' information;**

 **MCS, minimally**

 **conscious**

**state;VS/UWS,**

**unresponsive**

**wakefulness**

 **syndrome.**


(Continued)


**Table 1 | Continued**

this investigation, we performed a group analysis and a singlesubject analysis. Both analyses are important because results at the group level do not always reflect findings in the single subject (Kotchoubey et al., 2004; Holler et al., 2011) which are crucial for diagnosis in patients with DOC. Thus, we implemented two different preprocessing approaches: for group analysis, preprocessing steps included the following procedures: segmentation of the T1 image to compute the gray matter images; realignment to compensate for motion; unwarping (adjustment for movementrelated artifacts); pre-coregistration of the functional images of session 2 to session 1; coregistration of the mean EPI to the participant's gray matter image; normalization of an average image of the functional images with the segmentation parameters; data were spatially smoothed using a Gaussian Kernel of 8 mm full width at half maximum (FWHM); For single-subject statistical analysis, we did not perform normalization of the functional data to avoid artifacts induced by severe lesions. Voxel-wise statistical parametric maps were generated for each subject. Both conditions (own name and another name) and six realignment parameters were included in the model. The data were high-pass filtered with a cutoff at 128 s and corrected for serial correlations.

To extend findings of the previous study in patients with DOC by Qin et al. (2010), we performed a ROI analysis at the singlesubject level with the contrast own name vs. rest. A second contrast, own name vs. another, was applied to relate findings specifically to self-relatedness. Additionally, a third contrast, another name vs. rest, was selected to investigate deactivation in cortical midline regions.

To show differences between the three levels of consciousness (healthy controls, MCS, and VS/UWS), we performed a group analysis. Subject-specific contrast images were entered into a voxelbased second level analysis. Differences between groups were computed with an ANCOVA with group as a factor. For *post hoc* testing *t*-tests were applied. To address the problem of possible confounds of the two types of scanners and the differences in mean age between groups, we included scanner type and age each as a covariate.

The ROI analysis was performed for each cortical midline region using a small volume with a sphere of 10 mm radius. ROIs for responses to self-related content were chosen according to the study by Qin et al. (2010). In this study, three main ROIs in anterior medial cortical areas were identified for self-related processing validated in two experiments with healthy subjects: the caudal part of the ACC (cACC; 10, 18, 36); the supplementary motor area (SMA; 0, 13, 59); the anterior part of the ACC (aACC; 1, 26, 19). ROIs within the cortical midline structures for deactivation in response to another name were chosen from a large meta-analysis of DMN functional heterogeneity by Laird et al. (2009): precuneus (−2, −56, 50); posterior cingulate cortex (PPC; −5, −52, 25), medial prefrontal cortex (MPFC; −1, 55, 8). Coordinates were selected as specified in both publications and transformed into Montreal Neurological Institute (MNI) space for the group analysis. For single-subject analysis, the inverse of the normalization parameters were used to warp the ROI images to the particular image of each subject. Additionally, a Pearson correlation analysis (twotailed) was performed between the mean contrast estimates from each ROI in all patients and the scores of the CRS-R to relate

brain responses to behavioral responses and cognitive functioning. Correlation analyses were computed with SPSS (version 14; SPSS inc.)<sup>2</sup> . ROI analyses were corrected for FWE at the voxel level with a threshold of *p* < 0.05.

To address the ongoing debate of possible effects of small head motion on group comparisons, we excluded all sessions of subjects with head motion above a defined criterion and ensured that there were no differences between the three groups in any of the motion parameters by calculating a One-way ANOVA with group as a factor (*F* ≤ 1.77, *p* ≥ 0.185).

# **RESULTS**

#### **ROI ANALYSES AT GROUP LEVEL Group results**

In response to the own name vs. rest, significant activation in the control group at a corrected level was found in two ROIs: in the SMA (*t* = 4.92, *p* = 0.007) and in the cACC (*t* = 3.87, *p* = 0.049). The MCS group showed significant activation in the aACC (*t* = 6.36, *p* = 0.033). The VS/UWS group had no significant activation. Uncorrected, significant activation was found in the SMA for the MCS group (*t* = 2.22, *p*uncorr = 0.013) and for the VS/UWS group (*t* = 2.49, *p*uncorr = 0.006).

In response to the own vs. another name, significant activation was found only at the uncorrected threshold level: the control group showed significant activation in the SMA (*t* = 2.58, *p*uncorr = 0.005) and in the cACC (*t* = 2.69, *p*uncorr = 0.008). The MCS group exhibited significant activation in the cACC (*t* = 1.75, *p*uncorr = 0.040).

Significant deactivation was found in the precuneus (*t* = 7.93, *p* < 0.001), in the PCC (*t* = 5.09, *p* = 0.011), and in the MPFC (*t* = 4.29, *p* = 0.024) for the controls at a corrected level. Both patient groups did not show any significant deactivation, neither corrected nor uncorrected.

#### **Differences between groups**

Significant differences between control subjects and patients were evident in processing of the own name and another name (see **Figure 1**).

Differences in response to own name vs. rest were significant in the SMA between healthy controls and patients in MCS (*t* = 3.53, *p* = 0.006) and between controls and patients in VS/UWS (*t* = 2.94, *p* = 0.030). Comparing MCS with VS/UWS, differences were significant in the aACC (*t* = 3.19, *p* = 0.050), and at an uncorrected threshold level in the cACC (*t* = 2.95, *p*uncorr = 0.003).

In response to the own name vs. another, differences were significant in the SMA between control subjects and MCS (*t* = 3.04, *p* = 0.023). Uncorrected, additional significant differences were found in the cACC for controls vs. MCS (*t* = 1.77, *p*uncorr = 0.038) and for controls vs. UWS (*t* = 2.53, *p*uncorr = 0.008).

Differences in deactivation were significant between controls and MCS in the precuneus (*t* = 5.57, *p* < 0.001), in the PCC (*t* = 4.46, *p* = 0.002), and in the MPFC (*t* = 4.57, *p* = 0.002). Between controls and VS/UWS differences were significant in the

<sup>2</sup>www.spss.com

precuneus (*t* = 6.75, *p* < 0.001), in the PCC (*t* = 4.16, *p* = 0.005), and in the MPFC (*t* = 3.89, *p* = 0.009). There were no significant differences between the patient groups neither at an uncorrected threshold level nor corrected for multiple comparisons.

#### **ROI ANALYSES AT SINGLE-SUBJECT LEVEL**

Almost all of the control subjects, showing activation in response to the own name in one or more ROIs, deactivated in response to another name in at least one of the three ROIs except for two subjects who only showed significant activation in the SMA. **Figure 2** displays four healthy control subjects showing responses in the selected ROIs. Four controls deactivated in one or more of the corresponding ROIs without responding to the own name. One patient in MCS showed activation in the aACC but no deactivation. Additionally, three patients with VS/UWS showed activation in one ROI (two in the SMA; one in the cACC and aACC) but

**activation in response to the own name vs. rest, (B) significant activation in response to the own name vs. another name, and (C) significant**

**deactivation in response to another name vs. rest; for display purposes, results are thresholded at p** < **0.001 at the whole brain level, uncorrected for multiple comparisons**.

also no deactivation. Most of the control subjects exhibiting activation in response to the own name showed additional significant higher activation in response to the own name when directly compared to another name. Only one patient showed higher activation in response to the own name vs. another but without responding to the own name vs. rest, however. See **Table 2** for detailed information.

#### **ADDITIONAL ANALYSES**

Correlations between the behavioral scores of the CRS-R and responses to the own name were significant in the aACC (*r* = 0.39, *p* = 0.043). There were no significant correlations between the CRS-R scores and responses to own vs. another name in any anterior region (cACC: *r* = 0.09, *p* = 0.670; aACC: *r* = 0.37, *p* = 0.055; SMA: *r* = 0.01, *p* = 0.978). The correlation between the scores and deactivation in response to another name were not significant (precuneus: *r* = −0.37, *p* = 0.056; PCC: *r* = −0.15, *p* = 0.46; MPFC: *r* = −0.15, *p* = 0.467). **Figure 3** displays all correlations.

To assess the relation between activation in response to the own name in general and response to self-related content in particular, Yates' chi-square goodness of fit test was calculated assessing the number of subjects showing activation in response to the own name and to the own name vs. another in at least one ROI compared to those responding to only one of the contrasts or none [for the controls, χ 2 (1) = 6.97, *p* = 0.008, and for the patients, χ 2 (1) = 1.02, *p* = 0.313].

To exclude the possibility that a lack of activation in anterior midline regions is only due to a general absence of auditory processing in lateral temporal regions, we performed another Yates' chi-square goodness of fit test for the patients, χ 2 (1) = 0.05, *p* = 0.818.

# **DISCUSSION**

In this study, the brain response of 27 patients with DOC during self-referential processing was investigated and compared to deactivation in regions of the DMN.

At group level, we found significant activation of anterior midline regions in response to the own name in healthy controls and in one of the ROIs selected (aACC) in the group of subjects showing minimal signs of consciousness. In this region, we also found significant differences between both patient groups. Correspondingly, the degree of behavioral responsiveness in patients was related to the activation level in the aACC. These findings are in line with the study by Qin et al. (2010) which demonstrated that the ACC is involved in linking the self and consciousness.

In contrast to the study by Qin et al. (2010) though, a minority of patients demonstrated activation in response to the own name. Only 1 of the 9 MCS patients and 3 of the 18 VS/UWS patients showed a response in the selected ROIs. The possibility that lack of activation of the ACC may be due to a general lack of auditory processing can be excluded since there was no association between lack of activation in anterior midline regions and lack of activation in lateral temporal areas in patients.

Furthermore, the correlation between the scores of the CRS-R and the contrast estimates extracted from each ROI was only very weak in the ACC while in the population investigated by Qin et al. the correlation was very strong. These differences are an important finding because they demonstrate the high variability in patients with severe head injury perhaps due to the differences in cause, location, and dimension of the injuries. This corresponds with a previous study demonstrating that the etiology may influence brain responses stronger than the degree of consciousness (Fischer et al., 2010). Especially when investigating such a small **Table 2 | Significant activation in response to the own name and to the own name vs. another in regions of interest at the single-subject level; t-values are shown corrected for family-wise error at voxel level with p** < **0.05; CON, controls; MCS, minimally conscious state;VS/UWS, unresponsive wakefulness syndrome; cACC, caudal part of the anterior cingulate cortex; aACC, anterior part of the anterior cingulate cortex; SMA, supplementary motor area; PREC, precuneus; PCC, posterior cingulate cortex; MPFC, medial prefrontal cortex.**


number of patients as in the study by Qin et al. (four MCS and seven VS/UWS), this may be of particular relevance. Apart from that, it is important to note that we did not use a block-design to present the stimuli which may contribute to the reduced responsiveness. We also used a sphere of 10 mm for all ROIs. The size and form of the ROIs may influence the results as well.

A limitation of the study by Qin et al. (2010) is that they did not implement a control condition for the patients. To relate the activation observed in patients to self-referential processing directly, we included the contrast own name vs. another name in our analysis. Comparing the groups revealed significant lower responsiveness for patients to self-related stimuli in the cACC and SMA which is in line with the findings by Qin et al. But when examining the results at a single-subject level, it becomes evident that responses to the own name go along with responsiveness to self-relatedness only in healthy subjects and not in patients. Moreover, there are no differences between the patient groups when comparing self-related to non-self-related content. Consistently, the activation of the aACC in the MCS group did not exceed the threshold for correction of multiple comparisons when directly associated with self-referential processing (own name vs. other). Thus, the observed responses to the own name in the selected ROIs may not necessarily be due to processing of self-related content in patients with severe head injury.

Another aim of this study was to find further indication for conscious processing of self-relatedness in anterior midline regions. While our findings endorse the conclusion of Qin et al. (2010)that sub-regions of the ACC are linking self and behavioral responsiveness to some extent, this link does not necessarily rely on conscious processing. Although the activation in response to the own name was related to the behavioral responsiveness of the patients in sub-parts of the ACC, the findings overall do not provide evidence for a direct association with consciousness. There were significant differences in deactivation between the control group and the patient groups in all three selected ROIs. Deactivation in regions of the DMN is present in tasks requiring higher cognition and attention-focusing (Shulman et al., 1997b; Greicius and Menon, 2004). None of the responding patients were able to interrupt ongoing internal processes to focus attention which would have been a further indication for conscious processing. None of the responding patients differentiated between the own name and another name. Consistently, the patient groups did not differ in their response to the own name compared to another. Moreover, the correlation between behavioral responsiveness and activation in response to the own name, as becomes evident from **Figure 3**, was very weak. The differences between the patient groups probably rather reflect the impairment of cognitive processing in general than the degree of conscious processing of the stimuli. The impact of brain injury seems to interfere with selfrelated processing in anterior midline regions to a similar extent as it does with processes of other higher association areas going along with deficits in consciousness (e.g., Di et al., 2007). To further prove this suggestion, it might be useful to compare stimuli processing in the ACC to processing in other brain areas, such as the auditory cortex.

Interestingly, the SMA demonstrated the strongest responses in healthy controls and the strongest deficits in processing of selfreferential stimuli in patients. This area within the SMA (or the posterior part of the medial frontal cortex) is also known as a region involved in task control and attention monitoring (Amodio and Frith, 2006). An explanation might be that the own name with its self-related content in comparison to another name is much more involved in processes of attention which are highly affected in patients.

It is important to note that not all controls responding to the own name in the ROI analysis showed deactivation. Two of the control subjects activated in the SMA but did not deactivate in any of the frontal or posterior regions within the DMN.

# **REFERENCES**


233–238. doi:10.1001/archneur.61. 2.233


Furthermore, not all healthy controls responded to the own name in anterior midline regions. However, this is not a very exceptional finding since previous EEG studies also found a high variability in responses to the own name at single-subject level (Kotchoubey et al., 2004; Holler et al., 2011).

A limitation of this study is that consciousness is sufficient but not necessary for deactivation of the DMN and that the absence of deactivation does not necessarily imply an absence of consciousness. Moreover, the participants listened to names instead of sentences as used in the previous study (Crone et al., 2011), which does not include processing of semantic knowledge. Therefore, these conclusions are limited to interpretation and further studies are required to confirm these findings.

In summary, this investigation demonstrates the high variability of responsiveness in severe brain injury and the need for replications in large patient populations. Additionally, it provides further indications that processing of self-related stimuli such as the own name in anterior midline regions does not necessarily reflect a conscious response to external stimuli in the sense of understanding and differentiating. While almost all of the conscious subjects responding to the own name showed higher activation to self-referential stimuli and demonstrated additional deactivation in medial posterior and frontal regions, none of the responding subjects with impaired consciousness did so. Although processing of self-related content in the ACC seems to require a certain level of cognitive functioning, it is questionable whether activation in response to self-related content in cortical midline regions directly reflects conscious processing. Instead, the observed deficits in patients may rather be associated with alterations of network structures which interfere with higher cognitive processing in general (see Corbetta, 2012 for review) and are additionally accompanied by a breakdown of consciousness.

# **ACKNOWLEDGMENTS**

This work was supported by the Jubiläumsfonds of the National Bank of Austria (grant number 14201; 13643); and the Scientific Funds of the Paracelsus Medical University (grant number E-10/12/062-KRO).


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Mazzini, L., Zaccala, M., Gareri, F., Giordano, A., and Angelino, E. (2001). Long-latency auditoryevoked potentials in severe traumatic brain injury. *Arch. Phys. Med. Rehabil.* 82, 57–65. doi:10.1053/ apmr.2001.18076

Mitchell, J. P., Banaji, M. R., and Macrae, C. N. (2005). The link between social cognition and self-referential thought in the medial prefrontal cortex.*J. Cogn. Neurosci.* 17, 1306–1315. doi:10.1162/0898929055002418


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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 30 April 2013; accepted: 06 August 2013; published online: 26 August 2013.*

*Citation: Crone JS, Höller Y, Bergmann J, Golaszewski S, Trinka E and Kronbichler M (2013) Self-related processing and deactivation of cortical midline regions in disorders of consciousness. Front. Hum. Neurosci. 7:504. doi: 10.3389/fnhum.2013.00504*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Crone, Höller, Bergmann,Golaszewski,Trinka and Kronbichler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Looking for the self in pathological unconsciousness

#### **Athena Demertzi <sup>1</sup>\*, Audrey Vanhaudenhuyse<sup>1</sup> , Serge Brédart <sup>2</sup> , Lizette Heine<sup>1</sup> , Carol di Perri <sup>3</sup> and Steven Laureys <sup>1</sup>**

<sup>1</sup> Coma Science Group, Cyclotron Research Center and Neurology Department, University of Liège, Liège, Belgium

<sup>2</sup> Department of Psychology, Behavior, and Cognition, University of Liège, Liège, Belgium

<sup>3</sup> Department of Neuroradiology, National Neurological Institute C. Mondino, Pavia, Italy

#### **Edited by:**

Pengmin Qin, Univeristy of Ottawa Institute of Mental Health Research, Canada

#### **Reviewed by:**

Alexander Fingelkurts, BM-Science Brain & Mind Technologies Research Centre, Finland Andrew Fingelkurts, BM-Science Brain & Mind Technologies Research Centre, Finland Pawel Tacikowski, Karolinska Institute, Sweden

#### **\*Correspondence:**

Athena Demertzi, Coma Science Group, Cyclotron Research Center and Neurology Department, University of Liège, Allée du 6 août no 8, Sart Tilman B30, 4000 Liège, Belgium e-mail: a.demertzi@ulg.ac.be

There is an intimate relationship between consciousness and the notion of self. By studying patients with disorders of consciousness, we are offered with a unique lesion approach to tackle the neural correlates of self in the absence of subjective reports. Studies employing neuroimaging techniques point to the critical involvement of midline anterior and posterior cortices in response to the passive presentation of self-referential stimuli, such as the patient's own name and own face. Also, resting state studies show that these midline regions are severely impaired as a function of the level of consciousness. Theoretical frameworks combining all this progress surpass the functional localization of self-related cognition and suggest a dynamic system-level approach to the phenomenological complexity of subjectivity. Importantly for non-communicating patients suffering from disorders of consciousness, the clinical translation of these technologies will allow medical professionals and families to better comprehend these disorders and plan efficient medical management for these patients.

**Keywords: consciousness, self, neuroimaging, disorders of consciousness, default mode network, external awareness**

# **(SELF) CONSCIOUSNESS IN NON-COMMUNICATING CONDITIONS**

The scientific study of consciousness dictates that there is an intimate relationship between the mind and the brain (Feinberg, 2000; John, 2002; Freeman, 2007; Tononi and Laureys, 2009; Fingelkurts et al., 2013). Nevertheless, besides several attempts to define it, consciousness remains a difficult term to describe and different people may think differently about it (Demertzi et al., 2009). Here, we will define consciousness in an operational manner, namely consciousness is what is lost during dreamless sleep (Tononi, 2004). As such, consciousness is a matter of both waking states and experience, so that the less awake we get the less aware we become of our surroundings and ourselves.

Based on this definition, patients in coma are not conscious because they cannot be awakened. The linear relationship between wakefulness and awareness is violated in cases of severely braindamaged patients who are in a vegetative state (VS) and minimally conscious state (MCS). Indeed, patients is VS, also coined as unresponsive wakefulness syndrome (UWS; Laureys et al., 2010), maintain awaking periods as evidenced by eye-opening and they will never respond to any visual,somatosensory,or auditory stimulation indicative of preserved awareness (Jennett and Plum, 1972). On the other hand, patients in MCS show fluctuating signs of awareness and non-reflex behaviors, such as visual pursuit and command following (Giacino et al., 2002). Importantly, in both clinical conditions patients remain unable to communicate with their environment in a functional manner. In the absence of subjective reports, how can one know whether patients in VS/UWS and MCS experience something and what these experiences are? In

other words, can one claim that these patients retain a type of "core consciousness," which provides them with a sense of self about here and now? (Damasio and Meyer, 2009). We think that the study of patients with disorders of consciousness offers a unique lesion approach to tackle the necessary neural correlates of selfconsciousness. Our rationale lies on the argument that since clinical diagnosis shows that patients hold no subjective experience, the absence of subjective identity will be eventually reflected in patients' brain function. As these patients are not able to communicate or show high-level cognitive function, we will here refer to self-consciousness as to its basic expression. In other words, as selfdetection, namely when an organism can respond to stimuli with which is directly implicated or modify its behavior in ways which imply awareness of its own actions (Zeman, 2001). Accordingly, the employed experimental paradigms refer to the administration of self-referential stimuli (patients' own name and own face) and the subsequent measure of brain responses to these stimuli with neuroimaging and electrophysiological techniques. The excellent spatial resolution which is offered by functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), permits to better "localize" self-referential brain activity. Therefore, we will here focus on studies employing these neuroimaging methods to study residual self-consciousness in patients with disorders of consciousness. To date, such functional neuroimaging studies point to the critical recruitment of anterior and posterior midline cerebral areas in experimental paradigms employing self-referential stimuli. Activation of these midline regions is further observed during resting state conditions in healthy volunteers. This has led to the suggestion of a link between resting state activity

and unconstraint self-related mentation. We will review these studies in patients and healthy controls, discuss the involvement of midline areas to the notion of self in patients and will propose that self-related cognition might be a matter of a system-level dynamic activity rather than activation of specific brain areas.

# **ASSESSING SELF-CONSCIOUSNESS IN NON-COMMUNICATING PATIENTS**

Clinicians are offered with various clinical scales to detect sings of awareness at the bedside (Majerus et al., 2005). The Coma Recovery Scale-Revised (Giacino et al., 2004) is one of the most sensitive tool to diagnose and differentiate between patients in VS/UWS and MCS because it assesses all the defining criteria for MCS, such as visual pursuit (Seel et al., 2010). Nonetheless, it is not only a certain behavior that needs to be detected, but the way this is assessed seems to be equally important. For example, when visual pursuit was tested by means of a moving object, a moving person, and a moving mirror, more patients tracked their image in the mirror compared the other two stimuli and were hence considered as in a MCS (Vanhaudenhuyse et al., 2008). Similarly, to score sound localization with the Coma Recovery Scale-Revised, patients need to orient their head or eyes toward the source of the sound. When the patients' own names were used, more oriented their head or eyes toward the examiner compared to the meaningless sound of a ringing bell (Cheng et al., 2013). These studies imply that selfreferential stimuli are more effective to explore patients' responsiveness and can influence the diagnostic process (also, see Laureys et al., 2007). To what degree, however, can one claim that these paradigms also reflect the, indirect, assessment of residual selfconsciousness in this non-communicating clinical population?

One way to approach the answer is to measure patients' brain responses and activation during sensitive experimental manipulations and compare them with that of healthy controls. If the cerebral pattern is indistinguishable between the two groups, then one has good reasons to believe that the extracted statistical maps reflect the same construct (Owen, 2013). Naturally, there are emerging legitimate concerns about the degree of confidence one can have on functional neuroimaging results, especially in the absence of subjective reports (e.g., Fins and Schiff, 2010). In addition, our limited understanding of the dynamic neural complexity underlying consciousness and its resistance to quantification in the absence of communication (Seth et al., 2008) makes it difficult to establish strong claims about self-consciousness in non-communicating patients. Nevertheless, the use of these technologies have shed light on the gray zones between the different clinical entities of consciousness and have revealed that not all patients can be considered unresponsive (Laureys and Boly, 2008; Gantner et al., 2012). For example, fMRI has been used to assist the diagnosis of patients with disorders of consciousness (Coleman et al., 2009), to detect preserved awareness in behaviorally unresponsive patients (Owen et al., 2006), and even to communicate with them (Monti et al., 2010).

Due to the difficulty to control voluntary eye-opening of patients, most neuroimaging studies employing self-referential stimuli restrict to the auditory modality (**Table 1**). In a PET study with one patient in MCS, the patient's own name was presented next to baby cries and meaningless noise (Laureys et al., 2004). Passive listening to the own name recruited the activation of midline areas, such as precuneus and anterior cingulate/mesiofrontal cortex next to lateral parietal areas including language-related regions, such as Broca's and Wernicke's. Another *n* = 1 study with a patient in VS/UWS utilizing fMRI also showed that passive listening to the own name compared to other names, encompassed the activation of the medial prefrontal cortex bilaterally in parallel to temporoparietal and superior frontal cortices (Staffen et al., 2006). Including more patients (*n* = 11), it was shown that all four patients in MCS and six patients in VS/UWS showed cerebral responses to their own names either in the anterior cingulate cortex (ACC) or in the caudal part of the ACC or the supplementary motor area (predefined regions based on brain responses of healthy controls) (Qin et al., 2010). Interestingly, those two patients in VS/UWS who exhibited activity in the caudal ACC evolved to a MCS at a 3-month follow up. Similarly, two patients in VS/UWS when listening to their own name showed cerebral activation extending to associative auditory cortex and also recovered to MCS (Di et al., 2007). Such brain activations, however, are atypical of the VS/UWS. Indeed, it has been shown that auditory processing of simple stimuli in VS/UWS refers to the activation of only auditory primary cortices whereas hierarchically higher-order multi-modal association areas are not activated (Laureys et al., 2000; Boly et al., 2004). Although caution should be paid on the accurate behavioral evaluation of these patients with standardized tools, like the Coma Recovery Scale-Revised (**Table 1**), there are cases of unresponsive patients where functional neuroimaging can precede the clinic (e.g.,Owen et al., 2006). Taken together, these studies suggest that when activity of the anterior midline areas is recruited using the own name paradigm, this can work as prognostic marker (for a review, see Di et al., 2008).

Apart from activation studies utilizing self-referential stimuli, increasing attention has been paid to spontaneous brain activity and its significance to self-related cognition. During resting state, a set of brain areas encompassing precuneus, medial prefrontal cortex and bilateral temporo-parietal junctions have been shown to work by default, when subjects do not perform any task (Gusnard and Raichle, 2001). This default mode network (DMN) of areas in healthy controls has been related to internally oriented cognitive content, such as self-referential or social cognition, mind-wandering, and autobiographical memory recall (e.g., D'Argembeau et al., 2005; Mason et al., 2007; Buckner et al., 2008; Schilbach et al., 2008; Vanhaudenhuyse et al., 2011). Such intrinsic cerebral activity also seems to be implicated in consciousness processes. For example, in brain death, where all brainstem reflexes are lost parallel to continuous cessation of respiration, functional connectivity in the DMN is absent (Boly et al., 2009), or attributed merely to motion artifacts (Soddu et al., 2011). Coma patients show no identifiable fMRI DMN connectivity and in those patients where such connectivity can be detected may indicate subsequent recovery of consciousness (Norton et al., 2012). In patients with disorders of consciousness, such fMRI DMN connectivity is partially preserved yet severely disrupted, showing consciousness level-dependent decreases when moving from healthy controls to patients in MCS, VS/UWS, and coma (Vanhaudenhuyse et al., 2010). Interestingly, EEG studies have corroborated these findings: it has been shown that the strength of DMN EEG synchrony was smallest or even absent in patients in VS/UWS, intermediate in patients in MCS, and highest in healthy fully self-conscious


**Table 1 | Studies showing brain responses to the presentation of self-referential stimuli in patients in vegetative state/unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) by means of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) techniques (\*indicates prognostic value).**

ACC, anterior cingulate cortex; cACC, caudal part of the anterior cingulate cortex; SMA, supplementary motor area.

subjects (Fingelkurts et al., 2012). Similarly, brain metabolism in these midline structures is severely disrupted in patients in VS/UWS and MCS compared to patients who have emerged from the MCS or are in a locked-in syndrome (**Figure 1**; Thibaut et al., 2012). It has been further proposed that deactivation of the DMN is supposed to reflect interruptions of introspective processes. Such investigation in patients showed that, compared to healthy controls, deactivation in medial regions of the DMN was absent in patients in VS/UWS and reduced in patients in MCS (Crone et al., 2011). Taken together, studies of spontaneous activity in patients suggest that changes in the DMN functional connectivity could suggest modified self-related conscious mentation. Indeed, it has been suggested that in normal waking conditions, resting state activity in the posterior cingulate, and frontal areas accounts for self-referential thoughts (Whitfield-Gabrieli et al., 2011; Fingelkurts et al., 2012). Therefore, it could be inferred that decreased connectivity in these midline regions of the DMN reflects, at least to certain degree, restricted abilities for self-referential processing in patients with disorders of consciousness.

#### **THE SELF AS A PRODUCT OF A DYNAMIC SYSTEM APPROACH**

Since the early studies of resting state, it has been suggested that the brain's baseline activity can be organized in two brain networks showing anticorrelated activity to each other: an "intrinsic" and an "extrinsic" network (Fox et al., 2005; Fransson, 2005; Golland et al., 2007; Tian et al., 2007). The "intrinsic" network coincides

**FIGURE 1 | Metabolic activity in medial precuneus (MP) and mesiofrontal (MF) cortex is severely impaired in patients with disorders of consciousness, such as in vegetative state/unresponsive wakefulness syndrome and minimally conscious state**. Of note is that patients who have emerged from the minimally conscious state (who yet experience confusion and amnesia syndromes) show metabolic dysfunction only in the posterior cingulate and adjacent retrosplenial cortex but not in the lateral frontoparietal network (see text). Finally, fully conscious yet severely paralyzed patients with locked-in syndrome do not show metabolic impairment in any of these areas, suggesting a critical involvement of midline regions in supporting self-related cognition (figure adapted from Thibaut et al., 2012).

with the DMN and is involved in the same cognitive processes as the DMN. The "extrinsic" system encompasses lateral frontoparietal areas resembling the brain activations during goal-directed behavior and it has been linked to cognitive processes of external sensory input, such as somatosensory (e.g.,Boly et al., 2007), visual (e.g., Dehaene and Changeux, 2005), and auditory (e.g., Brunetti et al., 2008). Previous studies showed that these two systems are of a competing character in the sense that they can disturb or even interrupt each other (e.g., Tian et al., 2007). Such anticorrelated pattern is also illustrated in activation studies on motor performance (Fox et al., 2007), perceptual discrimination (Sapir et al., 2005), attentional lapses (Weissman et al., 2006), and somatosensory perception of stimuli close to somatosensory threshold (Boly et al., 2007).

We have recently proposed that these two systems may account for the phenomenological complexity of awareness. In particular, it is proposed that awareness, or the contents of consciousness, can be reduced to two components, namely the "external" awareness or everything we perceive through our senses (what we see, hear, feel, smell, and taste) and "internal" awareness or stimulusindependent thoughts (Demertzi et al., 2013). Interestingly, the switch between the external and internal milieu was found not only to characterize overt behavioral reports but also had a cerebral correlate (Vanhaudenhuyse et al., 2011). More particularly, it was shown that behavioral reports of internal awareness were linked to the activity of midline anterior cingulate/mesiofrontal areas as well as posterior cingulate/precuneal cortices. Conversely, subjective ratings for external awareness correlated with the activity of lateral fronto-parieto-temporal regions. These findings highlight that the anticorrelated pattern between the internal and external awareness system is of functional relevance to conscious cognition. Indeed, in an altered conscious state like hypnosis, where subjects report awareness alterations but remain fully responsive, hypnosisrelated reductions in functional connectivity were shown in the external awareness system parallel to subjective ratings of increased sense of dissociation from the environment and reduced intensity of thoughts about external events (Demertzi et al., 2011). Similar reductions in external awareness systems have been also shown for non-responsive conditions, such as deep sleep and anesthesia (for a review, see Heine et al., 2012).

Analysis of metabolic activity obtained in VS/UWS patients compared to healthy controls or comparisons with recovery of awareness (i.e., within-subject), have highlighted the critical role of a widespread fronto-temporo-parietal associative cortical network (Thibaut et al., 2012). Recent PET data indicate that recovery of MCS patients seems to be accompanied by a right-lateralized recovery of the external awareness network whereas the presence of command following, defining the MCS plus (Bruno et al., 2011), classically parallels the recovery of the dominant left-lateralized language network (Bruno et al., 2012). Similar results have been observed in slow wave sleep and general anesthesia (for review, see Boveroux et al., 2008). Interestingly, these findings are also confirmed in transient dissociative states of unresponsive wakefulness, such as absence seizures, complex partial seizures, or sleepwalking – all characterized by preserved automatic reflex motor behavior in the absence of response to commands and showing transient impaired activity in these fronto-temporo-parietal associative areas (Laureys, 2005; Blumenfeld, 2012).

According to a suggested framework taking the external and internal awareness systems into account, two complementary states of system imbalance are possible, where one system can be in a hyperfunctional state, while the other is hypoactive. Extrinsic system hyperfunction is expected to lead to a state of total sensorimotor absorption or "lost self." In contrast, intrinsic or default system hyperfunction is expected to lead to a state of complete detachment from the external world. A state where both extrinsic and intrinsic systems are hypofunctional is predicted to lead to markedly impaired consciousness as seen in disorders of consciousness (Soddu et al., 2009). A more recent proposal, adopting a similar system-level approach, points to the functional separation of the dorsal and ventral subcomponents of the posterior cingulate cortex (PCC): the ventral PCC appears to be highly integrated within the DMN, and is involved in internally directed cognition (e.g., memory retrieval and planning) whereas the dorsal PCC shows a highly complex pattern of connectivity, with prominent connections to the frontal lobes (Leech et al., 2012). According to the suggested model, differential regional activity can be explained by considering the arousal state, the milieu of attention (internal vs. external) and the breadth of attention (narrow vs. broad) (Leech and Sharp, 2013). The model proposes that through its interactions with the prefrontal cortex, the dorsal PCC is involved in controlling attentional focus. Hence, interactions of these PCC sub-regions with other intrinsic connectivity networks are then involved in shifting the balance of attention along an internal/external and broad/narrow dimension (Leech and Sharp, 2013).

Taken together these studies indicate that DMN and anticorrelated external awareness system activity underlies (at least partially) conscious ongoing mentation. It should be mentioned that fMRI anticorrelations were previously subject to debate in the literature. It has been argued, for instance, that fMRI functional anticorrelations are nothing more than noise in the signal due to regression of the brain's global activity during data preprocessing (Anderson et al., 2011). Other data, however, suggest that the anticorrelations persist both with and without global signal regression, suggesting some underlying biological origins for this anticorrelated pattern (Fox et al., 2009; Chai et al., 2012). We would agree with the latter evidence which is supported by studies in unconscious conditions, such as anesthesia, sleep, and in unresponsive patients (Boly et al., 2009) where these anticorrelations generally reduce or even disappear, accounting for their functional contribution to conscious cognition.

# **CONCLUSION**

Neuroimaging activation and resting state studies indicate an indirect measure of self-related cognition encompassing midline and lateral frontoparietal areas. Furthermore, such studies have recently shown a much more complex, dynamic, and multifaceted architecture of brain functional connectivity in the emergence of consciousness than previously thought. Importantly for noncommunicating patients suffering from disorders of consciousness, such neuroimaging measurements are of medical and ethical importance (Jox et al., 2012). What remains to be determined is the clinical translation of these technologies which will allow medical professionals and families to better comprehend these disorders, plan efficient medical management, and in a far reaching perspective, to acquire new opportunities to restore their brain functions.

# **ACKNOWLEDGMENTS**

This work was supported by the Belgian National Funds for Scientific Research (FNRS), tinnitus Prize 2011, the European Commission, the James McDonnell Foundation, the European Space Agency, Mind Science Foundation, the French Speaking Community Concerted Research Action, the Belgian Interuniversity Attraction Pole, the Public Utility Foundation

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"Université Européenne du Travail," "Fondazione Europea di Ricerca Biomedica," and the University Hospital of Liège. Athena Demertzi and Audrey Vanhaudenhuyse are FNRS Postdoctoral Researchers, Serge Brédart is a Full Professor of Cognitive Psychology at the University of Liège, Lizette Heine is FNRS Research fellow and Steven Laureys is FNRS Research Director.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 03 June 2013; accepted: 16 August 2013; published online: 03 September 2013.*

*Citation: Demertzi A, Vanhaudenhuyse A, Brédart S, Heine L, di Perri C and Laureys S (2013) Looking for the self in pathological unconsciousness. Front. Hum. Neurosci. 7:538. doi: 10.3389/fnhum.2013.00538*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Demertzi,Vanhaudenhuyse, Brédart, Heine, di Perri and Laureys. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# The degree of early life stress predicts decreased medial prefrontal activations and the shift from internally to externally guided decision making: an exploratory NIRS study during resting state and self-oriented task

#### **Takashi Nakao<sup>1</sup>\* † ,Tomoya Matsumoto<sup>2</sup>† , Machiko Morita<sup>3</sup> , Daisuke Shimizu<sup>3</sup> , ShinpeiYoshimura<sup>4</sup> , Georg Northoff <sup>5</sup> , Shigeru Morinobu<sup>2</sup> ,Yasumasa Okamoto<sup>2</sup> and ShigetoYamawaki <sup>2</sup>**

<sup>1</sup> Department of Psychology, Graduate School of Education, Hiroshima University, Hiroshima, Japan

2 Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan

<sup>3</sup> Faculty of Medicine, Hiroshima University, Hiroshima, Japan

<sup>4</sup> Faculty of Psychology, Otemon Gakuin University, Osaka, Japan

5 Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada

#### **Edited by:**

Niall W. Duncan, University of Ottawa, Canada

#### **Reviewed by:**

Gabriel José Corrêa Mograbi, UFMT – Federal University of Mato Grosso, Brazil Stefano Innocenzo Di Domenico, University of Toronto Scarborough, Canada

#### **\*Correspondence:**

Takashi Nakao, Department of Psychology, Graduate School of Education, Hiroshima University, 1-1-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8524, Japan e-mail: takana818@gmail.com

†Takashi Nakao and Tomoya Matsumoto have contributed equally to this work.

Early life stress (ELS), an important risk factor for psychopathology in mental disorders, is associated neuronally with decreased functional connectivity within the default mode network (DMN) in the resting state. Moreover, it is linked with greater deactivation in DMN during a working memory task. Although DMN shows large amplitudes of very lowfrequency oscillations (VLFO) and strong involvement during self-oriented tasks, these features' relation to ELS remains unclear. Therefore, our preliminary study investigated the relationship between ELS and the degree of frontal activations during a resting state and self-oriented task using near-infrared spectroscopy (NIRS). From 22 healthy participants, regional hemodynamic changes in 43 front-temporal channels were recorded during 5 min resting states, and execution of a self-oriented task (color-preference judgment) and a control task (color-similarity judgment). Using a child abuse and trauma scale, ELS was quantified. We observed that ELS showed a negative correlation with medial prefrontal cortex (MPFC) activation during both resting state and color-preference judgment. In contrast, no significant correlation was found between ELS and MPFC activation during color-similarity judgment. Additionally, we observed that ELS and the MPFC activation during color-preference judgment were associated behaviorally with the rate of similar color choice in preference judgment, which suggests that, for participants with higher ELS, decisions in the color-preference judgment were based on an external criterion (color similarity) rather than an internal criterion (subjective preference). Taken together, our neuronal and behavioral findings show that high ELS is related to lower MPFC activation during both rest and self-oriented tasks. This is behaviorally manifest in an abnormal shift from internally to externally guided decision making, even under circumstances where internal guidance is required.

**Keywords: internally guided decision making, very low-frequency fluctuations, task positive network, eyes-closed resting state, lateral prefrontal cortex, cortisol, mediation analysis, moderation analysis**

#### **INTRODUCTION**

By definition, early life stress (ELS) derives from adverse experiences during childhood and adolescence including physical, sexual, and maltreatment abuse (Brown et al., 2009). Demonstrably, ELS is associated with deficits in cognitive and affective function (Pechtel and Pizzagalli, 2011) and is a significant risk factor for mood and anxiety disorders later in life (Heim and Nemeroff, 2001; Heim et al., 2010; Schmidt et al., 2011). Several lines of evidence have indicated that ELS elicits structural changes in the brain. For example, reports of some animal studies have described that ELS results in abnormally increased synaptic density in the infralimbic cortex (Ovtscharoff and Braun, 2001), and decreased dendritic

spine density in the prefrontal cortex (PFC) (Murmu et al., 2006). Reports of human neuroimaging studies have described that ELS is associated with reduced gray matter volume including that of the PFC (De Bellis et al., 2002; Andersen et al., 2008; Paus et al., 2008; Hanson et al., 2010).

Although few functional neuroimaging studies have addressed the influence of ELS, activations within the default mode network (DMN) are known to be associated with ELS (Burghy et al., 2012; Philip et al., 2013a,b; van der Werff et al., in press; Cisler et al., 2013; Wang et al., in press). The DMN consists mainly of cortical midline structures (Northoff and Bermpohl, 2004; Raichle and Gusnard, 2005) and comprises the medial prefrontal

cortex (MPFC), posterior cingulate cortex, and superior temporal/inferior parietal cortex (Fox et al., 2005; Kim et al., 2010; Qin and Northoff, 2011). The DMN is more active at rest than during goal-directed/externally guided cognitive tasks (Raichle et al., 2001; Buckner et al., 2008). Regions within the DMN show a high degree of functional connectivity during rest (Raichle et al., 2001; Beckmann et al., 2005; Raichle and Snyder, 2007; Buckner et al., 2008). Regarding these features of the DMN, ELS is known to be associated with greater deactivation of DMN during a working memory task (Philip et al., 2013b), and shows decreased functional connectivity within the DMN during a resting state (Burghy et al., 2012; van der Werff et al., in press; Cisler et al., 2013; Wang et al., in press; Philip et al., 2013a).

Neuronally, the DMN can be characterized by large amplitudes of spontaneous slow oscillations during a resting state (Raichle et al., 2001; Fransson, 2005; Zou et al., 2008). Slow oscillations have been observed using measurements of different types, functional magnetic resonance imaging (fMRI; Biswal et al., 1995; Fransson, 2006; Chepenik et al., 2010), electroencephalography (EEG; Horovitz et al., 2008; Helps et al., 2010; Broyd et al., 2011), and near-infrared spectroscopy (NIRS; Obrig et al., 2000; Näsi et al., 2011; Pierro et al., 2012). Slow oscillations from 0.04 to 0.15 Hz are called low-frequency oscillations (LFOs). Even lower frequency oscillations (<0.04 Hz) are designated as very low-frequency oscillations (VLFOs) (Obrig et al., 2000; Näsi et al., 2011). Although the mechanisms underlying the slow oscillations remain unclear, several reports of the literature have described these as neuronal characteristics of psychological personality traits (Kunisato et al., 2011) and psychiatric disorders such as anxiety (Hou et al., 2012) and mood disorders (Chepenik et al., 2010; Wang et al., 2012). Psychiatric disorders have shown high degrees of ELS (Heim and Nemeroff, 2001; Heim et al., 2010; Schmidt et al., 2011). Therefore, one would suspect high ELS to be related to changes in slow oscillations during the resting state. This point, however, remains to be investigated.

In addition to LFOs during the resting state, the DMN shows activation in fMRI during various tasks such as self-reference (Kelley et al., 2002; Northoff et al., 2006), episodic memory retrieval (Buckner et al., 2008), envisioning the future (Szpunar et al., 2007), mentalizing (Gusnard et al., 2001; Amodio and Frith, 2006), and internally guided decision making (Nakao et al., 2012). The DMN is often explained integratively as associated with self-oriented/internally guided psychological processes (Qin and Northoff, 2011; Whitfield-Gabrieli and Ford, 2012). Again, however, no report in the relevant literature has described the association between ELS and DMN activity during self-oriented tasks.

This preliminary study was undertaken to investigate the relations between ELS and the degree of MPFC activations during a resting state and self-oriented task using NIRS. This non-invasive technique uses near-infrared light to evaluate spatiotemporal characteristics of brain function near the brain surface. The use of NIRS enables the detection of spontaneous slow oscillations in oxygenated hemoglobin (oxy-Hb: Obrig et al., 2000). The LFOs and VLFO measured by NIRS are known to be differentiated from other oscillatory phenomena such as heart beat and respiratory cycles (Obrig et al., 2000). The activation of surface regions of MPFC during self-oriented tasks has also been measured using NIRS (Di Domenico et al., 2012).

For the experiment described hereinafter, a child abuse and trauma scale (CATS) (Sanders and Becker-Lausen, 1995) was used to assess ELS. To control the effect of the recent stress level, we used the life event stress scale (LES) (Sarason et al., 1978). Stressful life events are known to affect brain function adversely through elevated cortisol level in the blood which is acutely or chronically caused by the hormonal stress response system: the hypothalamic– pituitary–adrenal (HPA) axis (Numakawa et al., 2013). Therefore, we also measured the blood levels of cortisol to assess whether early and/or recent life stress might elevate cortisol concentrations in the blood, resulting in alteration of PFC activation. We recorded eyes-closed (EC) and eyes-open (EO) resting-state NIRS before conducting cognitive tasks. In self-oriented cognitive and control tasks, color stimulus was used (see **Figure 1A** for example). The same color stimulus and color stimulus pairs were used in both tasks. As a self-oriented task, color-preference judgment (Johnson et al., 2005; Nakao et al., 2013) was used while the color-similarity judgment served as control (Johnson et al., 2005; Nakao et al., 2013) (see **Figure 1A**). We used these tasks for the following three reasons. First, using these tasks, we can differentiate between goal-directed/externally guided and selforiented/internally guided psychological processes (Johnson et al., 2005; Nakao et al., 2013). Although color-similarity judgment requires participants to make a decision based on the external criterion (i.e., color-similarity), color-preference judgments require participants to make a decision based on their own internal criteria. Second, the same color-set is used in both tasks: the effects of stimuli can be well controlled. Third, Johnson et al. (2005) reported that the color-preference judgment activate the DMN including the MPFC [Brodmann area (BA) 9, 10] compared to the color-similarity judgment. The MPFC is the region of interest (ROI) in this study.

## **MATERIALS AND METHODS PARTICIPANTS**

Twenty-two healthy volunteer participants (12 male; age range = 21–27 years, mean age = 22.7 years) were recruited from Hiroshima University. All participants were right-handed, with normal or corrected-to-normal vision. All were free of neurological and psychiatric disorders. To control possible confounding factors to brain activity (Duncan and Northoff, 2012), participants who were habitual drinkers or taking medication were excluded. Participants were not permitted to smoke tobacco from 3 h before the experiment started. Written informed consent was obtained from each participant before the investigation, in line with a protocol approved by the Research Ethics Committee of Hiroshima University. Each participant was paid a small fee for participating.

#### **SELF-REPORT MEASURES**

Early life stress was quantified using a CATS (Sanders and Becker-Lausen, 1995). The CATS is a 38-item questionnaire that measures subjective reports of various forms of childhood physical, sexual, and maltreatment abuse. For each item (e.g., "Did your parents ridicule you?", "Did you ever seek outside help or guidance because of problems in your home?", "Were you expected

to follow a strict code of behavior in your home?"), participants rated how frequently a particular abusive experience occurred to them during their childhood and adolescence, using a scale of 0–4 (0 = never, 4 = always). The CATS score was calculated by summing the ratings after reversing the scores of reverse items. Sanders and Becker-Lausen (1995) reported strong internal consistency (Cronbach's alpha = 0.90) and test–retest reliability (*r* = 0.89) for the total score. Validity was confirmed by demonstrating significant correlation with consequent psychological outcomes such as dissociation, depression, anxiety, difficulties in interpersonal relationships, and victimization, all of which have previously been associated with ELS (Sanders and Becker-Lausen, 1995; Kent and Waller, 1998). Numerous earlier studies have used this scale to assess ELS (e.g., Cohen et al., 2006; Philip et al., 2013b).

In addition to the CATS, we used the LES (Sarason et al., 1978) to assess recent stress levels. For the LES, participants were asked to indicate which of 57 events (e.g., "Death of close friend,""Trouble with in-laws," "Being fired from job") occurred during the prior 12 months and to rate the impact of each event using a seven point scale, ranging from extremely negative (−3) to extremely positive (+3). The LES scores were calculated using summing impact ratings for all events. Sarason et al. (1978) reported significant test–retest reliabilities for the total score (*r* = 0.63 and *r* = 0.64) from the two test–retest reliability studies.

#### **MEASUREMENT OF SERUM CORTISOL**

To assess a possibility that the MPFC activation was altered by stress-elevated cortisol level, we measured cortisol levels in the blood. First, 3 ml venous blood was collected using anticoagulantfree vacuum tubes and kept at room temperature for 1 h with subsequent centrifugation at 2,000 × *g* for 20 min at 4°C. Serum was collected and stored at −80°C until use. Cortisol levels were measured by radioimmunoassay at SRL Corp. (Tokyo, Japan).

#### **RESTING STATES**

After NIRS probe placement, participants were seated on a comfortable chair facing a computer screen in a dark shielded room. Before the experimental tasks, participants performed counterbalanced resting EC and EO baseline periods of 5 min each. Each participant was instructed to relax and allow the mind to disengage during these periods. During the EO resting state, participants were asked to gaze at a fixation cross presented at the center of the computer screen.

#### **COGNITIVE TASK**

After resting-state recording, participants performed cognitive tasks of two types: color-similarity judgment and color-preference judgment. Twenty-four colors were used in both tasks. Three colored squares were presented in each trial (see **Figure 1A** for example). The colored square presented at the upper center was the target color. The squares presented at the lower left and right were choices. The color squares were all 90 × 90 pixels. The similarity of colors was defined by the distance in CIELAB color space in which values L<sup>∗</sup> (light–dark), a<sup>∗</sup> (red–green), and b<sup>∗</sup> (yellow–blue) are shown at right angles to each other to form a three-dimensional coordinate system. One color wheel of the a∗–b<sup>∗</sup> plane was used to select color and to make color sets. Twelve colors were selected from one color wheel at every 30° of difference (see **Figure 1B**).

In both the tasks, color sets of two types (similarity-easy and similarity-difficult sets) were used (see **Figure 1B**). In the similarity-easy set (60 vs. 150°), one target-choice pair was clearly more similar (i.e., the difference between the target and choice was 60°) than another target-choice pair (i.e., the difference between target and choice is 150°). In the similarity-difficult set (90 vs. 120°), the similarities between the target and choices were closer between the two target–choice pairs. All target–choice color pairs were presented once in each of the tasks. The same color sets for 24 trials were used in these two task conditions.

In the color-similarity judgment task, participants were asked to judge which choice was more similar to the target color by pressing the button on the corresponding side. Participants were instructed clearly that the lightness was equal among these three colors. In the color-preference judgment task, participants were asked to judge which color pair (target–choice pair) they prefer. Participants were clearly instructed that no objectively correct answer exists: they must make their own decisions. These tasks were used in previous studies (Johnson et al., 2005; Nakao et al., 2013).

Participants performed eight blocks of six trials of tasks (four blocks per task). The block order was randomized across participants. Each block included a 10 s pre task baseline, 30 s cognitive task, and 20 s post task baseline (see **Figure 1A**). During the cognitive task, each trial began with the presentation of a task indicating a cue ("Similarity" or "Preference") and three black squares indicating the three color square locations. One second later, color stimuli were presented for 4 s. Participants were instructed to press either the left or right button with the corresponding index fingers as quickly and accurately as possible after the stimuli were presented. The reaction time (RT) from the presentation of the color stimuli to the response was recorded. The presentation side of colors and the order of the trials were randomized across participants.

#### **NIRS DATA ACQUISITIONS**

Relative changes in the concentration of oxy-Hb and deoxy-Hb were measured using a multichannel NIRS imaging system (FOIRE-3000; Shimadzu Corp., Japan) using three wavelengths (780, 805, and 830 nm) of infrared light based on Matcher et al. (1995). The data sampling time was 115 ms. The source–detector probes were placed in fronto-temporal regions. The probe set was mounted on a cap for fixation (**Figure 1D**). The lower frontal probes were positioned along the Fp1–Fp2 line according to the international 10–20 system used for electroencephalography. The distance between pairs of source–detector probes was set at 3 cm. Each measuring area between the pairs of source–detector probes was defined as a channel. It is considered that the machine with source–detector spacing of 3 cm measures points at 2–3 cm depth from the scalp (i.e., measurements are taken from the surface of the cerebral cortex; Hock et al., 1997; Toronov et al., 2001; Okada and Delpy, 2003a,b). The exact optical path length was unknown. Therefore, the unit used to measure these values was molar concentration multiplied by length (mM × mm). The 43 measuring points were labeled as ch1–ch43 (see **Figure 1C**). Because of a technical problem, data of three channels (ch25, ch28, and ch41) from eight participants failed to record a signal. Threedimensional locations of the NIRS probe were measured using a Fastrak System (TX-2; Polhemus, USA). Using the MATLAB toolbox NFRI functions<sup>1</sup> , statistical results for each channel were shown on the surface of a standardized brain (Singh et al., 2005).

#### **NIRS ANALYSIS**

The NIRS data analysis was done using software (MATLAB 8.0; The MathWorks Inc., Natick, MA, USA).

#### **Resting-state data**

Resting-state oxy-Hb data were filtered using a low-pass filter of 0.4 Hz. The linear trend caused by drift was removed (Tachtsidis et al., 2004). A Fast Fourier Transform (FFT) was performed on oxy-Hb data EC and EO resting-state data. The Welch technique with a Hanning window of 1024 sample points (117.76 s sliding window) and an overlap of 512 points was used. Power spectral density (mM × mm<sup>2</sup> /Hz) was calculated for each channel over the range of 0.02–0.15 Hz. Subsequently, the band-limited power in the following two frequency bands was calculated based on previous studies (Obrig et al., 2000; Tachtsidis et al., 2004; Näsi et al., 2011; Pierro et al., 2012): VLFO (0.02–0.04 Hz) and LFOs (0.04–0.15 Hz).

#### **Cognitive task data**

Oxy-Hb data during cognitive tasks were filtered using a low-pass filter of 0.2 Hz. The global drift was removed by application of a wavelet minimum description length (MDL) detrending algorithm (Jang et al., 2009) implemented in the MATLAB toolbox NIRS-SPM<sup>2</sup> (Ye et al., 2009). We specifically examined ∆oxy-Hb, which is the most sensitive parameter of cerebral blood flow (Strangman et al., 2002). Many previous NIRS studies calculated a *z* score in each recording channel for comparison among participants (Minagawa-Kawai et al., 2002; Takeda et al., 2007; Shimoda et al., 2008; Matsuzawa, 2012). For this study, the *z* score at each channel was calculated as follows: the mean ∆oxy-Hb value during the 30 s cognitive task vs. that during a 10 s pre task baseline period was divided by the standard deviation (SD) of ∆oxy-Hb during the pre task baseline. The *z* scores in each task condition were averaged across blocks.

#### **CORRELATION ANALYSIS**

Pearson correlation coefficients were calculated among possible combinations of our data (i.e., CATS score, LES score, cortisol levels, VLFO and LFO power spectrum density during EC and EO resting state of each NIRS channel, *z* scores for color-similarity judgment, and color-preference judgment of each NIRS channel, behavioral data during the two cognitive tasks). Outliers of each datum were excluded from the correlation analysis using an upper limit of the mean ± 3 SD of the participants' data. *P* < 0.05 was considered a significant correlation. A bootstrap procedure (Efron and Tibshirani, 1986) with *n* = 1000 resamples was used to establish the 95% confidence intervals (CI) around the *r* value.

<sup>1</sup>http://www.jichi.ac.jp/brainlab/tools.html

<sup>2</sup>http://bisp.kaist.ac.kr/NIRS-SPM.html

In cases where we examine correlations with the CATS score, partial correlations were also calculated to exclude the possible effects from the LES score and cortisol level. When we test for significant differences between two correlation coefficients, Fisher's *z*-transformation was applied to the correlation coefficients to generate a normal distribution. Then, *t*-statistics were calculated (Cohen and Cohen, 1983).

#### **RESULTS**

#### **SELF-REPORT AND CORTISOL DATA**

**Table 1** presents a summary of the averaged self-report and cortisol data, and correlation coefficients among these measurements. The mean CATS score was 30.77 (SD = 12.91, range = 16–60). The mean LES score was 0.62 (SD = 2.65, range = −12 to 4). The mean blood cortisol level was 11.30µg/dl (SD = 3.48, range = 4.7–17.8). None of these measurements was significantly correlated with age, gender, smoking status, history, or body mass index (BMI). The CATS score was not correlated with the LES score (*r* = 0.30, *p* = 0.18, CI = −0.07 to 0.59) as the index of recent stress. A clear distinction between early and recent life stress, measurement of ELS in CATS, is not confounded by recent life stress (LES). Both CATS (*r* = −0.04, *p* = 0.87, CI = −0.43 to 0.38) and LES (*r* = 0.15, *p* = 0.51, CI = −0.30 to 0.45) scores were not correlated with cortisol levels, suggesting that both early and recent life stress was not associated with the cortisol level, the elevation of which can alter the MPFC activity.

#### **RESTING-STATE DATA**

#### **Resting-state power spectrum density**

**Table 2** shows averaged power across all NIRS channels for each resting-state condition (EC and EO) and for each frequency band (VLFO and LFO). The mean VLFO power of the EC resting state

**Table 1 | Summary of averaged self-report and cortisol data, and correlation coefficients (r) among these measurements.**


M, mean; SD, standard deviation; CATS, child abuse and trauma scale; LES, life event stress scale.

**Table 2 | Summary of averaged power (mM** × **mm<sup>2</sup> /Hz) across all NIRS channels for each resting-state condition (EC and EO) and for each frequency band (VLFO and LFO).**


M, mean; SD, standard deviation; EC, eyes-closed resting state; EO, eyesopen resting state; VLFO, very low-frequency oscillations; LFO, low-frequency oscillations.

was 0.05 mM × mm<sup>2</sup> /Hz (SD = 0.02); that of the EO resting state was 0.07 mM × mm<sup>2</sup> /Hz (SD = 0.06). The mean LFO power of the EC resting state was 0.008 mM × mm<sup>2</sup> /Hz (SD = 0.004). That of the EO resting state was 0.01 mM × mm<sup>2</sup> /Hz (SD = 0.006). In both frequency bands, the EO resting state showed significantly greater power than the EC resting state showed [VLFO, *t*(21) = 2.15, *p* = 0.04; LFO,*t*(21) = 2.98, *p* = 0.007]. These results resemble those reported from earlier studies (Obrig et al., 2000; Tachtsidis et al., 2004; Yan et al., 2009).

#### **Correlation between resting state (VLFO, LFO) and early life stress (CATS score)**

The power of VLFO during the EC resting state at the MPFC around ch9 (BA9) was negatively correlated with the CATS score (*r* = −0.59, *p* = 0.004, CI = −0.81 to −0.25; see **Figure 2**). In contrast, the power of VLFO at the lateral part of the lateral prefrontal cortex (LPFC) at ch31 (BA10) (*r* = 0.49, *p* = 0.02, CI = −0.03 to 0.75) and ch20 (BA 46) (*r* = 0.45, *p* = 0.04, CI = 0.002–0.78) was positively correlated with the CATS score (see **Figure 2**). When the effects from LES and cortisol level were excluded by partial correlation analysis, ch9 (*r* = −0.54, *p* = 0.02, CI = −0.87 to −0.16) and ch31 (*r* = 0.51, *p* = 0.03, CI = −0.17 to 0.81) showed similar results with significant correlation. Regarding the EO resting state, although the power of VLFO at the LPFC showed positive correlation with the CATS score (ch31, *r* = 0.49, *p* = 0.03, CI = 0.10–0.78), partial correlation *r* = 0.55, *p* = 0.02, CI = −0.19 to 0.85), the MPFC showed no correlation with the CATS score.

In contrast to the VLFO, the power of resting state LFO showed no significant correlation with the CATS score during either EC or EO. As additional statistical tests for the correlations between the CATS and EC resting state (VLFO, LFO),we compared the correlation coefficient of VLFO directly with that of LFO.A significant difference was found between these correlations [ch9, *t*(19) = 27.26, *p* < 0.001; ch31,*t*(19) = 2.88,*p* = 0.009]. These results suggest that ELS is specifically related to VLFO rather than LFO.

# **COGNITIVE TASK DATA**

#### **Behavioral data**

**Table 3** presents behavioral data obtained for each task and each stimulus-set condition. The mean RT for the color-similarity judgment task was 1270.06 ms (SD = 310.32). That for the color-preference judgment task was 1612.80 ms (SD = 371.76). Within the color-similarity judgment task, the mean RT for the similarity-easy set trial was 1210.42 ms (SD = 324.19). That for the similarity-difficult set trial was 1329.70 ms (SD = 320.66). Within the color-preference judgment task, the mean RT for the similarity-easy set trial was 1581.74 ms (SD = 345.82). That for the similarity-difficult set trials was 1643.86 ms (SD = 429.97). Twoway repeated-measures ANOVA (task × stimulus set) revealed significant main effects of task [*F*(1, 21) = 37.80, *p* < 0.0001] and the stimulus set [*F*(1, 21) = 7.27, *p* = 0.01]. This result was consistent with those of previous studies using the same tasks (Johnson et al., 2005; Nakao et al., 2013).

The mean error rate in the color-similarity judgment task was 0.27 (SD = 0.06). Within the similarity judgment task, the similarity-easy set trials (mean error rate = 0.14, SD = 0.11) showed significantly lower error rates than the similarity-difficult

**Table 3 | Summary of behavioral data and averaged z score cross all NIRS channels for each task and each stimulus-set condition.**


M, mean; SD, standard deviation; r, Pearson's correlation coefficient; CATS, child abuse and trauma scale; RT, reaction times.

set trials (mean error rate = 0.40, SD = 0.07) [*t*(21) = 8.81, *p* < 0.001]. The observation of lower error rates further confirms that the similarity-easy set trials were indeed easier for our participants.

In addition to the difficulty in color-similarity judgment, color similarity might be yet another confounding influence, especially for color-preference judgment. The judgment of internal or subjective preference might be confounded by the more external or objective color similarity. It is possible that color-preference judgment can be biased by the color-similarity as the external criteria, especially when the color-similarity is a salient external figure (i.e., in the similarity easy–easy set trials). We therefore calculated the rate of similar color choice in the color-preference judgment task to assess how often the color-similarity biases color-preference judgment. We counted the trials in which a participant chose similar color in the color-preference judgment task; then that number was divided by the total number of color-preference judgment trials: 24. The mean rate of similar color choice in the preference judgment task was 0.50 (SD = 0.09). No significant difference was found between the similarity-easy set trial (mean rate of similar

color choice = 0.49, SD = 0.17) and the similarity-difficult set trial (mean rate of similar color choice = 0.50 SD = 0.10). These mean rates of similar color choice are equal or almost equal to the chance level: no evidence shows that the judgment of internal or subjective preference was confounded by the external color similarity as a whole participant group, even when the color-similarity is a salient external figure (i.e., even in similarity-easy set trials).

The rate of similar color choice in the color-preference judgment task showed, however, a significant correlation with the CATS score (*r* = 0.53, *p* = 0.01, CI = 0.12–0.80, see **Figure 2**; **Table 3**). Consistent results were observed even when the effects of the LES score and cortisol level were excluded by partial correlation analysis (*r* = 0.49, *p* = 0.03, CI = −0.83 to 0.84). Within the color-preference judgment task, the rate of similar color choice in similarity-easy set trials showed a significant correlation with the CATS score (*r* = 0.59, *p* = 0.004, CI = 0.16–0.79; partial correlation, *r* = 0.65, *p* = 0.003, CI = 0.32–0.86). In contrast, no significant correlation was found in the similarity-difficult set trial (*r* = 0.01, *p* = 0.95, CI = −0.48 to 0.43; partial correlation, *r* = −0.20, *p* = 0.42, CI = −0.78 to 0.36). For further statistical tests for the correlations, we compared the correlation coefficient of the similarity-easy set trial directly with that of the similaritydifficult set trial. A significant difference was found between these correlations [*t*(19) = 2.51, *p* = 0.02]. The statistically significant difference underscores that the participants with high ELS tended to choose similar color in the color-preference judgments only when color-similarity was a salient external feature, which suggests a shift from internally to externally guided decision making in the similarity-easy set trials by experiencing ELS.

Other behavioral data showed no significant correlation with the CATS score.

#### **NIRS data**

**Table 3** shows the averaged *z* score across all NIRS channels for each task and each stimulus-set condition. Regarding the *z* score of oxy-Hb for the cognitive tasks, the averaged *z* score across all channels for the color-similarity judgment task was 0.25 (SD = 3.96). That for the color-preference judgment task was 0.01 (SD = 2.77).Within the color-similarity judgment task, the *z* score for the similarity-easy set trials was 0.13 (SD = 3.54). That for the similarity-difficult set trials was 0.46 (SD = 4.42). Within the color-preference judgment task, the *z* score for the similarity-easy set trials was −0.35 (SD = 3.21). That for the similarity-difficult set trials was 0.08 (SD = 2.76). Because of the high SDs of the *z* score, three-way repeated-measures ANOVA (task × stimulus sets × channels) revealed no significant differences.

Nevertheless, the *z* score for the color-preference judgment task around ch18 (BA10) was negatively correlated with the CATS scores (ch 18, *r* = −0.61, *p* = 0.002, CI = −0.86 to −0.28, see **Figure 2**). Even when the effects from LES and cortisol level were excluded by the conduct of partial correlation analysis, consistent correlation results were found (ch18, *r* = −0.56, *p* = 0.01, CI = −0.82 to 0.08). In contrast, for the color-similarity judgment task, no significant correlation was found between the *z* score and the CATS score (ch 18, *r* = −0.14, *p* = 0.55, CI = −0.54 to 0.38; partial correlation, *r* = −0.22, *p* = 0.38, CI = −0.70 to 0.38). As further statistical tests for the correlations between the CATS

and *z* score of cognitive tasks, we compared the correlation coefficient of the color-preference judgment task directly with that of color-similarity judgment task. A significant difference was found between these correlations [ch18, *t*(19) = 3.12, *p* = 0.006]. This result suggests that the degree of MPFC activation during color-preference judgment task was specifically related to ELS, as distinguished from the color-similarity judgment task.

The *z* score for the color-preference judgment task around ch18 was negatively correlated with the rate of similar color choice in the preference judgment task (ch18, *r* = −0.62, *p* = 0.002, CI = −0.85 to −0.23, see **Figure 2**). No significant correlation was found between the *z* scores for the color-similarity judgment task and the rate of similar color choice in the color-preference judgment task (ch 18, *r* = −0.21, *p* = 0.36, CI = −0.60 to 0.21). For further statistical tests for the correlations between the rate of similar color choice in the color-preference judgment task and the *z* score of cognitive tasks, we compared the correlation coefficient of color-preference judgment task directly with that of the color-similarity judgment task. Significant difference was found between these correlations [ch18, *t*(19) = 2.76, *p* = 0.01], which suggests that participants who showed decreased MPFC activation during color-preference judgment tend to make colorpreference judgments based on color-similarity as an external criterion.

Within the color-preference judgment task, the rate of similar color choice in similarity-easy set trials showed significant correlation with the *z* scorefor the color-preference judgment task around ch18 (*r* = −0.57, *p* = 0.006, CI = −0.83 to −0.09). No significant correlation was found in the similarity-difficult set trial (ch 18, *r* = −0.20, *p* = 0.36, CI = −0.55 to 0.27). For further statistical tests for the correlations between the *z* score and the rate of similar color choice in the color-preference judgment task, we compared the correlation coefficient of the similarity-easy set trials directly with that of the similarity-difficult set trial. A significant difference was found between these correlations [*t*(19) = 2.17, *p* = 0.03].

Regarding the relation between the resting-state power spectrum density and the *z* scores of the color-preference judgment task, we calculated the correlation between the channels, which showed significant correlation with the CATS score (i.e., ch9 and ch31 of the EC resting state, and ch18 of the color-preference judgment task). The power of VLFO during the EC resting state at ch31 was negatively correlated with the *z* score of the colorpreference judgment at ch18 (*r* = −0.45, *p* = 0.03, CI = −0.72 to 0.21, see **Figure 2**). The power at ch9 showed no significant correlation with the *z* score at ch18. This relation was not found between VLFO during the EC resting state and the *z* scores of color-similarity judgment. The LPFC is known to be activated consistently during goal-directed tasks (Cabeza and Nyberg, 2000; Fox et al., 2005; Owen et al., 2005; Kim et al., 2010). Moreover, it is temporally anti-correlated with midline regions (e.g., MPFC), such that resting-state activation within the MPFC is associated with attenuation of the LPFC (Fox et al., 2005, 2009). Based on these notions, it is possible that participants who experienced ELS showed increased baseline/spontaneous activations in the LPFC, and activations associated with the decrease of MPFC activation during self-oriented task via anti-correlative relation between these regions.

Taken together, as **Figure 2** shows, the CATS sores were correlated with the VLFO power of EC resting state, the *z* score of color-preference judgment, and the rate of similar color choice in the color-preference judgment task. The following two tripartite relations were found. One is among the CATS score, the *z* score of the color-preference judgment task at MPFC, and the power of VLFO during the EC resting state at the LPFC. Another is among the CATS score, the *z* score of the color-preference judgment task at MPFC, and the rate of similar color choice in the color-preference judgment task. Furthermore, regarding the rate of similar color choice in the color-preference judgment task, the tripartite relation was observed in the similarity-easy, but not in the similarity-difficult set trials.

# **DISCUSSION**

The present study was undertaken to assess the relations between ELS and theMPFCfunction during a resting state and self-oriented task. As **Figure 2** shows, the CATS score was negatively correlated with the activations of MPFC during the EC resting state and color-preference judgment task (i.e., *z* score as relative activation from baseline): participants who experienced a high degree of ELS showed decreased activation both in the resting state and selforiented task. These relations were specific to VLFO during EC and *z* score of self-oriented task. These significant correlations remained even with LES score and cortisol level. In contrast, LFO during EC resting state,VLFO and LFO during the EO resting state, and the *z* score of the control task showed no correlation with the CATS score. These results demonstrate for the first time the specific relation between ELS and the MPFC activation during both the EC resting state (VLFO power) and self-oriented task. Additionally, we observed that both ELS and the MPFC activation during colorpreference judgment were associated behaviorally with the rate of similar color choice in the preference judgment. These relations were observed only in the similarity-easy set trials, which suggests that participants who showed high ELS and decreased MPFC activation during the self-oriented task tend to make decisions based on a salient external criterion during the task, which requires decisions based on their own internal criteria (i.e., tend to choose an obviously similar color in the color-preference judgment task). Taken together, our neuronal and behavioral findings demonstrate that high ELS is related to lower MPFC activation during both rest and the self-oriented task. This is behaviorally manifested as an abnormal shift from internally to externally guided decision making, even in situations where internal guidance is required.

Previous reports of fMRI studies have described that ELS is associated with greater deactivation of DMN during a working memory task (Philip et al., 2013b), with decreased functional connectivity within the DMN during a resting state (Burghy et al., 2012; van der Werff et al., in press; Cisler et al., 2013; Wang et al., in press; Philip et al., 2013a). Although NIRS as our index of resting-state brain activity and type of cognitive task differed from fMRI-BOLD, as described in reports of previous studies, our results were consistent with those in that ELS is associated with the attenuated MPFC function during not only the resting state but also self-oriented task. By contrast, an opposite correlation was observed between ELS and the resting-state LPFC activity

(**Figure 2**), supporting a notion from previous reports of some studies that MPFC is temporally anti-correlated with the lateral cortical region (Fox et al., 2005, 2009). Interestingly, it has been suggested that MPFC has a role in biasing decisions based on internal criteria (Volz et al., 2006; Nakao et al., 2010, 2012). Based on these notions, a possible explanation underlying these correlations is that participants with a high degree of ELS cannot shift to refer to their own internal criteria during self-oriented tasks because changes in their MPFC and/or their balance to the lateral regions do not allow them to make the shift from external to internal. They are stuck in the external, which makes it appear as though they avoid making decisions based on their own internal criteria to eliminate anxiety about one's own decision. This possibility seems more plausible in light of the observations that ELS induces anxiety-related behaviors in adulthood (Kalinichev et al., 2002; Dalle Molle et al., 2012).

Given that ELS disrupts a balance between LPFC and MPFC function leading to biasing decisions based on internal criteria during the self-oriented task, it is of interest to note that significant negative correlation between the ELS and the MPFC activation during self-oriented task was observed only in participants with enhanced LPFC activity during EC resting state (participants with larger VLFO power than median at ch31, *r* = −0.81, *p* = 0.003, CI = −0.94 to −0.54; participants with smaller VLFO power than median at ch31, *r* = −0.10, *p* = 0.77, CI = −0.66 to 0.55) (**Figure 3A**). This result suggests the possibility that whether the ELS affects to the MPFC activation during color-preference judgment was moderated by the resting state VLFO power at LPFC. To test this possibility, we conducted moderation analysis. This analysis revealed a marginal moderation effect from resting-state LPFC activity to the relation between the ELS and MPFC activity during color-preference judgment [moderation effect, β = −0.42, *t*(18) = −1.89, *p* = 0.08, see **Figure 3B**; effect of ELS, β = −0.40, *t*(18) = −2.01, *p* = 0.06; effect of resting-state LPFC activity, β = 0.005, *t*(18) = 0.02, *p* = 0.98; overall model statistics, *adjusted R*<sup>2</sup> = 0.42, *F*(3, 18) = 6.08, *p* < 0.05]. These results suggest that higher ELS result in the decreased MPFC activation during the self-oriented task in the participants who showed enhanced resting-state activity at the LPFC.

Our hypothesis that participants with a high degree of ELS cannot make a shift from external to internal during the selforiented task is based on the result of positive correlation between the ELS and the rate of similar color choice in preference judgment (**Figure 2**). Considering that these two scores are both negatively correlated with the MPFC activity during the self-oriented task, it is possible to assume that the MPFC activity during colorpreference judgment mediates the relation between ELS and the rate of similar color choice in color-preference judgment. For further exploratory analysis, we did mediation analysis to examine whether the relation between the ELS and the rate of similar color choice in color-preference judgment was mediated by the MPFC activity during color-preference judgment. The direct path (β = 0.53, *p* < 0.05, **Figure 4A**) from the ELS to the rate of similar color choice in color-preference judgment was significantly mediated by the MPFC activity during color-preference judgment (Sobel-test, *Z* = 1.73, *p* = 0.04, one tailed, **Figure 4B**). After controlling for the MPFC activity during color-preference judgment,

the direct path between the ELS and the rate of similar color choice in color-preference judgment was no longer significant [β = −0.25, *t*(19) = −2.12, *p* = 0.28].

Taken together, it is feasible that the participants with a high degree of the ELS cannot shift to refer to their own internal criteria during self-oriented tasks because their MPFC does not allow them to make the shift from external to internal, especially in the case that the resting-state activity in LPFC was enhanced. Additional studies with more participants' data are expected to confirm these preliminary findings from the multiple regression analyses.

How are our findings related to the self? Color-preference judgments presuppose an internal criterion according to which the judgment is made. The color must therefore be related and compared to an internal criterion (rather than an external criterion as in color-similarity judgment). Such relating and comparing must presuppose some kind of internal standard which is usually

assumed to be the self. This process of relating and comparing to an internal criterion can thereby be described as self-related processing (see Northoff et al., 2006; Qin and Northoff, 2011). Our data hint that such comparing and relating against an internal standard, the self, is deficient in participant with high ELS, which raises two questions related to mediating neuronal mechanisms and related to the presupposed concept of the self. Our data contribute to the first question. In addition to the task-related activity during color-preference judgment, ELS were predicted by the degree of resting-state activity. This suggests some kind of encoding (or representation) of self-related information (about the self) in the resting-state activity itself; this is well in line with previous findings that observed neural overlap (or even prediction) between resting-state activity and self-related activity (see Schneider et al., 2008; Qin and Northoff, 2011; Whitfield-Gabrieli et al., 2011; Nakao et al., 2012; Huang et al., in press). The present study contributes here in that it suggests this self-related information in the resting state to be susceptible to, at least in part, ELS that seems to affect the self (or better its encoding or representation in the resting state) directly. That leads us directly to the second question: what concept of self do we presuppose here? The resting-state activity itself, by definition, shows no kind of cognitive activity related to specific stimuli or tasks. It also shows no sensory, motor, or affective neural activity. Consequently, the self that is encoded or represented in the resting state cannot be described as sensorimotor self (see for instance Legrand, 2007), affective self (Panksepp, 1998; Damasio, 2010), cognitive self (see

LPFC denotes lateral prefrontal cortex.

Damasio, 2010), or social self (Schilbach et al., 2012). Instead, the self that is encoded in the resting state and susceptible to early stressful life events must be described conceptually independent of any specific sensory, motor, affective, cognitive, or social contents. Instead it is apparently more like some kind of structure or organization that serves as the internal standard or reference for subsequent comparing and relating of stimuli like colors that is color preference. Accordingly, our findings suggest a structure or organization-based concept of self which is well compatible with approaches in both neurophilosophy (Northoff, 2013) and the concept of the ego in neuropsychoanalysis (see Northoff, 2011).

Despite the importance of these data for revealing the relation between ELS and brain function, these findings leave several questions unresolved. First, although we found several correlations, as shown in **Figure 2**, causal relations among these measurements remain unresolved. These results tempt us to advance the following hypothesis: ELS results in increased LPFC during rest and decreased MPFC during rest and self-oriented task later in life. Because of these characteristics of neural activities, people with ELS make decisions based on a salient external criterion even when they must make a decision based on their own internal criteria. This hypothesis, however, remains speculative in the absence of data to corroborate these causal relations. Although we obtained consistent results (see **Figures 3** and **4**) with this hypothesis, those were from the preliminary regression analyses. Animal studies manipulating ELS and measuring brain activity under similar experimental settings must be done to reveal the effects of ELS.

Second, no significant difference was found between colorsimilarity judgment and color-preference judgment in terms of the *z* score. A previous study using fMRI (Johnson et al., 2005) showed increased MPFC activation during the color-preference judgment task compared to the color-similarity judgment task. One possible reason for this discrepancy is that the NIRS measures only that activity occurring within the surface of the MPFC. The regions measured by NIRS in this study and those others showing significant difference between these tasks in previous studies might not be exactly the same regions. Nevertheless,

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#### **CONCLUSION**

This preliminary study was conducted to investigate the relations between ELS and the MPFC function during a resting state and self-oriented task. Our obtained NIRS data have revealed that ELS is associated with decreased activation within the surface regions of MPFC during rest and during the self-oriented task. In addition, ELS and the decreased activation within the MPFC during the selforiented task was associated with a tendency to make a decision based on a salient external criterion during the self-oriented task. This study is expected to be of great interest in the field of ELS itself in that it provides evidence about the relations among ELS, restingstate brain activity, task induced brain activity, and behavioral tendencies. Beyond elucidating the phenomena associated with ELS, this line of investigation is expected to contribute to improvement of our understanding of resting-state brain activity and self-oriented processes. Because the present study confronts the two limitations as described above, additional human fMRI experiments and animal studies are expected to increase the validity of the findings presented herein.

#### **ACKNOWLEDGMENTS**

We thank the reviewers for their useful comments. This work was supported by the following grants: Hiroshima University Grants-in-Aid for a scientific research project to overcome stressvulnerability; the Strategic Research Program for Brain Sciences by the Ministry of Education, Culture, Sports, Science and Technology of Japan; JSPS KAKENHI Grant Numbers 24390284 and 25870467.


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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 26 April 2013; paper pending published: 13 May 2013; accepted: 16 June 2013; published online: 03 July 2013. Citation: Nakao T, Matsumoto T, Morita M, Shimizu D, Yoshimura S, Northoff G, Morinobu S, Okamoto Y and Yamawaki S (2013) The degree of early life stress predicts decreased medial prefrontal activations and the shift from internally to externally guided decision making: an exploratory NIRS study* *during resting state and self-oriented task. Front. Hum. Neurosci. 7:339. doi: 10.3389/fnhum.2013.00339*

*Copyright © 2013 Nakao, Matsumoto, Morita, Shimizu, Yoshimura, Northoff, Morinobu, Okamoto and Yamawaki. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.*

# What can psychiatric disorders tell us about neural processing of the self?

# **Weihua Zhao, Lizhu Luo, Qin Li and Keith M. Kendrick \***

Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China

#### **Edited by:**

Niall W. Duncan, University of Ottawa, Canada

#### **Reviewed by:**

Christian Sorg, Klinikum Rechts der Isar Technische Universität München, Germany Rongjun Yu, South China Normal University, China

#### **\*Correspondence:**

Keith M. Kendrick, Room 313, West Section, Main Building, Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, Sichuan 610054, China e-mail: k.kendrick.uestc@gmail.com

Many psychiatric disorders are associated with abnormal self-processing. While these disorders also have a wide-range of complex, and often heterogeneous sets of symptoms involving different cognitive, emotional, and motor domains, an impaired sense of self can contribute to many of these. Research investigating self-processing in healthy subjects has facilitated identification of changes in specific neural circuits which may cause altered self-processing in psychiatric disorders. While there is evidence for altered self-processing in many psychiatric disorders, here we will focus on four of the most studied ones, schizophrenia, autism spectrum disorder (ASD), major depression, and borderline personality disorder (BPD). We review evidence for dysfunction in two different neural systems implicated in self-processing, namely the cortical midline system (CMS) and the mirror neuron system (MNS), as well as contributions from altered inter-hemispheric connectivity (IHC). We conclude that while abnormalities in frontal-parietal activity and/or connectivity in the CMS are common to all four disorders there is more disruption of integration between frontal and parietal regions resulting in a shift toward parietal control in schizophrenia and ASD which may contribute to the greater severity and delusional aspects of their symptoms. Abnormalities in the MNS and in IHC are also particularly evident in schizophrenia and ASD and may lead to disturbances in sense of agency and the physical self in these two disorders. A better future understanding of how changes in the neural systems sub-serving self-processing contribute to different aspects of symptom abnormality in psychiatric disorders will require that more studies carry out detailed individual assessments of altered self-processing in conjunction with measurements of neural functioning.

**Keywords: schizophrenia, autism spectrum disorder, major depression, borderline personality disorder, selfprocessing, cortical midline system, mirror neuron system, inter-hemispheric connectivity**

## **INTRODUCTION**

Brain mechanisms controlling our fundamental sense of self are not only of great interest in themselves but also fundamentally influence our social, cognitive, and emotional behaviors. For most of us that feeling of a secure, private sense of self that only we can access, and which affords the simple ability of distinguishing between ourselves and others, is a given. We use our sense of self to monitor, gage, and learn about our reactions to internal/external changes to our bodies as well as the actions we perform and their consequences on our physical and social environment. Thus any human mental disorder where fundamental aspects of self-processing are impaired is likely to also manifest associated impairments in social and emotional behavior.

There are many different definitions of the self and detailing them is beyond the scope of the present paper (see Kircher and David, 2003; Gillihan and Farah, 2005; Legrand and Ruby, 2009; Christoff et al., 2011). The most pragmatic approach is to distinguish the physical, or bodily self (i.e., knowledge and awareness of the body) from the mental, or psychological self (i.e., autobiographical knowledge, knowledge about personal traits, and experience of first-person perspective). Some consider the integration of these two aspects results in the sense of self as an agent (Gillihan and Farah, 2005), whereas others propose a broader definition which includes an individual's knowledge of their relationship with physical and social stimuli in their environment (Northoff et al., 2006). Many studies investigating the neural circuitry involved in self-processing have used behavioral paradigms which focus on self attributes (i.e., "me") as opposed to the self as an agent ("I"). It has been argued that both attribute and agency aspects of self-processing must be taken into account (Christoff et al., 2011) and could involve different neural systems. Additionally, cultural and learning influences on self-processing have been increasingly recognized with differences between more collectivist (Asian) and independent (Western) cultures having been highlighted, with the former having a more extended selfrepresentation including other significant individuals, notably mothers (Zhu et al., 2007). Interestingly, this cultural effect is weakened in Chinese people raised in Western countries (Ng et al., 2010) and illustrates that both culture and learning can, to some extent, produce an extended concept and representation of self which can potentially blur the distinction between self and other processing.

In recent years a large number of studies mainly using both resting-state and task-related functional magnetic resonance imaging (fMRI) studies in healthy human subjects have implicated a cortical midline system (CMS) involving frontal and parietal components of the default mode network (DMN) as being of key importance for "self" as opposed to "other" processing (see Qin and Northoff, 2011) (see **Figure 1**). The particular involvement of the DMN has received conceptual support due to the observation that regions within it are most active when subjects are at rest and their thoughts are internally directed due to an absence of external stimuli (Gusnard et al., 2001). As such the DMN is referred to as "task-negative" to distinguish it from anti-correlated "taskpositive" networks which show low levels of activity at rest which then increase during the performance of tasks requiring attention to external stimuli (Fox et al., 2005). However, although many studies have provided evidence for regions in the DMN responding more to self than other-related stimuli, it has been difficult to disentangle the extent to which responses are truly self-specific or are influenced by other factors such as familiarity and learning.

A recent meta-analysis has identified CMS and other regions associated specifically with self-related information as opposed to familiar or unfamiliar others (Qin and Northoff, 2011). Evidence for self-specificity was mainly found in the perigenual anterior cingulate (AC), inferior frontal gyrus (IFG), and insula, with the AC localization corresponding to that shown in resting-state studies to be deactivated during tasks. The medial prefrontal cortex (mPFC) was influenced by both self and familiarity and the posterior cingulate cortex (PCC) by familiarity more than self. Thus overall, self-specific processing was associated more with frontal than parietal regions in the CMS.

A second neural system associated with aspects of selfprocessing, and which also includes fronto-parietal [IFG, precentral gyrus, precuneus, supramarginal gyrus (SMG), inferior parietal lobule (IPL)] as well as limbic (anterior insula and anterior mesial frontal cortex) regions is the so-called "Mirror Neuron System" (MNS) (Uddin et al., 2007; Cattaneo and Rizzolatti, 2009) (see **Figure 1**). The MNS responds equivalently to specific goaldirected actions whether they are performed by self or others, and is therefore ideally suited to compute self-other discriminations. Indeed, in parts of the MNS even auditory information suggesting that a specific action has been performed out of sight is an effective stimulus (Cattaneo and Rizzolatti, 2009). The CMS and MNS are linked both in frontal and parietal regions (particularly via the insula and IFG, although also between the IPL and PCC/precuneus), and it has been proposed that they have an integrated role whereby the MNS performs physical other-toself mapping, important for understanding agency attribution, whereas the CMS is more important for understanding psychological aspects. Interestingly, the meta-analysis on CMS and DMN in relation to self carried out by Qin and Northoff (2011) also identified a degree of self-specific processing in the two MNS regions (IFG and insula) with the most extensive connections with the CMS. Indeed, a number of studies have shown that the insula is activated during self-reflection (Modinos et al., 2009).

There is considerable interest in establishing whether selfrecognition and sense of agency occur independently in both brain hemispheres, or are lateralized to some extent, or dependent upon connectivity between the hemispheres. The anterior regions of the CMS (AC, mPFC) and MNS (IFG and insula) are connected via

**FIGURE 1 | Main regions and functional connections of the cortical midline (CMS) and mirror neuron (MNS) systems implicated in the control of self-processing**. Inter-hemispheric connectivity (IHC) via the anterior and middle/posterior corpus callosum are indicated by arrows with the dotted line across the two hemispheres sub-dividing the brain into anterior frontal regions interconnected via the anterior corpus callosum and posterior parietal regions interconnected via the middle/posterior corpus callosum. ACC, anterior cingulate; IFG, inferior frontal gyrus; INS, insula; IPL, inferior parietal lobule; mPFC, medial prefrontal cortex; PCC, posterior cingulate cortex; PCU, precuneus; RS, retrosplenial cortex; SMG, supramarginal gyrus. For simplicity the anterior (mPFC and ACC) and posterior (PCC/RS and PCU) are displayed as single regions. L, left and R, right hemisphere.

the anterior corpus callosum, whereas the posterior ones are connected via the medial/posterior callosum (PCC, precuneus, IPL, SMG) (see **Figure 1**). Studies using split-brain patients have generally concluded that either auditory or visual self-recognition can occur to some extent independently in both hemispheres, with some studies reporting a right hemisphere advantage and others left (see Uddin, 2011). On the other hand evidence from patients with "alien hand syndrome" (AHS – where individuals deny ownership of a hand and sometimes also its actions) suggests that some aspects of this syndrome are produced by damage either to the anterior (anarchic hand – where subjects consider that goaldirected movements of the hand are not under the control of their own will) or middle/posterior (inter-manual conflict) corpus callosum regions. While damage to frontal and parietal cortical regions may also contribute to aspects of AHS, there does seem to be support for the view that inter-hemispheric connectivity (IHC) involving the corpus callosum is important for awareness of goal-directed movement and a sense of limb ownership (see Uddin, 2011). Findings from patients with callosal agenesis also suggest impairments in aspects of sense of agency with poor personal insight, introspection, perspective taking, and self-awareness (Brown and Paul, 2000; Paul et al., 2007). Thus IHC may also play an important role in self-processing.

While we may be able to learn more about the neural substrates of self-processing from patients with brain lesions, they are relatively rare and damage often involves a number of different systems. A recent case study, for example, reported preserved selfawareness in a patient with damage to the insula, AC, and mPFC but without damage to the parietal lobes (Philippi et al., 2012). This might perhaps suggest that self-awareness does indeed involve multiple brain systems. However, a far more extensive source of patients with altered aspects of self-processing are those with psychiatric disorders. While these disorders are clearly complex, and often include extensive cognitive and emotional processing dysfunction, they are commonly associated with different patterns of altered functioning of CMS and MNS systems and IHC which may contribute to abnormal self-processing. Here we will focus on some of the main disorders where self-processing is known to be affected, namely schizophrenia, autism spectrum disorder (ASD), unipolar depression, and borderline personality disorder (BPD). To identify papers specifically addressing self-processing alterations in these disorders we used main search terms of "schizophrenia and self,""autism and self,""depression and self,"and"BPD and self" in PubMed and Google Scholar. Additionally we used search terms of "schizophrenia and sense of agency," "depression and rumination," and references included in the recent reviews cited.

# **SELF-PROCESSING IN SCHIZOPHRENIA**

Schizophrenia has long been considered as a self-disorder. However, although self-experience anomalies are considered to be a first-rank core symptom of schizophrenia (Schneider, 1959), there is still considerable debate as to their precise definition and the extent to which they contribute to other extensive cognitive and emotional dysfunction in the disorder as well as other symptoms such as pain insensitivity. Aspects of both the physical and psychological self are disturbed in schizophrenia with the main features being in terms of impaired self-other discrimination, including body-ownership, and also an altered sense of agency whereby patients have problems in determining whether their thoughts and actions are controlled by themselves or by external agents. It is not the purpose of this review to discuss the various symptoms in detail since this is done elsewhere (Sass and Parnas, 2003; Lysaker and Lysaker, 2010; Waters and Badcock, 2010). One of the key recent observations however is that evidence for self-disorders has been found in both schizotypal personality disorder and schizophrenia, suggesting that non-psychotic anomalies of self-experience occur across the schizophrenia spectrum (Raballo et al., 2011) and are a core feature which may also influence other cognitive and emotional symptoms. An influential theory attempting to explain the root cause of self-disorders in schizophrenia is that self-other distinctions are due to a faulty action processing mechanism linking motor and sensory systems (Frith et al., 2000;Waters and Badcock, 2010). This so-called internal forward model predicts the sensory consequences of motor commands which allows differentiation of sensations experienced on the basis of whether they result from intentional movement or from changes in the external world. Distinction between sensations is achieved because the model predicts reduced sensory effects occurring following self-generated movements and the internal system therefore deduces that sensations

result from a self-generated motor command. Thus it is hypothesized that schizophrenia patients are impaired in their ability to discriminate between sensations resulting from their own selfgenerated motor actions and those resulting from external agents due to prediction errors occurring in this sensorimotor comparator system. The result of this is that patients can feel that their own actions are not generated by themselves but by some external agent. This has been shown experimentally using action perception/feedback tasks where a reduction in precision in predicting the sensory consequences of action is associated with the severity of delusions of control (Synofzik et al., 2010). This lack of precision results in patients placing greater reliance on external retrospective rather than internally generated predictive cues for linking actions with external events (Voss et al., 2010). A simple behavioral demonstration of this is self-tickling where healthy subjects know the action is self-generated and the sensory feedback completely predictable and so are unresponsive, whereas when we are tickled by someone else it is not so predictable and we do respond. However, in schizophrenia patients this self vs. other recognition distinction breaks down and they can effectively tickle themselves (Blakemore et al., 2000). A similar argument based on a deficit in a neural comparator linking perception and action impairment has been made to extend this concept into cognitive systems to explain impaired theory of mind and emotional response deficits (Frith et al., 2000; Jeannerod, 2003). Indeed, a recent study has reported evidence for a deficit in error-likelihood prediction in the mPFC in schizophrenia patients in the context of a workingmemory task (Krawitz et al., 2011). Additional behavioral evidence for breakdown of a comparator mechanism linking perception and action during self-other interactions is impaired gesture and movement imitation (Matthews et al., 2013) and emotional contagion (unconscious imitation of smiling and yawning – Haker and Rössler, 2009) in patients. These behaviors are thought to particularly involve the MNS and therefore suggest that its function is altered in some way in schizophrenia.

A large number of structural and resting-state MRI studies have endeavored to establish the key structural and functional changes which occur in schizophrenia. Overall these studies consistently show that there is both structural and functional evidence for widespread disconnection between brain regions both within and across hemispheres and that changes in the CMS and MNS (Friston and Frith, 1995; Garrity et al., 2007; Huang et al., 2010; Lynall et al., 2010; Guo et al., 2012) and key sensorimotor and cortical integration regions such as the thalamus (Clinton and Meador-Woodruff, 2004; Welsh et al., 2010; Marenco et al., 2013) occur frequently as well as reduced IHC involving both the corpus callosum and the anterior commissure (Crow, 1998; Choi et al., 2011; Guo et al., 2012, 2013). Altered functional connectivity between pre-motor and motor cortices has also been observed (Guo et al., 2012), and may contribute to a disturbed sense of bodily self in schizophrenia which is known to be associated with these motor connections as well as the insula (Ferri et al., 2012a,b).

While there has been increasing recent interest in investigating which structural and resting-state changes in neural systems may specifically relate to the core symptoms of self-disorder in schizophrenia, many of the routine measures of positive and negative symptoms used do not address self-processing impairments adequately. For example, the widely used Positive and Negative Symptom Scale (PANSS) only considers the presence of hallucinations and delusions and lack of insight (lack of awareness of illness and need for treatment). The presence of auditory hallucinations is associated with more impaired self-recognition performance (Waters et al., 2012) and degree of preserved insight is associated with alterations in responses in brain regions associated with selfreflection (van der Meer et al., 2012). However, going forward the development and use of better qualitative and quantitative measures of self-disorders in schizophrenia will help identify more precisely the role of changes in specific circuitry in influencing different aspects of self-experience, and some progress in this direction has already been made (Raballo et al., 2011). Nevertheless, some task-dependent studies have attempted to establish which of the many altered neural circuits in schizophrenia may be of specific importance for altered self-reflection and sense of agency.

An influential recent task-dependent study has provided evidence for a possible anterior to posterior shift in activation of the CMS during a self-reflection paradigm where subjects were presented with positive and negative trait adjectives and asked to consider them in the context of describing self or other. Schizophrenia patients showed reduced activation in the right mPFC and increased activation in the bilateral middle/posterior cingulate gyri during self-reflection as well as reduced functional connectivity between the AC and middle/posterior cingulate (Holt et al., 2011). A subsequent study using a similar task has shown hyporesponsivity in the mPFC and hyperactivation in the precuneus during selfevaluation, both of which correlated with insight scores (Bedford et al., 2012). This further supports the view that reduced insight in schizophrenia may be related to impaired self-processing. Another study has found reduced activation in the AC in schizophrenia patients during self-monitoring of performance (Carter et al., 2001). Reduced functional connectivity between frontal and parietal components of the CMS has also been reported both during resting-state (associated with severity of hallucinations and delusions – Rotarska-Jagiela et al., 2010) and a working-memory task (Deserno et al., 2012). Additionally, increased activation during a self vs. other-reference task has been reported in the PCC and precuneus in the posterior CMS and the IPL and SMG in the posterior MNS as well as the post-central gyri (Shad et al., 2012).

A brain-wide resting-state functional connectivity analysis found that the greatest changes in schizophrenia occurred in these posterior regions of the CMS and MNS [notably involving the superior parietal gyrus and precuneus (CMS) and IPL, angular gyrus, and SMG (MNS)]. These CMS and MNS changes were associated with both positive (including delusions and suspiciousness/persecution) and negative symptoms, and had a high discriminative accuracy for distinguishing patients from healthy controls (Guo et al., 2012). While some reduced resting-state functional connectivity was also observed in the anterior CMS (AC and superior frontal gyrus) and MNS (IFG) regions, this was not related to symptom severity (Guo et al., 2012). Within the MNS, resting-state functional connectivity between the right IFG and the insula has been found to be decreased in schizophrenia patients (Moran et al., 2013), and increased right IFG/insula activation occurs during auditory hallucinations (Sommer et al., 2008).

There is also increasing evidence for altered functional connectivity between the MNS and CMS in schizophrenia with decreased resting-state connectivity between the IFG and PCC (Zhou et al., 2007) and between the insula and PCC (Moran et al., 2013). The main hub region affected in the resting-state analysis by Guo et al. (2012) was the IPL, in the posterior MNS, with its functional connections with posterior CMS regions (precuneus and superior parietal gyrus) strengthened, and those with the angular gyrus and SMG weakened. Thus schizophrenia patients may have decreased functional connectivity between frontal MNS regions and both anterior and posterior regions of the CMS but increased functional connectivity between posterior regions of both the MNS and CMS. Overall therefore, integration between the MNS and CMS self-processing systems would appear to be highly dysfunctional in schizophrenia patients.

Further evidence for an important role of altered IPL function in the posterior MNS in schizophrenia and self-processing has been provided by a number of other studies. An increased overlap of cortical maps in schizophrenia patients in medial frontal, medial parietal, IPL, and middle temporal cortex has been reported during implicit self vs. other voice distinctions, with altered IPL activity being positive correlated with positive symptom severity (Jardri et al., 2011). The IPL, angular gyrus, and SMG have also all been reported to be involved in action awareness, sense of agency, and self-recognition (Farrer et al., 2004, 2008; Torrey, 2007; Macuga and Frey, 2011). Further, repetitive transcranial stimulation of the IPL has been shown to interfere with self-other face discrimination in healthy subjects (Uddin et al., 2006) and parietal lobe epilepsy is associated with the occurrence of psychotic symptoms including delusions and hallucinations (Salanova et al., 1995). Finally, a magnetoencephalography study has reported reduced alpha and gamma band oscillations and phase-locking in the right inferior parietal cortex of schizophrenia patients during observation of biological motion, providing further evidence for altered mirror neuron properties in this region (Kato et al., 2011).

The potential contribution of reduced functional IHC in schizophrenia (Knöchel et al., 2012; Guo et al., 2013) to altered selfexperience has yet to be fully established, although studies showing that connectivity between the hemispheres is important for a sense of agency, but not for self-recognition, are clearly suggestive (see Uddin, 2011). A recent resting-state study has provided evidence for a brain-wide reduction in functional connectivity involving symmetric regions in the two hemispheres, and including both anterior and posterior parts of the corpus callosum. Furthermore, this was correlated with severity of both positive and negative symptoms (Guo et al., 2013). For patients with psychiatric disorders associated with abnormalities of the callosum, schizophrenia is the most common (David et al., 1993) and other abnormalities in the corpus callosum are associated with severity of reality distortion in schizophrenia patients, although it would appear that smaller changes may be worse than larger ones in this respect (Whitford et al., 2010). A further interesting observation is that atypical cerebral lateralization, as evidenced in individuals who are right handed but left footed, is associated with schizotypal traits and an abnormal sense of agency (Asai et al., 2011).

A summary of the main changes in self-processing neural networks in schizophrenia is provided in **Figure 2A** and **Table 1**.

Overall there is evidence for disruption in both activity and functional connectivity involving the CMS, MNS, and IHC in schizophrenia in terms of resting-state activity and functional connectivity associated with symptom severity. This is supported by some task-dependent studies involving self-referential paradigms. In many cases neural changes in these self-processing systems are also correlated with severity of delusions and hallucinations and with poor insight. The general pattern of changes observed is of reduced resting-state activity and responses during self-referential tasks in frontal regions of the CMS and MNS and increased ones in posterior parietal regions of these two systems. There is also reduced functional connectivity between frontal and posterior components of the CMS both in resting-state and during self-referential tasks and between the anterior MNS and anterior/posterior CMS, although it is increased between the posterior regions of the MNS and CMS. Thus there appears to be a shift from a balanced and integrated CMS and MNS in terms of their anterior and posterior components toward and unbalanced and disconnected pattern in schizophrenia with a posterior hyperactivity bias. Furthermore, since both anterior and middle/posterior divisions of the corpus callosum show reduced structural and functional connectivity the resulting reduced inter-hemispheric connectivity


**Table 1 | Overall activity and functional connectivity changes in frontal and parietal cortical midline system regions involved in self-processing in schizophrenia, ASD, depression, and BPD.**

AC, anterior/medial cingulate; ASD, autism spectrum disorder; BPD, borderline personality disorder; FC, functional connectivity; IFG, inferior frontal gyrus (frontal part of mirror neuron system); IH, inter-hemispheric; IPL, inferior parietal lobule (posterior part of mirror neuron system); PCC, posterior cingulate; PCUN, precuneus; SC, structural connectivity. \*BPD changes are shown for patients without co-morbid disorders.

between the anterior and posterior regions of the CMS and MNS may further exacerbate self-processing deficits.

## **SELF-PROCESSING IN AUTISM**

There is extensive evidence that self-other awareness is either impaired or delayed in terms of development in ASD, including self-recognition, body awareness, and sense of agency. Both clinical and research evidence has found that ASD patients have difficulties with sense of self and self-other confusion in terms of language use and make frequent pronoun reversal errors (I/me/you) (see Lyons and Fitzgerald, 2013). Individuals with ASD often have general postural and motor impairments as well as in action simulation, mimicry, and imitation (see Gallese et al., 2013), suggesting that similar to schizophrenia ASD patients may have impaired perception/action processing leading to problems in determining whether actions are self-generated or not. Indeed, there are a number of similarities between ASD and schizophrenia, including delusions, although while there are overlaps between the two disorders, and occasional co-morbidity, it is clear the severity of abnormal self-processing is much greater in schizophrenia (Fitzgerald, 2012).

As with schizophrenia resting-state and task-dependent fMRI and structural MRI studies have reported reduced connectivity involving long-distance connections but increased short-distance connectivity within frontal and temporal regions (see Uddin and Menon, 2009; Müller et al., 2011; Gallese et al., 2013; Lynch et al., 2013). It is argued that this results in a disruption in integrative processing between brain regions, and studies have shown altered connectivity in CMS and MNS, as well as in IHC, which may contribute to disordered self-processing (Anderson et al., 2011; Lyons and Fitzgerald, 2013).

In ASD, the CMS frontal (ventral mPFC and AC/medial cingulate) regions have been implicated in impairments in selfrecognition (particularly self-face recognition – see Lyons and Fitzgerald, 2013), self-other discrimination in mentalizing tasks (Lombardo et al., 2010), and social behavior (Dapretto et al., 2006; Lynch et al., 2013). However, relatively few studies to date have specifically used task-dependent paradigms to investigate disordered self-processing in ASD. One notable exception to this is an elegant fMRI study using a visual imagery task, where adolescent ASD patients either watch others performing actions or imagine themselves performing the same action (Chiu et al., 2008). The results revealed a specific reduction in the response of the medial cingulate to self performed actions but not when observing those

of others. In a second paradigm using a multi-round economic trust game the same deficit was observed in this medial cingulate region during self-decisions but not during those made by the partner in the game. The extent of reduced self-responses in the medial cingulate was also correlated with ASD symptom severity. In another task-dependent study using an introspective emotional awareness task, ASD patients were also found to show reduced activity in the left mPFC and right AC, although activity in the precuneus was decreased in the left hemisphere and increased in the right (Silani et al., 2008). Thus in the CMS, impaired anterior/medial cingulate function in ASD patients appears to be associated most consistently with self-processing dysfunction.

Resting-state functional connectivity within frontal (mPFC – AC; Vissers et al., 2012) and between frontal and parietal components of the CMS has been shown to be decreased in both adolescent and adult ADHD patients relative to controls (Monk et al., 2009; Assaf et al., 2010; Weng et al., 2010). However, this fronto-parietal functional connectivity increases significantly with age in healthy controls but does so to a lesser extent in ADHD patients (Wiggins et al., 2011). Reduced functional connectivity between frontal and parietal regions has also been shown in adult ASD patients in the context of an executive function task and was negatively correlated with Autism Diagnostic Observation Schedule (ADOS) scores (Just et al., 2007). A further recent study has reported increased resting-state PCC functional connectivity but decreased connectivity involving the precuneus, although not in relation to the frontal cortex (Lynch et al., 2013). Thus, similar to schizophrenia, there appear to be a number of connectivity and activity changes involving CMS parietal regions with a consistent finding being weakened functional connections between them and frontal regions of the CMS. Possibly the greater severity and delusional aspects of self-disorders in schizophrenia compared to ASD may reflect an even greater aberrant organizational shift toward posterior parietal regions and disconnection between them and frontal ones.

In view of motor and imitation impairments in ASD there has also been a recent focus on potential abnormalities in the MNS, although there is still considerable debate concerning the importance of the MNS role in this disorder (Dapretto et al., 2006; Rizzolatti and Fabbri-Destro, 2010; Enticott et al., 2012; Gallese et al., 2013). Studies to date have mainly highlighted reduced activation in frontal regions of the MNS (IFG), insula, and ventral pre-motor cortex (Dapretto et al., 2006; Silani et al., 2008; Uddin

and Menon, 2009; Enticott et al., 2012) associated with severity of social dysfunction in ASD. Out of all of these MNS regions the most commonly reported finding is of reduced activity in the right anterior insula (see Uddin and Menon, 2009). There is also reduced functional connectivity between the bilateral insula and AC indicating a reduced interaction between frontal regions of the MNS and CMS in ASD (Vissers et al., 2012) similar to schizophrenia. However, in contrast to schizophrenia, altered responses in the posterior parietal components of the MNS (i.e., IPL and SMG), or their functional connectivity with the posterior part of the CMS (PCC and precuneus) have not generally been reported in ASD. Indeed, differences in the IFG responses, but not those of the IPL, have been found between adult ASD patients and controls during performance of a mental rotation task (Silk et al., 2006). However, a recent study has reported a different developmental trajectory for IPL responses during an emotional self-referencing task. Whereas control subjects showed a reduction in responses during adulthood compared to adolescence, ASD patients showed an increase. Indeed, IPL responses were negatively correlated with ASD symptom severity in adults although there were no overall differences between controls and ASD patients in either adolescence or adulthood (Schulte-Rüther et al., 2013). This finding suggests that age-associated compensatory changes may be occurring in ASD in the IPL as well as in resting-state functional connectivity involving the PCC (Lynch et al., 2013). Nevertheless, overall changes in parietal CMS and MNS regions in ASD appear to be less marked than those observed in schizophrenia and this may contribute to the greater severity of disturbed self-processing in this latter disorder.

While a number of studies have reported neural changes in ASD primarily in the right hemisphere, and this has led to the hypothesis that right hemisphere dysfunction is of greatest importance in this disorder (Lyons and Fitzgerald,2013), there is nevertheless also evidence for involvement of altered inter-hemispheric connectivity. A recent structural and resting-state functional connectivity study found both significant reductions in corpus callosum volume and inter-hemispheric functional connectivity of the anterior insula and superior parietal lobule as well as sensorimotor cortex, fusiform gyrus, and superior temporal gyrus. Interestingly, only the functional connectivity changes were associated with ASD symptoms (Anderson et al., 2011). This study additionally reported a greater age-associated reduction in functional hemispheric connectivity in control subjects than in ASD patients, again suggesting possible age-associated compensatory changes in ASD. There may also be important links between structural changes in the corpus callosum and weakened functional connectivity between frontal and parietal regions of the CMS in ASD since these have been found to be correlated (Just et al., 2007). Another study reported 45% of children and 35% of adolescents with agenesis of the corpus callosum had scores on the Autism Spectrum Quotient above the autism-screening cut-off (Lau et al., 2012). A case study has also reported more severe impairment of self-referential behavior in an ASD patient with agenesis of the callosum (with damage primarily in the anterior and medial regions), although interestingly this was not associated with greater problems with appropriate first-person pronoun usage (Lombardo et al., 2012). Since the anterior part of the corpus callosum primarily connects

between frontal brain regions (see **Figure 1**) this suggests that disturbed self-processing in ASD may be mainly contributed to by altered intra- and inter-hemisphere connections involving frontal regions.

A summary of the main changes in self-processing neural networks in ASD is provided in **Figure 2B** and **Table 1**. Overall there is consistent evidence for frontal regions of the CMS (mPFC and anterior and medial cingulate) and MNS (IFG and anterior insula) being hyporesponsive during self-processing in ASD. Reduced inter-hemispheric connectivity in ASD also seems mainly to occur in the anterior part of the corpus callosum linking frontal and anterior insula regions. While some evidence for either decreased or increased activity has been reported in the posterior CMS (precuneus) and MNS (IPL) this is less consistent. Age dependent compensatory changes seen in posterior parietal regions of the CMS and MNS, and in inter-hemispheric functional connectivity, may help to improve both balance and integration between anterior and posterior parts of the two systems. There is some evidence for improvements in severity of ASD symptoms with age, at least in high functioning patients (Happé and Charlton, 2012), and perhaps such compensatory changes may also help prevent the occurrence of more severe disturbances in self-processing in ASD such as those seen in schizophrenia.

# **SELF-PROCESSING IN DEPRESSION**

Patients with major depression have a number of abnormalities in self-related processing, although these tend to be mostly in terms of increased self-focus, including excessive self-reflection (rumination) and associating themselves with negative emotions (see Northoff, 2007; Lemogne et al., 2012). Indeed, self-focus in depression has been shown to be a predictor of the likely re-occurrence of depressive episodes (see Nolen-Hoeksema et al., 2008). There have been a large number of resting-state and task-dependent studies reporting activity and functional connectivity changes in the DMN and regions controlling emotional and cognitive function in both first episode and treatment-resistant depression patients (see Wang et al., 2012). A recent study has also reported restingstate functional connectivity changes in the so-called"hate-circuit" comprising the superior frontal gyrus, insula, and putamen which may contribute to symptoms of "self-loathing" and reduced "selfesteem" which often occur in depressed patients (Tao et al., 2011). In this review we will focus primarily on changes in the CMS and MNS associated with rumination.

Neuroimaging studies have shown that frontal and parietal components of the DMN and CMS exhibit increased resting-state activity in depressed patients (see Wang et al., 2012), and that this reduces less than in controls when they view and appraise negative emotional stimuli (Sheline et al., 2009) or increases less in the mPFC and precuneus during self-focus (Grimm et al., 2009). It has been argued that the differences reported in the direction of altered mPFC activity in depression may reflect different interactions between mPFC and other regions in DMN and task-positive networks in event-related as opposed to block-based experimental paradigms (Lemogne et al., 2012). Indeed, another study has reported increased DMN dominance over task-positive regions (assessed by analysis of fronto-insular interactions) which

correlated with higher maladaptive depressive rumination scores and reduced adaptive rumination ones (Hamilton et al., 2011).

During a task where depressed individuals were cued to ruminate they exhibited increased activity compared to controls in the CMS (AC and PCC) and in the posterior MNS (IPL), although in the anterior MNS (IFG) decreased activation occurred (Cooney et al., 2010). Importantly, a study has revealed that there may be a degree of dissociation between anterior and posterior CMS responses when individuals are cued to think about hopes and aspirations as opposed to duties and obligations (Johnson et al., 2009). Both depressed patients and healthy controls showed similar reduced activation in the anterior CMS (AC and medial frontal gyrus) when thinking about hopes and aspirations and increased activations in the posterior CMS (PCC and precuneus) when thinking about duties and obligations. In depressed patients anterior CMS responses to hopes and aspirations were negatively correlated with rumination scores whereas in the posterior regions they were positively correlated. In a second experiment in the same study depressed patients were found to exhibit reduced activation compared to controls in the anterior CMS during a self-evaluation condition where patients tend to focus more on negative selfreferential thoughts. Negative self-referential thoughts tend to be perseverative in depressed patients and the study also found that they showed a reduced deactivation (i.e., actual activity levels were higher than in controls) responses in the posterior CMS (precuneus) during a distracter task. In both the anterior and posterior CMS regions activity during the distracter task was positively correlated with rumination scores. An anterior/posterior CMS dissociation in depression has also been shown in another study reporting reduced negative blood oxygen level dependent responses (NBRs) in the anterior CMS and increased ones in the posterior CMS during a self-relatedness task (Grimm et al., 2011). However, a previous study by the same group reported decreases in both anterior and posterior CMS regions using the same task (Grimm et al., 2009). This may reflect a medication effect since all the patients in the later study were medicated whereas in the earlier one they were not. Indeed, another study has shown that anti-depressant medications had a greater impact on functional connectivity changes in the posterior than in the anterior CMS (Li et al., 2013).

Another resting-state study has reported that functional connectivity between the mPFC and other DMN networks, as well as cognitive control and affective networks is increased (Sheline et al., 2010). Functional connectivity between the fronto-parietal CMS (AC and PCC) has also been found to increase during the resting-state, but not during a short-term memory task, and this was associated with rumination scores (Berman et al., 2011). Thus depression is consistently associated with increased functional connectivity between frontal and parietal regions of the CMS which distinguish it from schizophrenia and ASD where there is reduced connectivity. However, in line with anterior/posterior differences in activity changes in self-related tasks in depression a recent resting-state study has reported increased functional connectivity in the anterior CMS (mPFC and AC) which correlated positively with rumination scores, whereas in the posterior CMS (PCC and precuneus) reduced connectivity correlated negatively with over general autobiographical memory (Zhu et al., 2012). Another study has also reported increased functional connectivity within the frontal CMS (mainly mPFC) network and decreased in the posterior part (mainly precuneus) (Li et al., 2013). Additionally, this latter study found that successful treatment with anti-depressants only reversed functional connectivity changes in the posterior CMS.

Depressed patients also show decreased mimicry of happy face expressions (Schwartz et al., 1976) and reduced resting-state connectivity occurs in many components of the MNS including the IFG, insula, precentral gyrus SMG, and IPL (Tao et al., 2011). Reduced resting-state activity has been found in the insula in depression (Hamilton et al., 2011) and is associated with reduced interoceptive awareness (Wiebking et al., 2010). Further, there is some evidence for reduced resting-state functional connectivity between the insula and the AC and PCC in the CMS (see Sliz and Hayley, 2012) and between the IFG and AC (Wang et al., 2012). Possibly these weakened insula functional connections with both anterior and posterior CMS regions and between the IFG and the anterior CMS may contribute to the failure of depressed patients to disengage from negative thoughts and reflect a weakened influence of interoceptive cues and executive control over negative affect. Conversely, activity in the posterior part of the MNS (IPL) is increased during rumination (Cooney et al., 2010), suggesting that like the CMS there may be some differences between anterior and posterior components in depression. However overall, alterations in the MNS in depression which influence self-processing may be less influential than those in schizophrenia and ASD. Indeed, perhaps the reduced connectivity between the CMS and MNS in depression reflects a greater dominance of the CMS in depression and reduced potential conflict between CMS and MNS systems. This might help explain why depression does not result in a more severe self-processing dysfunction such as that in schizophrenia and ASD.

Inter-hemispheric connectivity is also reduced in depression and it has been proposed on the basis of TMS (Holtzheimer et al., 2001), electroencephalography (EEG) (Stewart et al., 2011), and fMRI (Kilgore et al., 2007) studies that an imbalance between left and right hemisphere activity may play an important role in contributing to this disorder. A diffusion tensor imaging study has found reduced fractional anisotropy in the anterior genu of the callosum which primarily connects between frontal cortical regions (Xu et al., 2013). However, to date no studies have attempted to associate IHC changes in depressed patients with self-focus or rumination, although it is interesting that as with ASD only connectivity between the frontal cortices may be impaired.

A summary of the main changes in self-processing neural networks in depression is provided in **Figure 2C** and **Table 1**. Overall the main pattern of changes involves increased resting-state activity in the anterior and posterior parts of the CMS and in the functional connectivity between them. During rumination patients also exhibit increased activity in these CMS regions as well as in the posterior MNS. During performance of self-reference tasks patients show either a reduced increase or decrease in activity in the CMS. However, while similar overall patterns of resting-state activity change usually occur in the anterior and posterior CMS several task-based studies have indicated a degree of dissociation between them with opposite directions of changes occurring during tasks, and also anti-depressant medication influencing posterior more than anterior changes in one case.

In the anterior MNS (insula and IFG) there is reduced restingstate activity in depressed patients and reduced functional connectivity with frontal (insula and IFG) and posterior (insula) regions of the CMS. There is also evidence for reduced inter-hemispheric connectivity involving frontal regions. Thus overall, depression is primarily associated with tonic hyperactivation in the CMS, contributed to by excessive rumination, and reduced activity changes in the same regions during self-referential tasks. These findings suggest an impaired ability to disengage from negative rumination during self-related tasks, perhaps contributing to an increased negative evaluation of self. This may also be contributed to by a reduced activity in the insula and its connections with both the frontal and posterior CMS, and between the IFG and anterior CMS, resulting in weakened control of negative affect due to impoverished interoceptive feedback and executive control.

The two core symptoms of depression are depressed mood and anhedonia. There is evidence for significant interactions between rumination and negative mood with rumination prolonging and deepening episodes of depression by promoting depressed mood. Rumination is also associated with suicidal ideation (Nolen-Hoeksema et al., 2008). The AC has been implicated both in negative mood and anhedonia and is increasingly regarded as a key region contributing to depression (Hamani et al., 2011; Pizzagalli, 2011; Treadway and Zald, 2011). While different functional connections of the AC are involved in terms of its influence on negative mood (amygdala) and anhedonia (fronto-striatal reward systems) compared to self-processing/rumination (insula and PCC/precuneus), there may be integration within the AC itself and this may help explain why this region is one of the most successful for the therapeutic application of deep brain stimulation in refractory depression (Hamani et al., 2011). Indeed, since rumination is considered to be highly predictive of the occurrence of depression it seems possible that rumination-induced changes in the AC in particular may promote the subsequent development of negative mood and anhedonia symptoms.

# **SELF-PROCESSING IN BORDERLINE PERSONALITY DISORDER**

Borderline personality disorder patients have dysfunctional emotional regulation, impulse control, interpersonal relationships, and self-image/identity (Leichsenring et al., 2011). The diagnostic criteria for BPD under DSM-IV required that individuals have five out of nine symptoms, and only one of these: "Identify disturbance: notably and persistently unstable self-image or sense of self" specifically pertained to altered self-processing. However, in DSM-V diagnostic criteria for BPD specify that a person must have a significant impairment in personality functioning in relation to self. BPD patients also often have co-morbid post-traumatic stress disorder (PTSD), obsessive compulsive disorder, depression or dissociative disorder (DD) and this can make interpretation of neuroimaging findings more complex. Nevertheless, identity disturbance appears to be a core and distinctive component of BPD with patients expressing a sense of "self-fragmentation" and "falling apart" with four key features (role absorption: i.e., being absorbed in a single role or cause; painful incoherence: i.e., lack of a coherent subjective sense of self; inconsistency: i.e., objective evidence of incoherent behavior; lack of commitment: i.e., uncommitted to jobs or values) (Wilkinson-Ryan and Westen, 2000).

In contrast to schizophrenia, ASD, and depression there are less structural and functional neuroimaging studies in BPD and few of them have attempted to associate changes specifically with altered self-processing. Interpretational problems are also caused by the fact that BPD patients studied often have co-morbid PTSD, depression, obsessive compulsive disorder, or other personality disorders (Korzekwa et al., 2009; Leichsenring et al., 2011). However, studies contrasting BPD with DD can be particularly information because the latter primarily involves feelings that everything is unreal, of being disconnected from one's body or feelings, and amnesia for autobiographical information (Korzekwa et al., 2009).

In terms of the CMS, the general pattern of findings from a variety of neuroimaging studies of BPD patients (mostly using positron emission tomography, PET) is for reduced size and resting-state activity in the mPFC and AC (see Lis et al., 2007; Korzekwa et al., 2009; Leichsenring et al., 2011; Wolf et al., 2011) although the mPFC is hyper-responsive to induced negative emotions and social exclusion, possibly reflecting reduced ability to exert emotional (Herpertz et al., 2001; Koenigsberg et al., 2009; Ruocco et al., 2010). However, one PET study has reported increased activity in female BPD patients bilaterally in the AC and in the right IFG although this may reflect co-morbidity with OCD/depression in many patients (Juengling et al., 2003). Another PET study with a small number of patients (*n* = 8) without comorbidities has reported similar findings (Salavert et al., 2011) as well as hypometabolism in the PCC and precuneus. Thus the pattern of resting-state changes in the CMS is not entirely consistent and needs to be confirmed with appropriate account being taken of potential co-morbidity contributions.

During emotion and reward-related tasks a study has reported significantly reduced deactivation in the anterior/medial cingulate cortex and retrosplenial cortex (isthmus of the PCC) in BPD patients. Indeed, in the retrosplenial cortex tasks evoked activation rather than deactivation. The amount of deactivation in the retrosplenial cortex was positively correlated with the degree of personality organization (Doering et al., 2012). A recent metaanalysis of neural correlates of negative emotionality in BPD has also found reduced activation in the AC but increased in the insula and PCC (Ruocco et al., 2012). To date no study has reported altered functional connectivity between the frontal and parietal regions of the CMS in BPD, which is perhaps surprising given similarities with schizophrenia and ASD in terms of identity disturbances.

Interestingly, the right parietal cortex (PCC and precuneus) has been reported to be reduced in size in BPD resulting in a greater left to right asymmetry (Irle et al., 2005). However, another study which found reductions in both AC and PCC gray matter in BPD, but corresponding increases in white matter, showed that PCC changes only occurred in patients with co-morbid schizotypal personality disorder (Hazlett et al., 2005). Indeed,Irle et al. (2005) also reported a positive correlation between gray matter volume in the parietal cortex and psychotic symptoms in their cohort of BPD subjects and in a subsequent study found that volume changes

in the superior parietal cortex were correlated with dissociative symptoms (Irle et al., 2007). Thus CMS parietal changes in BPD, as in schizophrenia and ASD, may be particularly associated with delusional psychotic symptoms contributing to a disordered sense of self.

Some structural and activity/functional connectivity changes have been found in both frontal and parietal components of the MNS in BPD, although no problems with facial expression/gesture imitation have been reported (Lis et al., 2007;Korzekwa et al., 2009; Leichsenring et al., 2011). Similar to the other disorders, restingstate functional connectivity changes involving the IFG and the insula have been reported (Wolf et al., 2011). Increased functional connectivity between the left insula and both the anterior (mPFC) and posterior (PCC/precuneus) CMS has been found which correlated with scores on the dissociative tension scale (Wolf et al., 2011). Furthermore, increased bilateral activation in the insula of BPD patients has been reported during an emotional empathy task (Dziobek et al., 2011). Another study has investigated effects of recalling autobiographical memories of resolved compared with unresolved life events in BPD patients (Beblo et al., 2006). This also found increased bilateral insula activation as well as in the IFG when contrasting the difference between responses to unresolved vs. resolved life events in patients vs. controls. However, decreased IFG activity has also been reported in BPD patients during a theory of mind task involving emotional attributions (Mier et al., 2013) and in response to induced aggression (New et al., 2009). Finally some evidence for decreased functional connectivity between the left PCC and the IFG (i.e., the anterior MNS) has been found during pain processing in BPD patients (Kluetsch et al., 2012). Only one study has found evidence for reduced activation of the posterior MNS (IPS) in BPD patients during a task involving distancing from negative emotion pictures (Koenigsberg et al., 2009).

Overall therefore, there is increasing evidence for hyperactivation in the insula in the frontal MNS regions which may be particularly associated with altered self-processing in BPD, although there also appear a number of alterations involving the IFG. Interestingly BPD is the only one of the four disorders reviewed here where insula activity and connectivity with the CMS is increased since in schizophrenia, ASD, and depression it is decreased. Also changes in the insula connectivity changes in BPD have only been reported in the left hemisphere. As with the CMS however, more studies are needed to clarify the precise changes occurring in the MNS, as well as its interactions with the CMS, that are specifically associated with identity disturbance in BPD.

While one study has reported a reduced size of the isthmus of the corpus callosum (which connects parietal and temporal lobes) in BPD patients, they had co-morbidity with PTSD (Rüsch et al., 2007), and another study failed to find any evidence for altered corpus callosum structure in first episode BPD patients (Walterfang et al., 2010). A more focused study using diffusion tensor imaging has reported a specific reduction in inter-hemispheric fibers connecting the AC in BPD, although this too involved patients with PTSD co-morbidity (Rüsch et al., 2010). Thus at this point it seems unlikely that altered IHC contributes specifically to disordered self-processing in BPD itself.

A summary of the main changes in self-processing neural networks in BPD is provided in **Figure 2D** and **Table 1**. While some degree of caution is required in drawing overall conclusions about the precise pattern of changes occurring, due to the relatively small number of studies carried out and co-morbidity problems, studies have found altered activity and task-responsivity in frontal and posterior CMS regions (particularly the AC), although the direction of observed changes is somewhat inconsistent. On the other hand there is increasing evidence for hyper-responsivity and functional connectivity in the insula in the MNS, while the IFG generally shows either reduced or increased activity. There is also some evidence for reduced activity in the IPL. While there is evidence for structural and some functional changes in parietal CMS regions (PCC/retrosplenial cortex and precuneus) at this point it is probable that these may be contributed to by schizoid comorbidity rather than BPD *per se*. Co-morbidity issues may also apply to reported changes in IHC.

Thus at this point the main changes observed in BPD itself would appear to reside in frontal regions of the CMS and MNS self-processing systems, with a distinguishing feature being left hemisphere dominated increased insula activity and functional connectivity with the CMS. A common feature between BPD and schizophrenia is also reduced connectivity between the IFG and posterior CMS which may also reflect the importance of reduced integration between anterior and posterior networks in self-processing dysfunction. Given the roles of the AC and mPFC in both control of affective responses and impulsivity, both of which show impairments in BPD (Leichsenring et al., 2011), it could be speculated that there may be potential overlap between disordered self-identity and affective and impulse control in these regions. Interestingly, there is a significant correlation between identity disturbance and affective instability but not with impulsive-aggression in BPD (Koenigsberg et al., 2001), which suggests a possible interaction between disordered self-processing and affective control in BPD. However, fronto-amygdala pathways are of most importance in the latter, and indeed amygdala hyperresponsivity to negative emotional stimuli is a key feature of BPD (Lis et al., 2007; Korzekwa et al., 2009; Leichsenring et al., 2011). On the other hand fronto-amygdala pathways do not appear to play a significant role in self-processing.

# **CONCLUSION AND FUTURE DIRECTIONS**

Overall it is clear that disordered self-processing in schizophrenia, ASD, depression, and BPD is associated with alterations in the CMS although the patterns of changes are somewhat different. A summary of these changes in **Figure 2** and **Table 1** shows that in schizophrenia, ASD, and BPD there is general evidence for reduced activity in the mPFC whereas in depression it is increased. The same pattern is seen for the AC except in BPD where conflicting findings have been reported. On the other hand, in the posterior parietal cortex part of the CMS activity changes in all four disorders are more varied, although with schizophrenia and depression showing a more consistent pattern of increase. A key feature when comparing the disorders is that resting-state functional connectivity between frontal and parietal regions of the CMS is decreased in schizophrenia and in ASD patients but increased in depression and unchanged in BPD. In schizophrenia, functional connectivity between frontal MNS regions (insula and IFG) and the posterior CMS is also reduced and thus in this disorder there is an almost complete disconnection between anterior and posterior parts of the CMS and MNS. Another unique feature of schizophrenia is that functional connections between the posterior parts of the CMS and MNS are increased. Thus, there is support for the view that there is a widespread functional shift from anterior frontal to posterior parietal parts of both the CMS and MNS in schizophrenia which may contribute to the severity of selfprocessing dysfunction in this disorder. On the other hand in the two other disorders with identity disturbance, ASD and BPD, neither has dysfunction in both the anterior and posterior CMS and MNS systems. Weakened functional connectivity in ASD is mainly restricted to the CMS, although with some reduced connectivity between anterior parts of the two systems, and in BPD only altered functional connectivity between the anterior and posterior MNS occurs. While functional connections between both of the anterior and posterior components of the CMS and MNS systems are altered in depression they show a degree of balance, with increases in the CMS and decreases in the MNS. This suggests that integration between processing in anterior and posterior regions is maintained, although with a bias toward CMS dominance which may act to promote excessive rumination and negative mood but without identity disturbance. Interestingly task-based studies in depressed patients suggest a degree of dissociation between responses in anterior and posterior parts of the CMS and also differential sensitivity to anti-depressant medication. This further underlines the importance of maintaining integrated functioning between frontal and posterior networks for optimal self-processing and suggests that different neurochemical signaling systems may be involved in regulating functional changes in each of them. Thus overall the patterns of changes observed in the four different disorders support a general hypothesis that self-identity disturbances in particular may primarily result from any breakdown in integrated interactions between the frontal and posterior components of both the CMS and the MNS. The severity of identity disturbance may depend on the extent to which disconnection of frontal and posterior components of both the CMS and MNS occurs.

There is increasing evidence that connectivity between the frontal and posterior parts of the CMS is disrupted during anesthesia or brain-damaged induced loss of consciousness (Boveroux et al., 2010; Vanhaudenhuyse et al., 2010) and that DMN function (Anticevic et al., 2012) and brain functional connectivity (Stephan et al., 2009) is influenced by NMDA-receptor signaling. As such, reduced connectivity in psychiatric disorders may produce disorders of both self and consciousness, which is particularly relevant in relation to schizophrenia (Sass and Parnas, 2003) where functional dysconnectivity has been associated with aberrant NMDA-receptor signaling (Stephan et al., 2009). NMDAreceptor antagonists, such as the dissociative ketamine, can elicit schizophrenia symptoms in healthy subjects and disrupt taskdependent fronto-parietal functional connectivity (Anticevic et al., 2012). Treatments with NMDA-receptor agonists have also produced some positive results in reducing schizophrenia symptoms (Tsai and Lin, 2010) as well as in ASD (Posey et al., 2004). The rapid anti-depressant effects of ketamine might be potentially explained by a reduction in the abnormally increased functional connectivity between anterior and posterior regions of the CMS in depression. This has received some recent support from a study showing that ketamine does indeed reduce functional connectivity

between the AC/mPFC and PCC in the CMS (Scheidegger et al., 2012). Impairments in NMDA-receptor function are also thought to play a role in BPD (Grosjean and Tsai, 2007). Clearly this is an important focus for future research and it will also be interesting to investigate the specific effects of NMDA-receptor treatments on self-processing dysfunction in these psychiatric disorders.

At this point the specific contribution of the MNS to disordered self-processing in schizophrenia, ASD, depression, and BPD is still difficult to assess, and caution is obviously required in making any broad assumptions that altered functioning in any MNS region relates to dysfunctional mirror neuron properties, since these regions are involved in other cognitive and emotional functions. Given the presence of impaired mimicry and other motor functions in schizophrenia and ASD, it is reasonable to suggest that changes in frontal (IFG and insula) and parietal (IPL/SMG) MNS regions and their links to pre-motor and motor cortices may contribute both to an impaired sense of physical self and self-other action attribution, particularly as a result of reduced temporal contiguity between perception/intention and action processing. Furthermore, enhanced functional connectivity between the parietal MNS and CMS in schizophrenia may serve to exacerbate the severity of symptoms of physical self-disorder, and perhaps help extend them more pervasively into cognitive and emotional domains. In depression, only relatively minor effects on face emotion mimicry have been reported and it is therefore unlikely that these reflect reduced temporal contiguity in perception-action processing as opposed to a general reduction in attention and responsivity to external stimuli. In this respect it is interesting that unlike the mixed pattern of changes in schizophrenia and BPD functional connectivity between the MNS and CMS is consistently reduced in depression. As already mentioned, this may perhaps reflect an increased dominance of the CMS over MNS self-processing systems in depression but without resulting in significant conflict between them which may be occurring in schizophrenia and BPD as a result of differential patterns of change.

Changes in IHC are also most evident in schizophrenia and appear to involve reduced connections between both frontal and parietal regions via the corpus callosum. Since the main aspect of self-processing that is affected by callosal damage and atypical cerebral lateralization is a sense of agency (Asai et al., 2011; Uddin, 2011), one can speculate that misattribution of agency in schizophrenia may be at least partly a consequence of reduced IHC. However, this remains to be established. In ASD, reduced connectivity via anterior/medial regions of the corpus callosum, which primarily link frontal areas, may also serve to further increase disordered self-processing resulting from frontal dysfunction, and it is interesting that many individuals with callosal agenesis have high scores on the Autism Spectrum Quotient. However, once again the precise contribution of changes to IHC on altered selfprocessing *per se* require further studies. With BPD on the other hand reported reductions in IHC may only occur in patients with co-morbid ADHD and so are less likely to contribute to sense of identity problems in this disorder.

From this review it can be seen that while some progress has been made toward identifying the neural correlates of abnormal self-processing in different psychiatric disorders, there is an urgent need for more future studies to include better assessments of specific aspects of self-processing which will permit more precise functional correlations between neural and behavioral changes to be made. Overall, studies serve to confirm the importance of the CMS in self-processing that is being increasingly established by studies using healthy subjects, although they also indicate that involvement of the MNS and IHC, and interactions between them and the CMS may be of key importance. It would seem therefore that while many different neural systems contribute to dysfunctional self-processing in human psychiatric disorders, some common and differential patterns of altered activity and functional connections involving the CMS, MNS, and IHC systems are

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# **ACKNOWLEDGMENTS**

This work was supported by an National Natural Science Foundation of China (NSFC) Grant to Keith M. Kendrick (Grant No: 91132720).

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 29 May 2013; paper pending published: 24 June 2013; accepted: 01 August 2013; published online: 15 August 2013.*

*Citation: Zhao W, Luo L, Li Q and Kendrick KM (2013) What can psychiatric disorders tell us about neural processing of the self? Front. Hum. Neurosci. 7:485. doi: 10.3389/fnhum.2013.00485 Copyright © 2013 Zhao, Luo, Li and Kendrick. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# HUMAN NEUROSCIENCE

# Self-referential processing, rumination, and cortical midline structures in major depression

# **Ayna Baladi Nejad1,2\*, Philippe Fossati 2,3 and Cédric Lemogne1,4,5**

<sup>1</sup> AP-HP, Service Universitaire de Psychiatrie de l'Adulte et du Sujet Âgé, Hôpitaux Universitaires Paris Ouest, Paris, France

<sup>2</sup> USR 3246, CR-ICM, CNRS, Université Pierre et Marie Curie Paris-VI, Paris, France

<sup>3</sup> AP-HP, Service de Psychiatrie d'Adultes, GH Pitié Salpêtrière, Paris, France

<sup>4</sup> Faculté de Médecine, Sorbonne Paris Cité, Université Paris Descartes, Paris, France

<sup>5</sup> U894, Centre Psychiatrie et Neurosciences, INSERM, Paris, France

#### **Edited by:**

Georg Northoff, University of Ottawa, Canada

#### **Reviewed by:**

Pengmin Qin, University of Ottawa Institute of Mental Health Research, Canada Yvette Sheline, Washington University School of Medicine, USA

#### **\*Correspondence:**

Ayna Baladi Nejad, Brain and Spine Institute, CR-ICM, Hôpital de la Pitié-Salpêtrière, 47 Boulevard de l'Hôpital, Paris 75013, France e-mail: aynanejad@gmail.com

Major depression is associated with a bias toward negative emotional processing and increased self-focus, i.e., the process by which one engages in self-referential processing. The increased self-focus in depression is suggested to be of a persistent, repetitive and self-critical nature, and is conceptualized as ruminative brooding. The role of the medial prefrontal cortex in self-referential processing has been previously emphasized in acute major depression. There is increasing evidence that self-referential processing as well as the cortical midline structures play a major role in the development, course, and treatment response of major depressive disorder. However, the links between self-referential processing, rumination, and the cortical midline structures in depression are still poorly understood. Here, we reviewed brain imaging studies in depressed patients and healthy subjects that have examined these links. Self-referential processing in major depression seems associated with abnormally increased activity of the anterior cortical midline structures. Abnormal interactions between the lateralized task-positive network, and the midline cortical structures of the default mode network, as well as the emotional response network, may underlie the pervasiveness of ruminative brooding. Furthermore, targeting this maladaptive form of rumination and its underlying neural correlates may be key for effective treatment.

**Keywords: major depression, rumination, self-referential processing, neuroimaging, fMRI, medial prefrontal cortex, anterior cingulate cortex, default mode network**

# **INTRODUCTION**

Major depressive disorder, or unipolar depression, is the greatest single contributor of all disease burden in the European Union (Wittchen et al., 2011). It is characterized by feelings of sadness and helplessness, anhedonia, lack of motivation, and social withdrawal. Early cognitive theories of depression posited that negative affect arises from the discrepancy between one's internal representation of oneself, the perceived self, and one's desired goals and attributes, the ideal self (Duval and Wicklund, 1972; Pyszczynski and Greenberg, 1987; Carver and Scheier, 1998; Higgins, 1999). There seems now to be a general consensus that an increased negative self-focus can lead to depression. Moreover, compared to healthy individuals, depressed patients have been found to attend more to negative stimuli and also to better recall negative stimuli than positive ones (Williams et al., 1996). For instance, in visual dot-probe tasks with emotional face stimuli, reaction times have been found faster for sad faces than neutral faces suggesting that depressive patients tend to direct attention to negatively valenced information (Gotlib et al., 2004). In depression, negative bias seems already apparent below the level of conscious awareness as evidenced by increased amygdala reactivity to masked sad faces (Victor et al., 2010). These biases could translate to an increased salience of negative life events that can reinforce the perceived shortcomings of

the self, and if such things are dwelled upon, the individual is eventually drawn into a depressive episode (Teasdale, 1985).

The repetitive thinking and focus on negative mood states is referred to as rumination (Nolen-Hoeksema et al., 1993). There is a large body of observational and experimental evidence suggesting a reciprocally reinforcing relationship between rumination and negative affect (Mor and Winquist, 2002). Rumination tends to increase when negative emotions are up-regulated (Ray et al., 2005). In depressive patients, levels of rumination have been associated with the severity and duration of depressive episodes (Nolen-Hoeksema et al., 2008). Also, increased levels of rumination have been found to increase the risk of depressive relapse in remitted patients (Roberts et al., 1998).

Although content in ruminative thought is typically retrospective and self-depreciating (Watkins and Moulds, 2005), not all components of ruminative thinking are necessarily harmful (Treynor et al., 2003). The component referred to as "selfreflection" can be adaptive if the sense of agency in bettering one's standing is retained. The maladaptive components of rumination are referred to as "brooding" and "depressionrelated," and are associated with a greater negative bias (Joormann and Gotlib, 2006). Therapeutic interventions specifically targeting these maladaptive components of rumination, such as mindfulness-based cognitive therapy, have been found effective in preventing depressive relapse (Teasdale et al., 2000; Ma and Teasdale, 2004; Bondolfi et al., 2010).

Rumination is a form of self-referential processing, which is the process of relating information to the self. In neuroimaging, self-referential processing has been associated with the medial prefrontal cortex, anterior and posterior cingulate cortex, insula, temporal pole, hippocampus, and amygdala (Gusnard et al., 2001; Kelley et al.,2002; Fossati et al.,2003;Phan et al., 2004;Ochsner and Gross, 2005; Johnson et al., 2006; Schmitz and Johnson, 2006; van der Meer et al., 2010). In a meta-analysis of neuroimaging studies focused on self-referential processing, Northoff et al. (2006) found that commonly activated regions lie in dorsal and ventral areas of the medial prefrontal and anterior cingulate cortices, as well as the posterior cingulate cortex and precuneus. These regions have been termed cortical midline structures (Northoff and Bermpohl, 2004) and somewhat overlap with the intrinsic default mode network (Raichle et al., 2001; Spreng and Grady, 2010; Qin and Northoff, 2011). The default mode network is found in resting state functional imaging and as a deactivated network in functional imaging during cognitive task performance (Fox et al., 2005; Smith et al., 2009). When the brain is at rest, i.e., not engaged in externally driven cognitive processing, then self-referential processing is believed to predominate (Gusnard et al., 2001) and more activity in the default mode network is observed.

Here, we present a review of the neuroimaging literature (up until April 2013) investigating rumination or self-referential processing in major depressive disorder. These studies are discussed together with related literature that might help to elucidate the role of cortical midline structures in major depression and maladaptive self-focus. Firstly, we will review functional magnetic resonance imaging (fMRI) studies that have addressed the role of the cortical midline structures during self-referential processing in major depression. These studies are separated according to a discussion implicating cortical midline structures, and a discussion of the modulatory dynamics between the cortical midline structures, the amygdala, and the dorsolateral prefrontal cortex. Furthermore, we summarize results from resting state functional connectivity data that suggest abnormalities of the default mode network function and its relationship with the task-positive network in major depression, which could lead to maladaptive self-focus. Finally, we will consider evidence suggesting that antidepressant treatments target the neural bases of self-referential processing and rumination in their therapeutic effects.

#### **SELF-REFERENTIAL TASKS IMPLICATING CORTICAL MIDLINE STRUCTURES IN MAJOR DEPRESSION**

Rumination has been found associated with the cortical midline regions, especially the more anterior portion. Kross et al. (2009) asked healthy subjects to adopt different thought processing strategies when recalling negative autobiographical memories during fMRI. The strategy which induced rumination, the repetitive and negatively toned style of self-referential processing, was found to increase neural activity in the subgenual anterior cingulate cortex and medial prefrontal cortex when compared

to non-ruminative conditions. In addition, these same cortical midline structures have been implicated in the pathophysiology of depression. In a meta-analysis of 64 structural magnetic resonance imaging studies, the greatest brain volume reductions in depression were found in the anterior cingulate cortex and orbital frontal cortex (Koolschijn et al., 2009). Functional imaging with positron emission tomography (Videbech, 2000) and magnetic resonance imaging (Mayberg, 2002; Drevets et al., 2008) has also implicated cortical midline regions, the anterior portion in particular, in the pathophysiology of major depressive disorder.

More specific to rumination, functional imaging studies which experimentally probe self-referential processing have identified anterior cortical midline structures as key areas of dysfunction in depression (Lemogne et al., 2012). In one study (Grimm et al., 2009), positive and negative picture stimuli were presented to depressed patients and healthy comparison subjects under two conditions: passive viewing, and self-related judgment where subjects responded yes or no as to whether they could personally relate to the picture shown. Patients with depression compared to healthy control subjects were found hypoactive in cortical midline structures such as the dorsomedial prefrontal cortex and supragenual anterior cingulate cortex, as well as the dorsomedial thalamus and ventral striatum, during self-referential processing.

Instead of emotional picture stimuli, positive and negative personality trait words have also been presented to subjects under similar conditions where they were required to make a judgment as to whether or not the word applied to them. Using this task with a control condition requiring subjects to judge whether the word was a socially desirable trait or not, Lemogne et al. (2009) found that patients with unipolar depression recruited an extended portion of the anterior cortical midline structures. A part of the dorsomedial prefrontal cortex, which was not recruited by control subjects for self-referential processing, was found increased in activity during the self-judgment condition in depression patients. Interestingly, the dorsomedial prefrontal cortex appeared to remain hyperactive during self-referential processing in a small subsample who were re-scanned several weeks later (Lemogne et al., 2010). In a separate study using a similar task but with a control condition asking whether the trait word describes the current prime minister of the subjects' country (Yoshimura et al., 2010), patients with major depressive disorder were found to exhibit hyperactivity in the medial prefrontal and rostral anterior cingulate cortices in the condition where they were asked to make a self-judgment for a negative trait word. These regions were hypoactive in comparison to healthy control levels in trials where positive trait words were presented.

Johnson et al. (2006) dissociated brain regions related to the type of content in self-referential processing in healthy control subjects, but, in a later study, found that these dissociations seemed not to apply for major depression patients. Self-referential thought related to hopes and aspirations tended to be associated with the anterior midline regions whereas self-referential thought related to duties and obligations was associated with the posterior cortical midline regions. In acutely depressed patients, the two kinds of self-related thoughts were not differentiated to the same extent as in control subjects (Johnson et al., 2009). This seemed to have been due to patients displaying hyperactivity during the control condition which led to less signal change in both self-related conditions. This pattern of activity was associated with a self-reported measure of rumination. With the same subjects they also investigated the distinction made by Watkins (2008) between two forms of self-focus: analytical self-focus – abstract thinking relating to the extended, narrative self – and experiential self-focus – concrete thinking concerned with one's current state. The analytical type of self-focus, similar to ruminative brooding, has been suggested to evoke negative self-referential thoughts in major depression. Patients with depression tended to display hypoactivity in the medial prefrontal and anterior cingulate cortices during both analytical and experiential conditions as well as hyperactivity in these regions during the control condition. This activity pattern was again stronger for higher rumination scorers (Johnson et al., 2009).

In another study (Cooney et al., 2010), subjects were prompted to ruminate by being asked to think about statements relating directly to their sense of self. This condition was contrasted with when subjects were asked to think about abstract (e.g., the idea of team spirit) or concrete statements (e.g., seeing shampoo bottles on a store shelf). Patients with depression revealed to be hyperactive during rumination-induction in anterior and posterior cingulate cortex, as well as the dorsolateral prefrontal cortex, amygdala, parietal, temporal, and occipital lobes. In a study by Kessler et al. (2011), personally relevant material were gathered from intimate interviews and later presented to unmedicated depressed patients and healthy controls during fMRI. Compared to controls, patients were found to display greater activation of the medial prefrontal cortex but also, amongst other areas, the amygdala, raising the question of brain dynamics between cortical and limbic regions during self-referential processing in depression.

#### **THE INTERPLAY OF CORTICAL AND LIMBIC REGIONS DURING SELF-REFERENTIAL PROCESSING IN DEPRESSION**

As well as cortical midline regions, the amygdala has been found abnormally recruited during self-referential processing in depressed patients (Cooney et al., 2010; Kessler et al., 2011). In a study solely investigating amygdala function, the bilateral amygdala response to self-referent emotional stimuli in remitted patients who underwent sad mood induction was found to predict the later increased recall of negative self-referential material (Ramel et al., 2007). This finding suggests an important role for the amygdala in the maintenance of depressive-related thought.

During a self-referential processing task where personally relevant negative, positive, and neutral words previously generated by the subject were presented during functional imaging, the amygdala exhibited a more sustained response to emotional stimuli in depressed patients and negatively correlated with rumination scores (Siegle et al., 2002). Along with the amygdala, the left hippocampus and dorsolateral prefrontal cortex also exhibited a more sustained response during self-referential processing. The dorsolateral prefrontal cortex is involved in the inhibition of limbic regions for the regulation of emotional response (Ochsner et al., 2012). However, considering that there are no direct anatomical connections between the amygdala and dorsolateral prefrontal cortex, the relationship is perhaps mediated by the medial prefrontal and anterior cingulate cortices. Animal studies examining anatomical connectivity of the amygdala have found, consistent over the different mammalian systems studied, prominent reciprocal connections to the medial prefrontal cortex with more elaborate amygdaloid connectivity to the forebrain in primate species (Price, 2003). Indeed, Siegle et al. (2007) in a follow-up study found that the variance of amygdala activity could be better explained by the activity of the anterior cingulate cortex than the dorsolateral prefrontal cortex. This study further found the anterior cingulate cortex hyperactive in response to negative stimuli and that the functional connectivity of the anterior cingulate cortex to the amygdala and to the dorsolateral prefrontal cortex was reduced in patients compared to controls.

Another study has found an increased connectivity between the amygdala and the medial prefrontal cortex in depression patients performing a self-referential word task (Yoshimura et al., 2010). However, in unmedicated depressed patients, functional connectivity between the amygdala and medial prefrontal cortex was observed decreased during rest and passive emotional picture-viewing (Anand et al., 2005). The conflicting findings of the latter two studies might be explained by a difference in the self-relatedness of the respective task stimuli. Self-referential processing might be modulating the amygdala and medial prefrontal connectivity, and differentially so in depressed patients compared to control subjects. Indeed, genetic liability for depression seems to influence the extent of the modulation derived from self-relatedness (Lemogne et al., 2011b). However, the different medication status of subject samples in these studies does not allow the ruling out of antidepressant drugs also exerting a modulatory influence on functional connectivity.

Findings from one study have also suggested that amygdala activity in depression was only disrupted in the negative selfreferential condition, whereas abnormality in dorsolateral prefrontal and anterior cingulate cortices was found to be general and spanned across all conditions (Hooley et al., 2009). In this study, subjects were imaged while presented with recordings of their mothers either praising, or criticizing them, or discussing a neutral subject. Remitted, formerly depressed patients displayed hyperactivity in the amygdala during criticism but displayed hypoactivity in the dorsolateral prefrontal cortex and anterior cingulate cortex in all conditions compared to healthy individuals. This decreased prefrontal involvement in the task might indicate decreased cognitive control over emotional responsiveness in the remitted patients which might further explain the hyperactive amygdala response during the criticism condition.

In a self-referential task with personality trait words, Lemogne et al. (2009) found the medial prefrontal cortex displayed greater functional connectivity with the dorsal anterior cingulate cortex and the dorsolateral prefrontal cortex in patients with depression compared to controls. A study with healthy individuals (Wagner et al., 2012) found activity of the rostral anterior cingulate cortex to negatively co-vary with the activity in the dorsolateral prefrontal cortex. The activity in rostral anterior cingulate cortex was linked to negative self-referential processing and associated with depressive symptom severity. As will be later discussed, the rostral anterior cingulate cortex seems important for treatment response in depression (Pizzagalli, 2011; Fu et al., 2013) and perhaps this is due to its possible role as a hub between the limbic, the self-referential, and the cognitive control networks.

## **RESTING STATE INTER-REGIONAL DYNAMICS OF CORTICAL MIDLINE REGIONS IN MAJOR DEPRESSION**

Aberrant rest-stimuli interactions has been suggested as a core dysfunction in depression which could underlie many of the symptoms including increased negative self-focus (Northoff et al., 2011). One study comparing whole-brain functional brain connectivity to a default mode network node in depressive patients and healthy control subjects, only found abnormal connectivity during the rest epochs and not during epochs of emotional word recall (Berman et al., 2011). This is also in line with the previously mentioned studies of self-referential processing suggesting that depression patients exhibit abnormal activity already during control conditions (Hooley et al., 2009; Johnson et al., 2009).

However, activity within rest epochs have been found to be dependent on the cognitive processing of the preceding condition. For example, task difficulty in working memory conditions affects subsequent rest periods (Pyka et al., 2009, 2012), but perhaps more relevant here, the self-relatedness of stimuli has also been found to affect subsequent rest periods (Schneider et al., 2008). If depressive patients differentially process emotional stimuli then it would follow that the rest epochs would also differ from comparison subjects. Furthermore, depressed patients might also have a more sustained neural response to emotional/self-referential stimuli, as Siegle et al. (2002)suggest, which could spill over into rest periods.

Most of functional brain imaging in present times use magnetic resonance imaging to pick up changes in the blood oxygenation level-dependent (BOLD) signal, a proxy for neural activity. Task activation studies traditionally use a mass-univariate general linear modeling approach to contrast implicit resting baselines to task-related activity peaks, i.e., relative signal changes are measured. With resting state activity there are no experimental parameters to which to model BOLD activity. Activity fluctuations are seen in relation to other regions in the brain with the assumption that regions with similar brain activity patterns are communicating with each other, i.e., the degree of functional connectivity between regions is measured. The resting state connectivity of parcellated brain regions, as assessed by correlation coefficients, within the default mode network, as well as the affective network, visual cortex, and cerebellum, were found to be highly discriminative of patients with depression from healthy control subjects using a multivoxel pattern classifier (Zeng et al., 2012). Differences in functional connectivity during resting state between patient and control groups could suggest that aberrant activity in depression is intrinsic and not only related to selfreferential processing. Alternatively, connectivity differences could be reflective of qualitatively different thought content during rest in depressed compared to healthy individuals. Furthermore, resting state connectivity might be affected by antidepressant drugs and/or depressive episode duration. Increased resting state functional connectivity of the precuneus and the thalamus to the rest of the default mode network was found in depressed patients, and this increase also correlated with the duration of depressive episode (Greicius et al., 2007). Default mode network dysconnectivity was, however, already apparent in treatment-naïve patients with first-episode depression (Zhu et al., 2012). These latter two studies were similar in that they both used independent component analysis to investigate resting state activity but they differed in the direction of the dysconnectivity finding in patients. Whereas Greicius et al. found increased default mode network connectivity of posterior regions, Zhu et al. found posterior default mode network connectivity to be decreased in patients compared to healthy control subjects.

The Zhu et al. (2012) study also found default mode network connectivity in the anterior regions, ventral medial prefrontal, and anterior cingulate cortices, to be increased in depression compared to healthy control levels and this was also positively correlated with rumination scores. In another resting state study of depressive patients (Sheline et al., 2010), the dorsomedial prefrontal cortex, was found to exhibit an increased connectivity to seed regions representative of the cognitive, default mode, and affective networks suggesting that the anterior cortical midline might mediate the dysfunction of these networks which has been previously reported in depression. In a seed-based functional connectivity analysis of anterior cingulate resting state activity in young depressive patients, Davey et al. (2012) also found that the dorsomedial prefrontal cortex displayed increased connectivity, which the authors suggest could be reflective of the increased self-referential processing in patients.

A dysfunctional dorsolateral prefrontal cortex has been implicated as perhaps a precursor to the hyperactive midline cortical processing found in depression (Marchetti et al., 2012). The resting state functional connectivity between the dorsolateral prefrontal cortex and anterior cingulate cortex was found increased in depressive patients, which might suggest altered cognitive regulation processes that can lead to the negative self-focus in depression (Davey et al., 2012). In support of a cognitive disinhibition leading to increased rumination, many task activation studies which have probed self-referential processes in depression patients have also found anomalies in the dorsolateral prefrontal cortex, a key node of the task-positive, cognitive control network (Siegle et al., 2007; Lemogne et al., 2009; Cooney et al., 2010; Yoshimura et al., 2010; Kessler et al., 2011). Additionally, one study found that the integrity of superior longitudinal fasciculus (the frontoparietal fiber tract) was compromised in major depression patients and the degree of white matter integrity was negatively correlated with rumination scores (Zuo et al., 2012).

Cognitive control,or the lack of it,seems to also be an important factor in determining the degree of rumination a healthy individual normally engages in. In a task activation study with healthy subjects performing an emotional go/no-go task (Vanderhasselt et al., 2011), those who were reported as high ruminative brooders exhibited increased dorsolateral prefrontal cortical activation compared to low ruminators. This might suggest greater cognitive recruitment to overcome the emotionality of the stimuli which tends to be more salient in those prone to rumination. Another study (Kuhn et al., 2012) found that rumination was associated with gray matter volume reductions in the anterior cingulate cortex and inferior frontal gyrus which also overlapped with regions whose functional connectivity during rest was associated with rumination. The authors suggest that the associations to these areas, which have roles in cognitive inhibition, are indicative of a deficit in the suppression of ruminative thought.

The dynamics between the cognitive network and the default mode networks can also be seen from a bottom-up perspective where increased maladaptive self-focus and thereby hyperactive cortical midline regions interfere with normal cognitive function. One resting state study using a metric of network dominance looked at the relationship between rumination and resting state networks in patients with depression (Hamilton et al., 2011). The authors found that the activity of the default mode network was more dominant than the cognitive, task-positive network in the resting state profiles of depression patients compared to healthy control subjects. The degree of dominance of the default mode network was also positively correlated with scores on maladaptive rumination and negatively correlated with the more adaptive, "self-reflective" rumination. Hence, this default mode network dominance could explain the invasiveness of rumination in depression.

## **SELF-REFERENTIAL PROCESSING AND CORTICAL MIDLINE STRUCTURES AS TREATMENT TARGETS**

The cortical midline structures have been found important for treatment response in depression. A strengthening of the connectivity between the anterior cingulate cortex and amygdala has been associated with symptom remission after antidepressant treatment in patients (Chen et al., 2008). Deep brain stimulation of the subgenual anterior cingulate cortex ameliorates symptoms in treatment-resistant depression (Mayberg et al., 2005). The same region's pre-treatment level of response to negative words has been found predictive of response to cognitive therapy in depression (Siegle et al., 2012). Also, the resting state activity of the rostral anterior cingulate cortex has been found predictive of pharmacological treatment response in depression whereas posterior midline areas predicted treatment non-response according to a meta-analysis of longitudinal studies in depression (Pizzagalli, 2011).

A self-referential task was used to study the acute effect of citalopram, a selective serotonin reuptake inhibitor, in high neuroticism scorers who are thought to be at increased risk for depression. After administration of citalopram, high neuroticism scorers displayed decreased activity in the medial prefrontal and rostral anterior cingulate cortices in response to negative selfreferential processing compared to high neuroticism scorers who had received a placebo (Di Simplicio et al., 2012). This study suggests that one mechanism by which antidepressants exert their action might be through the inhibition of negative self-referential processing in depression. A similar finding was reported in a study of remitted depression patients where neural response to negative emotional faces were attenuated in depression patients in remission compared to controls (Thomas et al., 2011). This study found that the neural response to negative stimuli was positively correlated with rumination scores which suggest that decreased neural activity is protective against rumination and hence depressive symptoms. In another study, which also found a positive correlation between negative stimuli neural response and rumination scores in remitted patients, the reactivity of the medial prefrontal cortex was further found to predict relapse status 18 months later (Farb et al., 2011). Similarly suggesting attenuated response to negative stimuli as therapeutic, healthy subjects were found to display reduced negative bias and reduced neural response to negative stimuli following a mindfulness task (Paul et al., 2013).

Another possible mechanism of action in antidepressants might be through increasing salience and neural processing of positive stimuli (Harmer et al., 2003, 2004; Miskowiak et al., 2007; Norbury et al., 2008). Yoshimura et al. (2013) found that, after cognitive behavioral therapy in depression patients, there was an increased neural response in the medial prefrontal and anterior cingulate cortices to positive, self-referential stimuli together with a decreased neural response in the same regions to negative stimuli. However, in a longitudinal investigation using a similar self-referential processing task as the latter, the medial prefrontal cortical hyperactivity found in a small sample of depressed patients did not change over weeks of antidepressant treatment (Lemogne et al., 2010). Additionally, a study with healthy subjects treated 3 weeks with escitalopram who performed a similar self-referential processing task, found the greatest treatment effect to lie in the precuneus and posterior cingulate cortex (Matthews et al., 2010). These discrepancies might result from the different therapeutic interventions, for example, acute versus prolonged antidepressant drug treatment, or antidepressant drug treatment versus cognitive behavior therapy.

# **DISCUSSION**

The anterior cortical midline structures, namely, medial prefrontal cortex and anterior cingulate cortex, seem implicated in the abnormal self-referential related activity of patients with major depression. This abnormality tends toward an increased level of activity. Studies finding decreased activity of these regions during self-referential processing in patients had also found increased activity in the comparison conditions (Hooley et al., 2009; Johnson et al., 2009), and therefore the apparent hypoactivity could be relative due to the statistical contrast. Overall, studies suggest that there is an aberrantly increased level of anterior cortical midline activity, if not during self-referential processing, then basally. There seems to be some discrepancy in the findings as to the specific localization within the anterior midline cortex of this dysfunction (see **Figure 1**). The discrepancy might be due to the broad range of tasks employed in the literature as well as the methods employed to analyze the data. Many studies opt for a region-of-analysis approach varying in their method of region selection. There is variability even in whole-brain analyses when it comes to statistical thresholding which might affect the reliability of some results. Also, some findings are based on small samples and this might also contribute to some inconsistencies in the literature.

Some studies have identified an abnormally increased responsiveness of the anterior cortical midline regions during specifically negative self-referential conditions (Siegle et al., 2007; Yoshimura et al., 2010, 2013; Wagner et al., 2012). However, studies have also reported a behavioral difference in conditions where a judgment needs to be made as to whether the positive or negative stimuli

is something the participant can personally relate to (Siegle et al., 2007; Grimm et al., 2009; Lemogne et al., 2009; Yoshimura et al., 2010). Patients with depression tend to personally relate to negative stimuli more often than control subjects, and also personally relate to positive stimuli less often than control subjects. No study to date has looked at whether the processing of self-related negative stimuli is abnormally recruiting the midline cortical region, or whether the abnormal activity reported in this region is a proportional, "normal" response in light of the behavioral differences between groups,where patients seem to be relating negative stimuli more often to the self than control subjects. If the latter is true then the activity in the cortical midline region might not be pathological *per se* but just reflect a normal neural reaction to negative self-related material. The accounting of behavioral differences will be an interesting avenue for future studies to explore.

There is growing evidence for dysfunctional interactions between regions related to emotion, self-referential, and higher cognitive processing. In animal neuroanatomical studies, prominent reciprocal connections have been identified between the medial prefrontal and anterior cingulate cortices and the amygdala as well as with the thalamus, ventral striatum, and hypothalamus (Ongur and Price, 2000). The interactions between these regions play a significant part in the regulation of emotional and visceral response, and are therefore implicated in the pathophysiology of mood disorders (Price and Drevets, 2010, 2012). In the self-referential task-related imaging literature, the anterior cortical midline structures also seem to be repeatedly identified as mediators between the amygdala, an area associated with emotional response, and the dorsolateral prefrontal cortex, an area associated with cognitive control and emotion regulation. The functional connectivity of the anterior cortical midline structures to the amygdala and dorsolateral prefrontal cortex has been found disrupted in patients with major depression (Anand et al., 2005; Siegle et al., 2007; Lemogne et al., 2009; Yoshimura et al., 2010; Wagner et al., 2012). The resting state literature in parallel offers support to the idea that disrupted cognitive control leads to intrusion of ruminative thought, and ruminative thought has been further associated with increased connectivity and activity of the

default mode network (Sheline et al., 2010; Hamilton et al., 2011; Davey et al., 2012; Marchetti et al., 2012). Rumination could stem from a top-down failure, where lack of inhibition from dorsolateral prefrontal regions to the anterior cingulate cortex allows free reign of ruminative thoughts. Or the failure could be a bottom-up process where overactive limbic regions tag negative emotionality and salience to experiences which lead to increased rumination and thereby to an interference with normal higher cognitive function and control. Although functional connectivity analyses have revealed dysconnectivity in major depression, more causal connectivity analyses could better identify the nature of this modulatory impairment.

The relationship between self-referential processing and abnormal activity in the cortical midline areas has not been replicated in medication-naïve patients to verify that the abnormality does not stem from antidepressant effects. One small pilot study examined whether these patterns of activation were stable over sustained antidepressant treatment (Lemogne et al., 2010). Additionally, one study examined the neural correlates of self-referential processing among a drug-naïve, at-risk for depression sample (Lemogne et al., 2011a). These latter two studies provided some evidence for trait-like hyperactivity in the dorsomedial prefrontal cortex. However, Yoshimura et al. (2013) recently found that this same region might be modulated by cognitive behavior therapy. Also, a study on at-risk, healthy subjects (high neuroticism scorers) found that hyperactive ventromedial prefrontal cortex response decreased after 7 days of citalopram treatment (Di Simplicio et al., 2012). Therapeutic effects of antidepressant treatment seem to be related to either a decreased neural response to negative self-referential stimuli or an increased response to positive self-referential stimuli. However, therapeutic actions of antidepressants on self-referential related activity have been more often than not studied in healthy individuals. Only a few longitudinal imaging studies have been conducted with patient samples. Also considering the delayed therapeutic response of antidepressants, a longer intervention period would be desirable in future studies in order to relate the therapeutic changes in self- and depressive-related symptoms with neural activity change.

# **CONCLUSION**

Although there may be some discrepancies between studies, there nonetheless seems to be a general convergence on the anterior cortical midline structures as playing an important role in maladaptive rumination in major depression. Evidence in support of this is derived from task-related as well as resting state data. Anterior cortical midline structures have been found to display abnormally increased activity usually in relation to negative selffocus. There is also evidence that activity within the cortical midline regions is associated with behavioral measures of rumination. The pervasiveness of ruminative thought in depression might be driven by a reduced top-down inhibition of the cortical midline and limbic regions, thereby allowing for the predominance of negatively charged and self-focused thought. In line with this, the dorsolateral prefrontal cortex has been found dysfunctional during self-referential processing and its dynamics with the emotional and self-referential associated brain regions seem also disrupted in depression. However, whether these disruptions arise from a topdown or a bottom-up mechanism is not yet clear. Moreover, too few longitudinal studies have been conducted in order to determine to what extent these neural dysfunctions are a precursor or a product of the depressive state, and to what extent does medication influence brain dynamics.

# **REFERENCES**


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# **Definition Box**

*Self-referential processing* is the cognitive process of relating information, often from the external world, to the self.

*Self-focus* refers to attention directed inwardly, to the self, as opposed to the external world.

*Rumination* is repetitive and distressful form of thinking that can be symptomatic of depression. Adaptive forms of rumination, however, have been identified where the content can be positive and can lead to problem resolution.

# **ACKNOWLEDGMENTS**

This work was supported by Assistance Publique – Hôpitaux de Paris (Département de la Recherche Clinique et du Développement), and funded by Programme Hospitalier de Recherche Clinique – Ministère de la Santé PHRC AOM11209, and Agence Nationale de la Recherche ANR 12 SAMA 011 01 SENSO and under the program "Investissements d'avenir" ANR-10-IAIHU-06.

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**Conflict of Interest Statement:** Ayna Baladi Nejad reports no potential conflicts of interest. Philippe Fossati has received grants from Servier and honoraria from Lundbeck and Servier. Cédric Lemogne has accepted paid speaking engagements in industry-sponsored symposia from Astra Zeneca, Lundbeck, Pierre Fabre, Pfizer, and Servier.

*Received: 03 May 2013; paper pending published: 20 June 2013; accepted: 24 September 2013; published online: 10 October 2013.*

*Citation: Nejad AB, Fossati P and Lemogne C (2013) Self-referential processing, rumination, and cortical midline structures in major depression. Front. Hum. Neurosci. 7:666. doi: 10.3389/fnhum.2013.00666*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Nejad, Fossati and Lemogne. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Self through the mirror (neurons) and default mode network: what neuroscientists found and what can still be found there

# *Stefano Sandrone1,2\**

*<sup>1</sup> NATBRAINLAB – Neuroanatomy and Tractography Brain Laboratory, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King's College, London, UK*

*<sup>2</sup> Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland*

*\*Correspondence: sandronestefano@ini.ethz.ch*

#### *Edited by:*

*Georg Northoff, University of Ottawa, Canada*

A search for the word *self* in the Stanford Encyclopedia of Philosophy finds 1187 entries: trying to give a complete definition of this concept is not so easy. It is a great puzzle that states who we are in the world, as Alice in Wonderland once argued, afraid she could not explain herself when she came across the Caterpillar. Unfortunately, we cannot use such an excuse. Furthermore, as neuroscientists, trying to depict the self from a scientific perspective seems to get harder and harder the deeper we get into our knowledge of the brain's structure and functions. Generally speaking, the self has been seen through different lenses, according to the dominant *zeitgeist*. Classical cross-cultural studies confirmed what was intuitively conceivable: the concept of the self is highly varied across social groups and across traditions, mainly clustered around the wellcharacterized dichotomy between western and eastern visions (Markus and Kitayama, 1991; Baumeister and Finkel, 2010; Martínez Mateo et al., 2013), where the first is considered more independent and the latter more interconnected. In recent years, research on the self has significantly increased thanks to the cross-fertilization of disciplines that were once considered separated, such as philosophy, psychology, psychiatry, and neuroscience (Gallagher, 2011) and, to a certain extent, all the other neuro-related disciplines such as neuroethics, neuroesthetics, and neuroeconomics (Legrenzi and Umiltà, 2011). Old questions can now be addressed through recently developed – and still improving – technological tools falling under the term "neuroimaging," such as positron emission tomography (PET) or functional magnetic resonance imaging (fMRI). As the self is by definition multifaceted and polyhedral both in space and time, the flourishing of new, twisted viewpoints is thus useful to further shape and deepen our knowledge on this intriguing topic. Remarkably, the investigation on the self benefits from two of the most recent discoveries, both of them claimed to be serendipitous, made in the highly interdisciplinary field of neuroscience: the Mirror Neuron System (MNS) and the Default Mode Network (DMN).

On the one side, the MNS mechanisms first unify execution and perception of an action, with a set of neurons, ranging from premotor and supplementary motor areas to primary somatosensory and inferior parietal cortices, coding for a precise action and activated also in the observers' motor system (Cattaneo and Rizzolatti, 2009; Keysers et al., 2010). Although it has been sometimes misinterpreted (Rizzolatti and Sinigaglia, 2010), MNS is crucial for the study of the self. In fact, frontoparietal mirror neuron areas are crucial for the motor-simulation mechanisms, as well as cortical midline structures engaged in selfrelated information processing (Uddin et al., 2007) both in normal and pathological brain, as it can be seen for example in autistic (Enticott et al., 2012; Gallese et al., 2013) and schizophrenic subjects (Ferri et al., 2012; McCormick et al., 2012; Mehta et al., 2012).

On the other side, since 2001 it has been understood that when an individual is alerted though not actively engaged in cognitive tasks, spontaneously organized neural activity occurs in a unique constellation of brain regions called DMN and involving the posterior cingulate cortex, the precuneus, and regions of the ventromedial prefrontal cortex (Raichle et al., 2001; for an account of its discovery please refer to Raichle and Snyder, 2007; Buckner, 2012). The DMN has been consistently reported to be related to self-referential processing. In fact, activations and deactivations of DMN brain regions have often been related to self-specific processes in both healthy and diseased conditions (Gusnard et al., 2001; Sheline et al., 2009; Irish et al., 2012). Each area of the DMN seems to be involved in different subfunctions of self-referential processing (van Buuren et al., 2010), and a detailed map of the anatomo-functional DMN subregions is currently in progress (Salomon et al., 2013).

Even though some methodological caveats should be properly addressed and hopefully solved in the next years as far as resting states are concerned (Northoff et al., 2010, 2011), it is more and more evident that the boundaries between the perception of the "self" and the "other" should be pivotally found (also) around the CMS. Furthermore, being directly involved into both MNS and DMN, the self is at a crossroads between these two discoveries, and it is conceivable that in the near future such research on the self will be better valorized and further propelled through new insights that can directly derive from studying the MNS and DMN. The relationship between MNS and the self as well as its links with the study of the self and internal/external stimuli started to be discussed both for MNS (Sinigaglia and Rizzolatti, 2011) and DMN (Qin and Northoff, 2011), but a synergy between researchers from different subfields (of neuroscience and above) is strongly required to further look at the self through the mirror neurons and the DMN looking glass.

Remarkably, the first evidence of mirror neurons was obtained in monkeys with electrophysiological studies (di Pellegrino et al., 1992) and then replicated on man with neuroimaging techniques (Kilner et al., 2009; but see also Lingnau et al., 2009), electrophysiological recordings (Mukamel et al., 2010), and cerebral stimulation devices (Cattaneo et al., 2010; Avenanti and Urgesi, 2011). Instead, the opposite happened for the DMN. Experiments were carried out first on humans, then on chimpanzees (Rilling et al., 2007), monkeys (Kojima et al., 2009; Mantini et al., 2011) and, more recently, on rats (Lu et al., 2012), thus suggesting that DMN can be a crucial aspect of the mammalian brain. Replicating the data obtained from the "Mirror Test" (Gallup, 1970, 1994; Gallup et al., 2004) and investigating the emerging self, MNS, and DMN while performing the test or during the resting state may provide deep insight, and may help describe the emergence of the self from an evolutive perspective. Moreover, DMN activity has been longitudinally elucidated across the whole life cycle, namely from its emergence in 2-day-old newborns (Gao et al., 2009) to its disappearance in dead brain patients (Boly et al., 2009). Similarly, the ontogeny of social relationship has been addressed from twin fetuses (Castiello et al., 2010) onward (Kilner and Blakemore, 2007; Lepage and Théoret, 2007). Therefore, the developmental and maturational processes and the boundaries of the self can be further addressed with a combined MNS and DMN approach. In addition, both MNS and DMN seem to be altered in neurological and psychiatric conditions (Iacoboni and Dapretto, 2006; Sandrone, 2012, 2013), and, interestingly, abnormalities and disruptions recently started to be studied as predictive behavioral markers and clinical diagnostic tools. Future investigations will be aimed at capitalizing on clinical studies on neurological and psychiatric patients in order to improve the ability of DMN in discriminating single patients from single healthy controls with increasing sensitivity and high specificity, and if possible, to realize a joint MNS and DMN-based functional taxonomy of self-related diseases. Variations in the functional connectome will then hopefully be further linked and attributed to clinical variables as well (Castellanos et al., 2013), in the framework of the widely spreading connectomic approach (Griffa et al., 2013) and of the future development of recently emerged biological technique (Chung and Deisseroth, 2013; Chung et al., 2013).

There are very good premises to add new chapters in the challenging pursuit of the boundaries of the self in the brain. A work on the self deals with the more intimate meaning of mankind and, quoting the writer Lewis Carroll, will make all of us once again "curiouser and curiouser" toward the wonderland of neuroscience.

#### **Acknowledgments**

Many thanks to Chiara Balestri, Marta Boerci, Saee Paliwal and Mathias Bannwart for their thoughtful comments on the manuscript.

#### **References**


knowledge. *Conscious. Cogn.* 21, 1365–1374. doi: 10.1016/j.concog.2012.05.001


*Prog. Neurobiol.* 92, 593–600. doi: 10.1016/j. pneurobio.2010.09.002


*Received: 15 June 2013; accepted: 03 July 2013; published online: 24 July 2013.*

*Citation: Sandrone S (2013) Self through the mirror (neurons) and default mode network: what neuroscientists found and what can still be found there. Front. Hum. Neurosci. 7:383. doi: 10.3389/fnhum.2013.00383*

*Copyright © 2013 Sandrone. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.*

# A philosophical perspective on the relation between cortical midline structures and the self

# **Kristina Musholt \***

Department of Philosophy, Logic and Scientific Method, London School of Economics and Political Science, London, UK

#### **Edited by:**

Georg Northoff, University of Ottawa, Canada

#### **Reviewed by:**

Britt Anderson, Brown University, USA Evan Thompson, The University of British Columbia, Canada

#### **\*Correspondence:**

Kristina Musholt, Department of Philosophy, Logic and Scientific Method, London School of Economics and Political Science, Houghton Street, London WC2A 2AE, UK e-mail: k.musholt@lse.ac.uk

In recent years there has been increasing evidence that an area in the brain called the cortical midline structures (CMSs) is implicated in what has been termed self-related processing. This article will discuss recent evidence for the relation between CMS and self-consciousness in light of several important philosophical distinctions. First, we should distinguish between being a self (i.e., being a subject of conscious experience) and being aware of being a self (i.e., being able to think about oneself as such). While the former consists in having a first-person perspective on the world, the latter requires the ability to explicitly represent one's own perspective as such. Further, we should distinguish between being aware of oneself "as subject" and being aware of oneself "as object." The focus of existing studies investigating the relation between CMS and self has been predominantly on the ability to think about oneself (and in particular thinking of oneself "as object"), while the more basic aspects involved in being a self have been neglected. However, it is important to widen the scope of the cognitive neuroscience to include the latter, not least because this might have important implications for a better understanding of disorders of the self, such as those involved in schizophrenia. In order to do so, cognitive neuroscience should work together with philosophy, including phenomenology. Second, we need to distinguish between personal and subpersonal level explanations. It will be argued that although it is important to respect this distinction, in principle, some subpersonal facts can enter into constitutive conditions of personal-level phenomena. However, in order for this to be possible, one needs both careful conceptual analysis and knowledge about relevant cognitive mechanisms.

**Keywords: self-consciousness, consciousness, cortical midline structures, phenomenology, schizophrenia, personal level, subpersonal level**

# **INTRODUCTION**

Self-consciousness is a topic that is one of the classical concerns of philosophy. More recently, it has also begun to take center stage in cognitive science studies, including neuroimaging studies. In particular, in recent years there has been increasing evidence that an area in the brain called the cortical midline structures (CMSs) is implicated in what has been termed self-related processing. This article will discuss recent evidence for the relation between CMS and self-consciousness in light of several important philosophical distinctions.

After briefly summarizing what is known to-date about the relation between the self and CMS and raising some general concerns regarding the attempt to localize the self in the brain, it will first be argued that we should distinguish between *being a self* (i.e., being a subject of conscious experience) and *being aware of being a self* (i.e., being able to think about oneself). While the former consists in having a first-person perspective on the world, the latter requires the ability to explicitly represent one's own perspective as such. This, in turn, requires an awareness of other minds, and the ability to contrast one's own perspective with that of others. It will be argued that the focus of existing studies investigating the relation between CMS and self has been predominantly on the ability

to think about oneself, while the more basic aspects involved in being a self have been neglected. It will be argued further that it is important to widen the scope of cognitive neuroscience to include the latter, not least because this might have important implications for a better understanding of disorders of the self, such as those involved in schizophrenia. In order to do so, cognitive neuroscience should work together with philosophy, including phenomenology. It will also be argued that we should distinguish between thinking of oneself "as subject" and thinking of oneself "as object" and that it might be interesting to target this distinction in future empirical studies.

Second, the article will ask what and how exactly (if anything) the study of CMS can teach us about self-consciousness. It will be argued that we need to distinguish between personal and subpersonal level explanations. At the personal level we refer to a person's conscious experience and mental states in order to make intelligible the behavior of a person by providing the reasons the person might have for acting in the way that they do. Subpersonal level explanations on the other hand provide information about the physiological or computational enabling conditions of personal-level phenomena. Properties at the subpersonal level are neither conscious, nor do they make reference to mental states or reasons. This raises the question as to how we should think of the relation between these two levels of explanation. Can neuroscience only ever provide us with correlations or causal relations between personal and subpersonal level phenomena? Or can a brain state, such as a particular pattern of activation in CMS, be part of the constitutive basis of being in a psychological state, such as a state of self-awareness? It will be argued that, in principle, some subpersonal facts can enter into constitutive conditions of personal-level phenomena. However, in order for this to be possible, one needs both careful conceptual analysis and knowledge about relevant cognitive mechanisms (such as neurocomputational mechanisms).

# **THE SELF AND CORTICAL MIDLINE STRUCTURES**

It seems that in recent years social cognitive neuroscience has made much progress in identifying the neural correlates of selfawareness. In particular, functional neuroimaging (fMRI) studies have demonstrated the involvement of CMS, including the ventral medial prefrontal cortex (vMPFC), dorsal MPFC (dMPFC), and parietal/posterior cingulate cortex (PCC), as well as the anterior CMS (e.g., ACC) in self-related processing (e.g., Gusnard et al., 2001; Kelley et al., 2002; Northoff and Bermpohl, 2004; Platek et al., 2004; Ochsner et al., 2005; Northoff et al., 2006; Yaoi et al., 2009).

The involvement of CMS in the processing of self-related stimuli seems to be independent of the sensory domain in which the self-related stimulus is being represented (e.g., auditory, visual, mental), and of the task domain (e.g., verbal, spatial, memory, emotional, facial, social, agency) used in any specific study. More recently, a study by Moran et al. (2009) also found that CMS are involved both in the explicit and implicit processing of self-related stimuli, that is, in situations that involve self-relevant stimuli, regardless as to whether subjects were asked explicitly to engage in self-referencing.

Interestingly, the brain areas associated with the processing of self-related stimuli seem to overlap with what has been called the "default-mode network" of the brain. This network is thought to be involved in the processing of self-generated stimuli (as opposed to stimuli from the external world) and is thought by some to instantiate "the self" (Gusnard et al., 2001; Wicker et al., 2003; Schneider et al., 2008) 1 .

However, here, I want to raise some doubts regarding the possibility of locating the self in the brain.

For one thing, it has been pointed out that the relevant studies often do not adequately distinguish familiarity (i.e., the personal familiarity with a place, person, or other stimulus, which may elicit autobiographical memories or emotional reactions) from self-relatedness (Gillihan and Farah, 2005), and between selfspecific and non-self-specific task demands (such as the recruitment of attention or executive control functions, which might be required in order to make evaluative or recognitional judgments) (Legrand and Ruby, 2009). Specifically, Legrand and Ruby, 2009, p. 270) argue that self-related tasks, which involve self-evaluative

judgments, are not self-specific, because "the evaluative processes enabling identification, attribution, and reflection upon a subject are not different for self and others."

These concerns were partly addressed in a recent meta-analysis by Qin and Northoff, 2011, p. 1223). The aim of this study was to investigate "the relationship between brain activity related to the processing of self-specific, personally familiar, and other (nonself and non-familiar) stimuli," while controlling for task- and stimulus-dependent effects. The study demonstrated that there is indeed overlap between the processing of self-related, otherrelated, and familiar stimuli in several regions of the CMS (in particular in the MPFC and PCC). However, the perigenual anterior cingulate cortex (PACC) seems to be recruited specifically in the processing of self-related stimuli, as well as during resting-state conditions. The study also partly confirmed the hypothesis put forward by Legrand and Ruby (2009)that general task demands (such as those involved in evaluative and recognitional judgments) lead to an activation of CMS (in particularMPFC and PCC/precuneus), suggesting that such activation is not specific for the processing of self-related stimuli. Again, the PACC seems to be exempt from this, though Qin and Northoff (2011) point out that due to a lack of control in the original studies their results are not conclusive with respect to this point.

In sum, this meta-analysis suggests that the PACC seems to be recruited specifically for the processing of self-related stimuli as well as in resting-state activity, while other regions of the CMS, such as the MPFC and the PCC are involved in the evaluation of stimuli as well as in the processing of familiarity and the distinction between self and other.

Moreover, other areas of the brain were also identified as being involved in the processing of self-related stimuli. These include the lateral prefrontal cortex and the left anterior insula. These areas have also been suggested to be involved in self-referential processes in previous studies (Keenan et al.,2001;Platek et al.,2008;Modinos et al., 2009).

Taken together these results suggest some involvement of CMS (in particular the PACC) in the processing of self-related stimuli. However, the results also indicate the involvement of CMS in other processes, such as general (i.e., non-self-related) evaluative or recognitional judgments, as well as the involvement of other areas in self-related processing, thus raising doubts as to how specific the relation between CMS and self is. What this shows is that we have to be very careful with regard to claims suggesting that the self is "located" in particular areas of the brain.

Notice also that it is common in the literature on self and CMS to equate self-related with self-specific processing (accordingly, these two terms have been used somewhat interchangeably in this section). However, as mentioned above, according to Legrand and Ruby (2009), self-relatedness should be distinguished from selfspecificity. That is to say that on their view one should distinguish between the process of judging a stimulus to be self-related and the self-specifying functional processes that implement a self/non-self distinction at a more fundamental level (and which provide the basis for judgments of self-relatedness) (also, see Christoff et al., 2011).

This distinction, which we will return to in the following, is related to a more general concern regarding the attempt to locate

<sup>1</sup>Though note that Schilbach et al. (2008) argue that activity in the default system of the brain is intimately linked to a human predisposition for social cognition. The relation between social cognition and self-awareness will be further discussed below.

the self in the brain, namely the fact that the phenomenon of selfawareness is multi-faceted, involving, for example, the distinction between being a self (i.e., being the subject of conscious experience) and being aware of being a self (i.e., possessing the ability to think about oneself), as well as between synchronic and diachronic aspects of self-awareness (where the former indicates awareness of oneself at a given time and the latter awareness of oneself across time), or between cognitive, agentive, and affective elements of self-awareness. Given this multi-faceted nature, it is not surprising that recent results shed doubt on the notion of a particular location for "the self." In fact, given the multi-faceted and complex nature of the self and self-awareness, we should expect both selfrelated and self-specific activity to be broadly distributed across the brain, involving diverse affective and cognitive processes. In the following section, I am going to take a closer look at the first distinction – that is, the distinction between being a self and being aware of being a self – with the aim of evaluating the implications of this distinction for studies of the relation between CMS and the self.

# **BEING A SELF vs. BEING SELF-AWARE**

Within philosophy different notions of self and self-awareness can be distinguished. One of the crucial distinctions on my view is the distinction between being a self (i.e., being the subject of conscious experience) and being aware of being a self (i.e., being able to think about oneself).

The former consists in having a first-person perspective on the world, that is, a particular point of view. In contrast, the latter consists in the ability to think about oneself as such, that is, to explicitly represent one's perspective as such. Thus, while the former can be characterized as being "world-directed," the latter is "self-directed." The ability to think about oneself, in turn, requires conceptual abilities, an awareness of other minds, and the ability to contrast one's own perspective with that of others (Musholt, 2012).

It is important not to conflate these two notions with each other. For while it is reasonable to assume that every conscious experience is experience from a subjective point of view, this subjective point of view need not itself be part of the representational content of experience. It is one thing to have a perspective on the world (or to be aware of different ways in which one can interact with the world), but it is quite another to be aware of having this perspective (or to be aware of oneself as an agent) (Baker, 1998, 2012). In fact, it would put an unnecessary cognitive burden on the organism to always represent its own perspective on the world. Rather, precisely because an organism's perception of the world is always from its own perspective, this fact itself can "drop out" of the content of conscious experience – the self can be thought of as an "unarticulated constituent" (Perry, 1998) of experience. That is to say that while perception contains implicitly self-related information (for instance, the objects in one's environment are always presented in a certain distance and orientation from oneself), this does not mean that the self is part of the explicit representational content of experience (Musholt, 2013). The explicit representation of one's own perspective only becomes important once an organism has an understanding of the perspective of others and wants to contrast its own perspective with that of others (Beckermann, 2003; Musholt, 2012). (This ability, in turn, can enable a host of other important abilities, such as the ability to deceive as well as the ability to cooperate by sharing intentions.) Accordingly, selfconsciousness and intersubjectivity can be regarded as two sides of the same coin. Interestingly, some studies have found that some parts of the CMS, as well as other areas of the brain, such as the temporoparietal junction (TJP) are activated in the reflection on both one's own and the mental states of others (e.g., Mitchell et al., 2005; Uddin et al., 2007; Lombardo et al., 2010).

That being said, the way we think about ourselves is not necessarily the same as the way we think about others. Rather, following a distinction introduced by Wittgenstein (1958), one can distinguish two-ways in which a subject can be self-aware. In one case, the subject thinks of herself "as subject." This is the case, for example, when the subject experiences a mental state – such as a pain, for example – and on the basis of this experience ascribes the state to herself by using the first-person concept: "I have pain." Although mental state concepts, such as the concept "pain," can be applied both to self and other (reflecting a common conceptual schema), each of us also has privileged access to their own pain state.While I can ascribe pain to you by inferring from your behavior or your facial expression that you must be in pain, I do not need to rely on behavioral observation or inference in order to ascribe pain to myself. Rather, the access to my pain is direct, immediate, and non-inferential. However, the subject can also think of herself "as object," that is, in the same way as she would think of another (i.e., by adopting the perspective of another onto herself). For example, when the subject observes herself in the mirror and ascribes to herself the property of being tall, she does this on the same basis as she would in the case of another – in this case by looking at herself. Self-ascriptions of the first kind have special significance for self-knowledge, because they are often taken to be "immune to error through misidentification relative to the first-person pronoun" (Shoemaker, 1968). This is to say that when ascribing properties to oneself by taking oneself "as a subject," one might be wrong with regard to the property one is self-ascribing, but one cannot be wrong with regard to the subject of this selfascription – oneself. The reason for this is because the relevant thought does not contain an identification component – I do not need to identify myself in order to know that I feel pain (Evans, 1982). In contrast, when I look at myself in the mirror and judge that I am tall, I am identifying the person that I see in the mirror with myself. Hence, this thought is liable to error through misidentification.

Note that these different types of self-representation are not distinguished in terms of their *content*, but rather in terms of their *mode* of presentation. When thinking of oneself "as subject" one adopts a first-person mode of presentation, that is to say, a mode that is specific to ways of gaining information about oneself (Perry, 2002; Recanati, 2012). In contrast, when thinking of oneself "as object" one adopts a third-person mode of presentation, that is to say a mode of presentation that is not specific to ways of gaining information about oneself. In the former case the resulting selfascription will be immune to error through misidentification, as no identification is required, whereas in the latter case it will not. For example, I can ascribe a mental state, a certain belief state, say, to myself either on the basis of my awareness of the mental state

in question (from the first-person perspective), or on the basis of adopting another's perspective onto myself (from the thirdperson perspective), for instance by reflecting of my past behavior and concluding that I must have a certain belief without having been aware of it. The content of the self-ascription will be the same in both cases, namely "I believe x," whereas the mode – the basis upon which the self-ascription is made – will be different. Similarly, I can judge that my legs are crossed either on the basis of proprioceptive experience (from the first-person perspective) or on the basis of looking at them in the mirror (from the thirdperson perspective). Again, the content of the judgment "My legs are crossed" will be the same in both cases, but the mode will be different. In the first case my judgment simply makes explicit the fact that proprioceptive information necessarily concerns the subject of experience – no self-identification is required. In the second case, the subject identifies the image in the mirror with herself.

Thus, we should distinguish perspectivalness and other aspects of subjectivity that constitute part of the structure of consciousness as such (and that provide the basis for the ability to think about oneself "as subject"), and specific types of conscious experience, namely experience or awareness of the self (where this is to be understood in terms of explicit self-representation, or thinking about oneself as such). Moreover, while the latter requires conceptual abilities and is closely tied to our ability to ascribe mental states to others, this is not say that the way in which we represent or think about ourselves is necessarily the same in which we represent our think about others. Rather, we can distinguish between thinking about oneself "as subject" (in the first-person mode) and thinking about oneself "as object" (in the third-person mode).

The distinction between "being a self" and "being aware of being a self"is related to the distinction between pre-reflective and reflective self-awareness (e.g., Zahavi, 2005; Legrand, 2007a; also, see Legrand, 2003, 2006). However, there are also important differences. For one thing, while the notion of possessing pre-reflective self-awareness is largely equivalent to the notion of "being a self" (i.e., being a subject of conscious experience), I prefer to reserve the term "self-awareness" for the ability to refer to oneself in thought, which, in turn, requires the ability to explicitly represent oneself. However, this issue can largely be regarded as a terminological matter for the purposes of this paper (for a detailed discussion, see Musholt, 2013). More importantly, though, the notion of reflective self-awareness is not quite the same as the notion of being aware of being a self (i.e., the ability to think about oneself), because while Legrand and others seem to think that reflective self-awareness (and thus explicit self-representation, or thinking about oneself) necessarily implies being aware of oneself "as object" (see in particular Legrand, 2007a), as I have argued above, one can think about oneself (and thus explicitly represent oneself)*either* "as subject" *or* as "object," depending on whether the explicit self-representation is based on a first-person mode of presentation (i.e., a way of gaining information that is specific to the self), or on a third-person mode of presentation (i.e., a way of gaining information that is not specific to the self). Therefore, the three-way distinction between being a self on the hand and representing or thinking about oneself either "as subject" or "as object" on the other hand that I have introduced here does not map exactly onto the two-way distinction between pre-reflective and reflective self-awareness.

Now, which of these notions (if any) are in play in studies investigating the relation between CMS and the self?

Most of the relevant neuroimaging studies so far have relied on the explicit judgments of self-relatedness. They usually involve the presentation of personality traits which subjects have to rate as being more or less self-related on a given scale. [Though note that (Heinzel et al., 2006; Northoff et al., 2009; Qin and Northoff, 2011) use a broader notion of self-relatedness which includes knowledge of one's own body, knowledge of psychological traits, and episodic memory, as well as more generally the relationship to specific stimuli in the environment, such as the degree of personal relevance and meaning attached to emotional pictures.] It seems clear that in these kinds of studies what is being probed is (explicit) selfconsciousness. Participation in these studies requires subjects to have a concept of themselves and to be able to reflect on questions such as whether a certain personality trait belongs to them or not. Even knowledge of one's bodily features, psychological traits, and memories requires the ability to think about oneself. Moreover, insofar as specific stimuli are rated as being more or less selfrelevant or meaningful, they also need to be reflected upon and to be put in relation to oneself – which, again, requires thinking about oneself. Thus, it seems clear that by and large the studies that are investigating the relation between CMS and the self are investigating explicit self-awareness, and not the more basic aspect of the subjectivity of conscious experience, of being a self or a subject of experience (cf. Legrand, 2003, 2007a; Legrand and Ruby, 2009; Christoff et al., 2011.) While recently, studies have begun to address aspects of self-awareness that do not rely on explicit selfreflection (Moran et al., 2009), these studies still rely on explicit, conceptual knowledge about the self (such as knowledge about personal semantic information).

What seems less clear is whether subjects who engage in this task do so by thinking of themselves as they would of another person (i.e., "as object"), or whether they think of themselves "as subject." In the case of exposure to emotional pictures, it seems plausible that subjects think of themselves"as subject."The picture elicits a (more or less) intense emotional reaction, which the subject can then self-ascribe by means of introspection, that is, on the basis of their experience. As subjects only have privileged access to their own experiences in this way, this seems to be different from the way in which they would think of someone else. On the other hand, it might not always be apparent to me what emotional state I am in, and I might in some cases have to rely on inference in order to figure out what I am feeling – similar to when I am trying to figure out the emotional state of someone else. However, in the case of ascribing personality traits or bodily traits to oneself, the subjects seem to think of themselves "as object." In order to be able to ascribe bodily traits to oneself, one needs to look at oneself, as one would at another (for instance, by looking at a mirror or a picture). Similarly, we often ascribe personality traits to ourselves on the basis of what other people (such as friends or family) tell us about ourselves, or by reflecting on past experiences and judging our own behavior in light of what it tells us about our personality. Again, this way of thinking about oneself is not in principle different from the way one would think about another.

What would be interesting is for future experiments to take into account this distinction in order to try to find out whether and how the distinction between thinking of oneself "as subject" and thinking of oneself "as object" is reflected in different patterns of neural activation. In order to do, paradigms would have to be developed to clearly distinguish between these two conditions. That is, the paradigms in question would have to be able to distinguish between judgments that are made based on ways of gaining information that are specific to the self (such as judgments made on the basis of the experience of a mental or bodily state) and those that are made based on ways of gaining information that are not specific to the self.

Although some studies have made first steps in that direction (Ochsner et al., 2005; Jenkins and Mitchell, 2011), they do not adequately distinguish between thinking of oneself "as subject" and thinking of oneself "as object." For example, Ochsner et al. (2005) investigated the difference between direct and reflected self-appraisals, where the former was supposed to tap into the subject's own beliefs about their traits, and the latter the subject's perception of how others view them. They found that different judgment types all activated MPFC, though direct appraisals as compared to reflected appraisals also recruited the posterior cingulate, whereas reflected as compared to direct appraisals also recruited the insula, orbitofrontal, and temporal cortex. While these differences are interesting, note that the distinction between direct and reflected self-appraisals is not the same as the distinction between thinking of oneself "as subject" and thinking of oneself "as object." This is because even in direct self-appraisals the subject needs to make herself an object of self-reflection in order to determine whether specific traits belong to herself. In contrast, when the subject thinks of herself "as subject," she self-ascribes certain properties (such as the property of having a visual experience, feeling a pain or an emotion, or being an agent) in a direct, non-inferential way, on the basis of exploiting the self-specifying mechanisms that are implicit in conscious experience. In order to do so, she need not make herself an object of self-reflection; rather, she simply needs to apply the first-person concept in order to make explicit the self-specifying information that is implicit in her experience. (See below for further discussion of what this self-specifying information might consist in.)

Another recent study by Jenkins and Mitchell (2011) studied different types of self-reflection, namely reflection on one's personality traits, reflection on current mental states, and reflection on bodily characteristics. They found that there was a robust region of MPFC that was more engaged when participants thought about themselves than when they made judgments about another person, regardless of the kind of self-reflection. They also found that differences in type of self-reflection were reflected in other areas of the brain, such as the TJP (for judgments of current mental states) or the cerebellum (for judgments of physical traits). But notice again that the different types of self-reflection studied here do not reflect the distinction between thinking of oneself "as subject" and thinking of oneself "as object."This is because the different types of self-reflection under investigation here are distinguished in terms of their content. However, as I have argued above, the distinction between thinking of oneself "as subject" and thinking of oneself "as object" is not based on a difference in content, but rather on a difference between modes of presentation. So while reflection on one's stable personality traits arguably requires thinking of oneself "as object," thinking about one's current mental states might either be based on direct experience of the latter (thinking of oneself "as subject"), or on inferences similar to those employed in reasoning about the mental states of others. After all, as I pointed out above, while we do have privileged access to some of our mental states (for instance, I do not normally need to rely on inference to know that I experience a pain), other mental states (such as a slight feeling of irritation) might only become apparent when I reflect on my recent behavior and infer that I must be feeling irritable. Indeed, given that the experimental paradigm is based on explicit self-reflection, it seems plausible that it will predominantly be the latter – thinking of oneself "as object" – that is being prompted here. Interestingly, Jenkins and Mitchell, 2011, p. 216) found that "reflecting on one's own current mental states was specifically associated with activation in regions previously linked to inferences about the mental states of others, including medial parietal cortex and bilateral temporoparietal junction," in line with the thought that such self-reflection relies on processes that are similar to reflecting on the mental states of others. This is in line with previous findings as well (e.g., Mitchell et al., 2005; Uddin et al., 2007; Lombardo et al., 2010) 2 . Similarly, while reflection on my bodily traits will usually be an instance of thinking of myself "as object," I can also self-ascribe bodily properties (such as the property of having my legs crossed) on the basis of proprioceptive experience, and thus "as subject." Thus, more research is needed to specifically address the question whether the philosophical distinction between thinking of oneself "as object" (in the third-person mode) and thinking of oneself "as subject" (in the first-person mode) is reflected in the neurobiology.

Moreover,it would also be interesting to enlarge the scope of the neurocognitive study of the self to include the more basic aspects of the subjectivity of conscious experience, of being a self or a subject of experience, rather than focusing on the ability to think about oneself alone (cf. Legrand, 2003, 2006, 2007a,b; Legrand and Ruby, 2009; Christoff et al., 2011). Again, while these are to be distinguished from explicit self-awareness (in the sense of thinking about or representing oneself), they provide the basis for the ability to think first-person thoughts "as subject" (i.e., first-person thoughts that are immune to error through misidentification). Moreover, while there is no reason to think that these basic aspects of being a self will also be related to CMS activity, as they arguably constitute a structural feature of all conscious experience and interaction with the world, they are nonetheless an important aspect of our understanding of the self<sup>3</sup> . As mentioned in the previous section, recently, Legrand and Ruby (2009) and Christoff et al. (2011) have suggested that these are instantiated by self-specifying processes, which implement what they call a functional self/non-self distinction in perception, action, cognition,

<sup>2</sup>Though notice that since the ascription of mental and bodily states to oneself and to others (or to oneself "as object" and "as subject") will always rely on a common conceptual schema (despite differences in mode of presentation), we should always expect some overlap between judgments involving the same concepts.

<sup>3</sup> Indeed, as Christoff et al. (2011) point out, it is likely that the widespread assumption that the self is "instantiated" by the default-network of the brain will be called into question if we expand the scope of the empirical study of the self. For it will be precisely in interactions with the external world that the more basic aspects of being a self will come into focus. Also see Legrand (2007a).

and emotion<sup>4</sup> . After all, in order to be able to engage and interact with the environment, an organism must be able to (implicitly) distinguish between afferent signals arising as a result of the organism's own efferent processes (i.e., reafference signals) and afferent signals arising as a result of environmental events (i.e., exafference signals) (see, e.g., Christoff et al., 2011, p. 105). The sense in which the self is specified by means of these processes is as a subject of perception, emotion, and cognition, as well as an agent – hence they can provide the basis for thinking of oneself "as subject," that is, in the first-person mode.

Notice though that while Christoff et al. (2011), as well as Legrand and Ruby (2009) and Legrand (2006, 2007a) take these processes of implicit self-specification to result in a type of selfexperience or self-awareness, as mentioned above, I would prefer to reserve this term for the ability to explicitly represent the self. While self-specifying processes are doubtlessly involved in processes of perception, action, cognition, and emotion at the subpersonal level, this does not imply that the self is represented in the content of experience at the personal level (and on my view the latter is required for genuine self-awareness; see Musholt, 2013 for detailed discussion). But setting aside this largely terminological issue, I agree with Legrand (2003, 2006, 2007a,b), Legrand and Ruby (2009), and Christoff et al. (2011) that insofar as both the study of the subjectivity of conscious experience and of the ability to represent oneself in thought are important avenues of research, one should not unnecessarily restrict the cognitive neuroscience of the self to the latter alone. Rather, one should attempt to study both of these aspects, albeit against a background of careful conceptual distinction.

#### **IMPLICATIONS FOR SCHIZOPHRENIA**

Studying the implicitly self-specifying processes that are involved in perception, action, emotion, and cognition might also be interesting from a clinical perspective, as it could shed light on the neural correlates of disorders of the self, such as those occurring in patients suffering from schizophrenia. Recent research on schizophrenia suggests that both self-consciousness (in the sense of representing oneself) and the general structure of consciousness as such can be altered in patients suffering from this disorder.

Phenomenologically inclined authors have recently suggested that schizophrenia is an ipseity disturbance, or self-disorder,which manifests itself in both altered forms of self-awareness, as well as altered forms of consciousness more generally. Put differently, schizophrenia seems to affect both the "world-directed" and "selfdirected" aspects of consciousness. As Sass and Parnas (2003) put it:

"[. . .] this ipseity disturbance has two fundamental and complementary aspects or components. The first is hyperreflexivity, which refers to forms of exaggerated self-consciousness in which a subject or agent experiences itself, or what would normally be inhabited as an aspect or feature of itself, as a kind of external object. The second is a diminishment of self-affection or auto-affection—that is, of the sense of basic self-presence, the implicit sense of existing as a vital and self-possessed subject of awareness." (p. 428)

This is to say that patients suffering from schizophrenia seem to direct an unusual amount of attention toward aspects of their self that are normally not explicitly represented – the self becomes objectified, rather than being part of the subjective experience of engaging with the world. At the same time, the experience of oneself as a subject seems in some sense diminished or reduced. And further, these "complementary distortions are necessarily accompanied by certain kinds of alterations or disturbances of the subject's 'grip' or 'hold' on the conceptual or perceptual field" (Sass and Parnas, 2003), suggesting that it is not just the conscious experience of oneself that is altered, but also more generally the conscious experience of the world. Put differently, the very structure of consciousness as such seems to be affected. The fact that ipseity disturbances in schizophrenia affect both how the world in general is experienced as well as leading to specific aspects of the self entering into the focus of attention is also stressed by Sass et al. (2011).

If this analysis of schizophrenia as an ipseity disturbance is right, and if, furthermore, Legrand and Ruby (2009) and Christoff et al. (2011) are right in stressing the role of implicitly selfspecifying processes in various types of conscious experience, then it stands to reason that it is precisely these processes that are affected in schizophrenia. Accordingly, further study of these processes and their potential relation to ipseity disturbances in schizophrenia – in particular disturbances of the general structure of consciousness – could help to make progress in understanding the causes of schizophrenia. While some studies have already begun to address the relation between abnormal CMS function and abnormal self-reflection in schizophrenia (van der Meer et al., 2010), as well as with faulty interpretation of social events, which, in turn, might contribute to the development of delusions (Holt et al., 2011), it would be worthwhile to further investigate both the link between abnormal CMS function and abnormal self-reflection, as well as the link between abnormalities in implicitly self-specifying processes (independent of processes of self-reflection that are being linked to CMS) and ipseity disturbances.

Indeed, Christoff et al. (2011) mention two paradigmatic cases of such self-specifying processes, namely cognitive control and emotion regulation. They also point to various brain regions thought to be associated with these processes, in particular the lateral PFC, dorsomedial PFC, and dorsal ACC (for cognitive control and explicit emotional regulation), and the rostral ACC (rACC), subgenual ACC, and vmPFC (for implicit emotional regulation). It would be interesting to see whether these brain areas show a different pattern of activation in patients suffering from schizophrenia.

#### **THE ROLE OF PHENOMENOLOGY**

However, such an endeavor also requires careful conceptual and phenomenological analysis. As we have seen above, the study of the self is multi-faceted and one needs to be careful in detailing which aspect of the self or self-awareness one is intending to study and in showing that the paradigms employed do indeed capture the specific aspect or phenomenon in question. Phenomenology can

<sup>4</sup>The notion of self-specifying processes and their relevance for self-consciousness is also discussed at length by, for example, Bermúdez (1998) and Vosgerau (2009).

help with such an analysis. Indeed, as various authors (e.g.,Varela, 1996; Gallagher, 1997; Sass and Parnas, 2006; Thompson, 2007; Sass et al., 2011) have pointed out, the relation between phenomenology and cognitive neuroscience can be seen as being mutually constraining. This means that phenomenological analysis can provide part of the data set that neuroscientific theorizing needs to take into account. After all, a neuroscientific study of self and selfawareness cannot succeed without an understanding of what it is that one wants to explain, and phenomenology – as the study of the structure of awareness (including self-awareness) – can provide this understanding. At the same time, neuroscience can also provide data that challenge established ways of thinking about phenomenology, thus providing impulse for new ways of conceptualizing aspects of conscious experience. An example for this might be a case in which neuroscience highlights the involvement of distinct neurobiological systems in a type of experience that was previously analyzed as being unified. While this result need not necessarily lead to a change in the analysis of the conscious phenomenon in question (because one cannot simply assume that all aspects of subpersonal level processing are reflected at the personal level; see below), it can prompt further reflection that might ultimately reveal the phenomenon to be more complex than was previously thought (Sass et al., 2011).

To put the interaction between phenomenology and cognitive neuroscience into more concrete terms, one way (initially suggested by Varela, 1996) in which this interplay between phenomenology and neuroscience can be put into practice is by asking participants to describe their experiences by means of open-ended questionnaires, so as to avoid the imposition of pre-established theoretical categories. The resulting descriptions must then be validated intersubjectively in order to be usable for the interpretation of correlated measurements of brain activity and/or behavior (Sass et al., 2011, p. 5). At the same time, neuroscientific findings, for example the discovery of distinct systems underlying the experience of what appears to be a unified phenomenon, can motivate further investigation into the correct phenomenological analysis (Sass et al., 2011) 5 .

Another way of incorporating phenomenology into cognitive neuroscience is by relying on results from philosophical phenomenology (that is, on a philosophical analysis of the phenomenology of certain experiences, rather than on interviews with participants), and to employ these in order to inform the set-up of experiments. This is called "phenomenological front-loading" (Gallagher, 2003). Again, the methodology is not to be seen as a "one-way-street" – rather, there should be a dynamic interplay between phenomenological analysis and preliminary trials in the process of establishing the best experimental paradigm.

The emphasis on the need for such a two-way exchange between philosophy and neuroscience brings us to the third part of this paper, namely the relation between personal and subpersonal level explanations.

# **THE PERSONAL AND THE SUBPERSONAL IN NEUROIMAGING THE SELF**

At the personal level we refer to a person's conscious experience and mental states, for example in order to make intelligible the behavior of a person by providing the reasons the person might have for acting in the way that they do. Subpersonal level explanations on the other hand provide information about the physiological or computational enabling conditions of personallevel phenomena. Properties at the subpersonal level are neither conscious, nor do they make reference to mental states or reasons.

Clearly, talk about the self and self-awareness is talk about personal-level phenomena. Likewise, phenomenological analyses are situated at the personal level – the level of the subject's experience (or phenomenology). Brain imaging results, on the other hand, are situated at the subpersonal level.

It is important to keep these two levels separate in order to avoid the mistake of ascribing properties to one level that only belong to the other. For example, we can only properly ascribe conscious mental states to the person, not to parts of the person, such as the brain (or areas within the brain) (Bennett and Hacker, 2003). Likewise, as we have seen above, although there are implicitly self-specifying processes that form part of the cognitive mechanisms enabling the perception of and interaction with the environment, we cannot simply assume that the information contained in these processes is explicitly represented at the personal level. Rather, there are good reasons to think that in basic forms of perception and action the self is not explicitly represented (Musholt, 2013). Moreover, while the personal level is amenable to appeals to reason, the subpersonal level is not reasons-responsive.

If this is so, how should we think about the relation between personal and subpersonal level explanations?

There are three different ways of conceptualizing this relationship. First, personal-level phenomena can simply be correlated with subpersonal level phenomena without this implying either a causal or a constitutive relationship. On this view, neuroimaging studies can only provide us with information about the neural correlates of the self and self-awareness. Second, subpersonal level explanations can give us information about the causes or enabling conditions of personal-level phenomena. On this view, neuroscience can reveal the causes of certain personal-level phenomena, but it doesn't tell us anything about what these phenomena really *are*. Third, subpersonal level explanations can enter into the constitutive conditions of personal-level phenomena. That is, they can enter into a conceptual understanding of what a specific phenomenon consists in.

Some philosophers (e.g., McDowell, 1994; Hornsby, 1997, 2000) have argued that the personal and the subpersonal are autonomous levels of explanation, and that information about subpersonal level processes can at best provide us with knowledge about the (causal) enabling mechanisms of personal-level phenomena, but it cannot tell us anything about the constitutive conditions of the latter. This is because personal-level explanations – explanations that proceed by reference to a person's conscious mental states and their reasons for doing something – are

<sup>5</sup>For a detailed open-ended questionnaire along those lines, which has been developed on the basis of self-descriptions obtained from patients suffering from schizophrenia for the study of anomalous self-experience (see Parnas et al., 2005). For a discussion of how phenomenology could be incorporated into the study of auditory verbal hallucinations in particular (see McCarthy-Jones et al., 2013).

of a distinct kind, so that it would be a mistake to try to combine such explanations with explanations of a very different kind, such as those that operate at the subpersonal level. While one type of explanation appeals to how things *ought* to be, by means of appealing to reasons, the other explains how things *happen* to be, by means of appeal to nomological generalizations (Hornsby, 1997; Shea, 2013).

Put differently, on this view, explanations that refer to reasons are constitutive of personal-level explanations. And since we cannot appeal to reasons at the subpersonal level, facts about what goes on at the subpersonal level cannot enter into explanations as to what constitutes personal-level phenomena (Colombo, 2013). As Hornsby puts it: "a study of the mechanisms of neural transmission won't help in understanding what a person's intentionally doing something *consists in*" (2000, p. 16; cited in Colombo, 2013, emphasis mine).

However, other philosophers (Colombo, 2013, Shea, 2013) have recently argued that even if the mental cannot be reduced to the neurobiological (and it seems plausible that it cannot), there might still be ways in which information about subpersonal level processes can contribute constitutive conditions for personal-level phenomena.

How so? Basically, according to Colombo (2013), such an interaction would be based on what Churchland (1986) has termed a co-evolutionary conception of the relationship between different explanatory levels. Such a co-evolution" involves explanations and concepts at one level being susceptible to correction, reconceptualization, and sometimes elimination, in light of discoveries and conceptual refinements at other levels" (Colombo, 2013, p. 6).

This approach is exemplified by the aforementioned two-wayinteraction between phenomenological and neuroscientific analysis, where neuroscientific results might in some case motivate the re-examination of phenomenological analysis, even if they cannot in and of themselves force a phenomenological redescription. If, based on neurobiological findings, we arrive at a different conceptualization of what a certain conscious experience *really is*, then, so it seems, this information will have made a contribution as to what *constitutes* the experience in question. After all, according to Hornsby and McDowell, a constitutive explanation provides us with an account of what a personal-level phenomenon, such as a person doing something intentionally *consists in*. Thus, an appeal to subpersonal mechanisms might – in certain circumstances – help us explain both the presence and break down of personal-level phenomena in ways that go beyond correlation (or even causation).

A concrete example for such an interaction that is discussed by Colombo (2013)involves the cases of addiction, pathological gambling, and "sex addiction."At the personal level, both pathological gambling and "sex addiction" seem similar in the relevant respects; accordingly, one might classify them as instantiating the same phenomenon, namely a type of addiction. However, as Colombo points out, there is evidence suggesting that addiction has a particular neurocomputational signature. In particular, addiction seems to involve the engagement of the so-called "reward-system,"which relies on computations based on dopamine activity. In the case of addiction, an increased flow of dopamine into the rewardsystem leads to a loss of inhibition or impulse, thereby granting

the system increased influence over the subject's behavior. As a result,

"[. . .] the reward system simultaneously learns to pursue a target obsessively and increases the relative valuation of stimuli that predict it. . .. [It systematically pulls] attention back toward the addictive target, and away from the alternative motivators on which cortical systems are trying to focus." (Ross, 2010, p. 138; cited in Colombo, 2013, p. 17)<sup>6</sup>

Now, as Colombo (2013) further points out, pathological gambling seems to share this neurocomputational signature. "Sex addiction," on the other hand, doesn't seem to involve the kind of changes to the dopaminergic reward-system observed in both addiction and pathological gambling (Ross et al., 2010). Moreover, the subpersonal facts about the neurocomputational mechanisms, in conjunction with what we know about gambling help us to understand while gambling can become addictive: it allows for perfect control over the cues that are predictive of reward (such a pressing a button on a slot machine), while providing no control over actual reward-contingencies (the actual winning of money). Neither of these features seems to be present when it comes to sex. Consequently, according to Colombo, while an understanding of the neurocomputational mechanisms of addiction helps us to understand pathological gambling *as* a form of addiction, the same cannot be said about "sex addiction." Thus, it seems to be wrong to describe a certain type of behavior as a case of addiction to sex – knowledge about the mechanisms of addiction together with knowledge about the subpersonal processes that underlie gambling and "sex addiction" suggests that the label "sex addiction" constitutes a conceptual mistake. We can thus see that knowledge about subpersonal facts can form part of the constitutive (or conceptual) conditions for a personal-level phenomenon. This, in turn, can have important theoretical as well as practical implications, for instance in terms of developing treatments (Colombo, 2013).

A second example that is would like to consider, which is discussed by Shea (2013), refers us back to the importance of the cognitive neuroscience of the self and self-awareness. Consider again the implicit self-specifying mechanisms that are involved in perception, action, emotion, and cognition mentioned above. I have suggested above that a break down in these mechanisms might contribute to some of the symptoms associated with schizophrenia. Infact,it has recently been suggested that certain positive symptoms, such as auditory hallucinations or the loss of a sense of agency might be due to such a break down (Fletcher and Frith, 2009; Shea, 2013). In particular, the idea is that such symptoms can be traced back to changes in the way in which representations of the world are updated by error signals (which are, in turn, linked to abnormal dopamine neurotransmission). As we have seen above, self-specifying processes are generally explained in terms of a comparator model that distinguishes between afferent signals arising

<sup>6</sup>But notice that the gambling need not be experienced as rewarding by the patient at the personal-level. In fact, it is precisely one of the hallmarks of addiction that patients themselves would like to stop the behavior in question, but find themselves being unable to do so, due to the subpersonal processes driving the behavior. So again, it is important to keep personal and subpersonal level explanations separate, even though there can be fruitful interaction between them.

as a result of the organism's own efferent processes (i.e., reafference signals) and afferent signals arising as a result of environmental events (i.e., exafference signals). Now, one hypothesis is that, say, in the case of auditory hallucinations, the mechanism that normally distinguishes between one's own voice and that of another by means of such a comparison is impaired, such that the patient is no longer able to reliably tell the difference between the voices generated by others and their own inner speech. Normally, inner speech is predictable based on the subject's belief and other mental states (in contrast to the speech of others). However, so the hypothesis, in the case of a break down of the normal comparator mechanism, the patient might receive a prediction-error signal when engaging in inner speech, which would lead them to conclude that the voice must have been generated by someone else (Shea, 2013).

Notice that this model is still controversial. However, we do not need to be concerned here with whether this is indeed an accurate model for the explanation of certain positive symptoms in schizophrenia. Rather, what matters for our present purposes is the point that if such a subpersonal level model could be established, it would go some way to explain what clearly is a personal-level phenomenon, such as the experience of auditory hallucinations. In particular, as Shea (2013) suggests, it might go some way in explaining why some of the features that are normally associated with the personal level, namely the rational connections between various mental states, break down. After all, according to this model, it is the very subpersonal mechanisms that normally enable an accurate representation of and rational response to evidence that are hypothesized to be affected, thereby explaining why such a rational response is no longer possible. Accordingly,

"[. . .] if a patient's experience of hearing voices can be explained by a pathology in the subpersonal mechanisms that constitute the normal capacity for responding to evidence in rational ways, then we again have a subpersonal factor that is more than just an external cause of the personal level phenomenon. It is *part of the constitutive basis of that phenomenon*. But because it is operating abnormally, the nature of the personal level phenomenon itself changes." (Shea, 2013, p. 17, emphasis added)

Thus, not only can knowledge about brain mechanisms be important in order to develop a causal understanding of (thereby contributing to the creation of better treatments of) pathological experiences and behaviors, but it can also contribute to the conceptual question as to what constitutes a specific phenomenon. This includes phenomena related to the self, such as the ability to distinguish between one's own voice and those of others (or between one's inner speech and the perception of the speech of others). Of course, this leaves open whether knowledge about cognitive processing in CMS does likewise have the potential to enter into the constitutive conditions for self-reflection.

It is important to be clear that localization studies as such remain at the level of correlating personal and subpersonal level phenomena. If we want to move beyond correlations and toward knowledge of causal, or even constitutive conditions, we need information about the specific mechanisms involved in bringing about personal-level phenomena. That is to say,we needfunctional (e.g., neurocomputational) analyses. Although they themselves cannot provide information about mechanisms, localization studies can provide an important first step in this direction because once we have identified the areas that are activated in certain cognitive processes, we can begin to develop hypotheses about their specific functional roles and the computational mechanisms that enable them to fulfill these roles.

# **CONCLUSION**

The leading question of this Research Topic was "Why and how is the self related to the brain midline regions?" As we have seen, while there is evidence to suggest that CMS do indeed play a privileged role in self-related processing, we have also seen that there is reason to doubt that the self is strictly speaking "located" in the CMS. This is because the CMS can also be shown to be involved in non-self-related cognitive tasks, while self-related processing also seems to involve brain areas outside of the CMS. Moreover, we have seen that it might not make much sense the speak of "the self" as such to begin with, as the notion of self and self-awareness is complex and multi-faceted.

Indeed, there are several philosophical distinctions that can be made with regard to the self and self-experience. This article focused on one of these, namely the distinction between being a self (i.e., being a subject of conscious experience) and being selfaware (i.e., being able to think about oneself), where the latter is closely tied to the ability to think about others. In addition, we saw that one can distinguish between thinking about oneself "as subject" (in the first-person mode) and "as object" (in the thirdperson mode). It was shown that studies of the relation between CMS and the self tend to focus on the ability to think about oneself, while neglecting the more basic aspects of being a self. Moreover, the sense of self-representation targeted in these studies seems to be mostly the sense of thinking of oneself "as object." It was suggested that it might be worthwhile to target the distinction between thinking of oneself "as subject" and thinking of oneself "as object" in future studies to see whether this distinction is reflected in the neurobiology.

In addition, it was suggested that while the more basic aspects of being a self might not possess any particular relation to the CMS, it would nevertheless be wrong to restrict the cognitive neuroscience of the self to the ability to think about oneself, not least because a better understanding of the more basic aspects of being a self (i.e., certain aspects of conscious experience in general, such as the perspectivalness of conscious experience) might be important for a better understanding of disorders of the self, such as schizophrenia.

It was further argued that in the pursuit of the study of the self and self-awareness, cognitive neuroscience, and philosophy (in particular phenomenology) ought to work together.

Finally, it was shown with the help of two examples that while it is important to respect the distinction between the personal and the subpersonal, knowledge about subpersonal level processes can potentially contribute to a reconceptualization of personal-level phenomena, including those that are related to the self. However, this leaves open whether a particular pattern of activation in CMS can be considered part of the constitutive basis of being in a state of self-awareness. What the discussion about the relation between the personal and the subpersonal also shows is that in order for there to be a fruitful interaction between different levels of explanation, we need not only careful conceptual and

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**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 12 June 2013; accepted: 16 August 2013; published online: 02 September 2013.*

*Citation: Musholt K (2013) A philosophical perspective on the relation between cortical midline structures and the self. Front. Hum. Neurosci. 7:536. doi: 10.3389/fnhum.2013.00536*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Musholt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# What can the organization of the brain's default mode network tell us about self-knowledge?

# **Joseph M. Moran1,2\*,William M. Kelley <sup>3</sup> and Todd F. Heatherton<sup>3</sup>**

<sup>1</sup> U.S. Army Natick Soldier Research, Development, and Engineering Center, Natick, MA, USA

<sup>2</sup> Center for Brain Science, Harvard University, Cambridge, MA, USA

<sup>3</sup> Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA

#### **Edited by:**

Niall W. Duncan, University of Ottawa, Canada

#### **Reviewed by:**

Georg Northoff, University of Ottawa, Canada Niall W. Duncan, University of Ottawa, Canada

#### **\*Correspondence:**

Joseph M. Moran, Center for Brain Science, Harvard University, 52 Oxford Street 290, Cambridge, MA 02138, USA e-mail: jmoran@wjh.harvard.edu

Understanding ourselves has been a fundamental topic for psychologists and philosophers alike. In this paper we review the evidence linking specific brain structures to self-reflection. The brain regions most associated with self-reflection are the posterior cingulate and medial prefrontal (mPFC) cortices, together known as the cortical midline structures (CMSs). We review evidence arguing that self-reflection is special in memory, while noting that these brain regions are often engaged when we think about others in our social worlds. Based on the CMSs' patterns of connectivity and activity, we speculate about three possible interpretations of their role in supporting self-reflection that are somewhat overlapping, and not intended to be mutually exclusive. First, self may be a powerful, but ordinary case for a cognitive system specialized for thinking about people. Second, mPFC may serve as a processing "hub," binding together information from all sensory modalities with internally generated information. Third, mPFC may serve as a cortical director of thought, helping to guide moment-by-moment conscious processing. Suggestions are made for future research avenues aimed at testing such possibilities.

#### **Keywords: cognitive neuroscience, self-reflection, medial prefrontal cortex, posterior cingulate cortex, default mode network**

How do we know what we are like? How do we determine the boundaries between ourselves and the world around us? How do we know what is ours, and what is not? Questions like these have engaged philosophers for millennia, and psychological scientists throughout psychology's relatively brief history. Great progress has been made by practitioners of these fields, who have recently been joined by neuroscientists bearing the promise of going beyond introspection, self-report, and behavior to the source of our sense of self, the brain. This work is theoretically useful in at least two ways. First, it enables characterization of how the brain implements the psychological process(es) of self-reflection, allowing for links between the neural and psychological levels of analysis. Second, it may suggest new ways to interpret and modify accounts of self-reflection at the psychological-level, allowing neural-level data to influence psychological-level theorizing. Wielding two major empirical breakthroughs, cognitive neuroscientists have made significant headway in understanding how the brain gives rise to a sense of self, revealing surprising knowledge about the organization of the neuronal networks responsible for self-reflection.

# **THE DEFAULT MODE NETWORK AND SELF-REFLECTION**

In brief, these breakthroughs consisted first of the discovery of what has come to be known as the default mode network (Shulman et al., 1997; Raichle et al., 2001), and second of the independent identification that a subset of these brain regions are enlisted when we engage in self-reflection (Gusnard et al., 2001; Johnson et al., 2002; Kelley et al., 2002). To be clear, this network's involvement is observed most closely during the psychological task of reflecting on one's personalities and characteristics (selfreflection), rather than during self-recognition, thinking of the self-concept, or thinking about self-esteem, for example. As such, this paper will focus on self at the level of self-reflection and the neural networks responsible for this task. The set of regions contributing to self-reflection consists primarily of the medial prefrontal cortex (mPFC), encompassing the medial surface of the medial frontal gyrus [Brodmann's Areas (BAs) 8 and 10], and the medial parietal cortex, roughly encompassing the retrosplenial and posterior aspects of the cingulate cortex, the area bounded at the anterior by the paracentral lobule, and at the posterior by the parieto-occipital sulcus (BAs 23, 31, 7). For ease of reference, we will refer to this medial parietal cluster together as posterior cingulate cortex (pCC). These regions have come to be known together as the cortical midline structures (CMSs) (Northoff and Bermpohl, 2004), and are the regions most closely associated with self-reflection in meta-analyses (e.g.,Northoff et al., 2006; Qin and Northoff, 2011).

The default mode network concept arose to explain the puzzling observation that when subjects rest quietly with eyes closed, CMS activity is elevated (as measured by positron emission tomography), along with that of anterior temporal lobes and lateral parietal cortices (Shulman et al., 1997). This set of regions is more active when people rest than when they are engaged in goaldirected tasks, and display *functional connectivity*: these regions' activity rises and falls together during the normal course of cognitive engagement and disengagement from the external world

(Greicius et al., 2003; Fox et al., 2005). This led Raichle and colleagues to propose that this set of regions formed a default mode network; a network that may serve to generate internal mental stimuli and pay attention to our stream of consciousness, but whose activity is attenuated when we turn our attention to the outside world (as in goal-directed tasks) (Gusnard et al., 2001; Raichle et al., 2001). Following these observations, several labs demonstrated direct overlap between the brain regions engaged during rest and during self-reflection (Wicker et al., 2003; D'Argembeau et al., 2005; Schneider et al., 2008; Whitfield-Gabrieli et al., 2011). This relation is further supported by a meta-analysis (Qin and Northoff, 2011), which reported that the same finding occurred across many studies.

# **MEDIAL PREFRONTAL CORTEX**

Several aspects of these regions' neuroanatomy may support these well-characterized roles. mPFC is larger than any other prefrontal region in humans (Ongur et al., 2003). By proportion, it covers more of the cortex in humans and has more space available for connections with other supramodal areas than in other primates (Semendeferi et al., 2001). It has a greater density of dendritic spines (69% more on average than primary sensory cortex) and smaller density of cell bodies on the average than other cortical regions, suggesting more complex associative processing (Jacobs et al., 2001). Finally, mPFC is almost exclusively interconnected with other heteromodal processing regions in the prefrontal cortex (Barbas and Pandya, 1989; Petrides and Pandya, 1999), anterior temporal cortex (Amaral and Price, 1984; Morán et al., 1987), and the cingulate gyrus (Morecraft and Van Hoesen, 1993; Arikuni et al., 1994). Most of these connections are reciprocal in nature (Passingham et al., 2002).

These regions are considered to be part of the "social brain": a network implicated by neuroimaging and lesion work in representing the people that populate our social worlds (Adolphs, 2001; Heatherton, 2011; Lewis et al., 2011). mPFC's enlargement in humans, preponderance of interconnections rather than cell bodies, and connections with other "social brain" nodes are all features that point toward a role in social abstraction, a skill for which humans are evidently selected (Dunbar, 2009). Indeed, humans form much larger social networks than do other animals (Dunbar, 1998). Lewis et al. (2011) showed further that the size of particular mPFC regions is correlated both with the degree to which we are able to represent multiple others' viewpoints and the size of our social networks. Underscoring the role of mPFC in social processing in general, and self-processing in specific, a recent metaanalysis further subdivides mPFC into ventral and dorsal aspects (Denny et al., 2012; Wagner et al., 2012), showing that ventral mPFC responds more to self, and dorsal mPFC responds more to others.

#### **MEDIAL PARIETAL CORTEX**

Posterior cingulate cortex shares many reciprocal connections with mPFC. In addition, the subregions of pCC are reciprocally connected with one another in a bilateral manner (Cavanna and Trimble, 2006). Along with mPFC, pCC is disproportionately large in humans relative to non-human primates (Goldman-Rakic, 1987). pCC shares many connections with subcortical and cortical

regions and serves as "association cortex," allowing the brain to "integrate both external and self-generated information and to produce much of the mental activity that characterizes *Homo sapiens*" (Cavanna and Trimble, 2006, p. 568). This set of neuroanatomical features suggests that these regions would be good candidates for those able to perform the inward-focusing and selfgeneration of stimuli that constitute mental activity when we are not focused on the external world (Mason et al., 2007; Smallwood et al., 2008). That these regions are disproportionately developed in humans, and that humans congregate in the largest social networks, suggests that much of this mental activity at rest might be about ourselves and others.

If we were to plan to design a system that would be able to retain information about itself, to determine what is and is not self, and to update that store of information in a flexible and goaldependent manner, we could do worse than to outfit it with the array of connections and features that are possessed by the CMS. While the neuroanatomical evidence is certainly suggestive of a set of regions that are specialized for self-reflection, stronger evidence has emerged in cognitive neuroscience. Work that we and others have done has repeatedly demonstrated that reflecting on the self engages the CMS relative to reflecting about (certain) other people, or non-social classes of stimuli (Craik et al., 1999; Johnson et al., 2002;Kelley et al., 2002; Heatherton et al., 2006; Moran et al., 2011; Whitfield-Gabrieli et al., 2011). This work has supported the idea that the self is a special cognitive structure, providing a superordinate means by which information can be encoded into memory (Fossati et al., 2004; Macrae et al., 2004). This position is further supported by neuropsychological work from Klein et al. (1999) that revealed a post-lesion dissociation in patients' abilities to form memories about the self versus about general semantic categories. The theoretical position that self-is-special is in direct contrast to the notion that the self is a "powerful, but ordinary" structure in memory; a view which suggests that our improved memory for information encoded in reference to the self is simply a result of the greater familiarity of the self-concept (Greenwald and Banaji, 1989), but that the semantic structures of self are no different from the semantic structures of sailboats and silver jewelry. Even though the cognitive neuroscience evidence strongly supports the self-is-special view, Denny et al.'s (2012) meta-analytical finding of a dorsal-ventral axis along which mPFC appears to be differentiated for other- and self-representation appears contradictory. Why is it the case that, on the one hand, our neural representations of self and other are so closely allied, but on the other hand these representations occur in regions of the cortex distinct from (and largely anatomically disconnected from) those networks that are engaged when we reflect about non-social sources of information?

## **WHY DOES SELF-REFLECTION ENGAGE THE CORTICAL MIDLINE STRUCTURES?**

We consider three possible explanations for this pattern of results that are speculative, not intended to be mutually exclusive, and are at least partially overlapping. First, one possibility is that Greenwald and Banaji (1989) may have been half-right: it may be that social information is special, and that the self is a powerful-butordinary *social* knowledge structure. Second, Heatherton (2011) has proposed that mPFC serves as a"hub,"binding together heavily

into a "conscious workspace."

processed information from secondary sensory areas from each of the senses with internally generated information to represent the conscious "workspace." Third, mPFC may act in a meta-cognitive fashion by guiding our moment-to-moment thought processes; in essence, in deciding what to think about next. See **Figure 1** for a schematic representation of each of these models.

# **IS THE SELF A POWERFUL-BUT-ORDINARY SOCIAL CONSTRUCT?**

On the self is a powerful-but-ordinary social construct view, the CMS could be seen as representing social information *per se*, and their seeming selectivity for self-relevant information might simply represent an extreme case of social information processing about a social target (the self) that by definition is more *familiar* than all other social targets. The overarching view of simulation theory (Gordon, 1986) is that in order to understand others we run a mental simulation of how we might act in given social situations. Conversely, the emerging discipline of neural hermeneutics (Gallotti and Frith, 2013) suggests that in order to understand ourselves, we pay close attention to the social behavior of others. Both of these viewpoints converge on the idea that the self might be a powerful, but ordinary social target.

One obvious prediction of this idea is that the CMS might be differentially engaged by the representation of (and processing about) social targets that are differentially familiar to us. Familiarity contains the concepts of both closeness and similarity: close individuals are those we feel close to (including family and friends), whereas similar individuals are those who share characteristics with us (like members of our race, political affiliation, or age group). Indeed, in Qin and Northoff's (2011) meta-analysis, they observe that stimulus *familiarity* drives activation in a similar ventral mPFC region just as much as does self-reflection. In addition, Denny et al.'s (2012) meta-analysis shows that ventral aspects of mPFC are preferentially engaged by reflecting on the self versus others. If this region is sensitive to the familiarity (or "selfness") of social information, then it should respond more to information that is more self-relevant than not. Several studies have found such a pattern of results (e.g., Phan et al., 2004; Moran et al., 2006). Indeed, Mitchell et al. (2006) observed that social targets manipulated to be similar to the self engaged this ventral mPFC region, whereas social targets manipulated to be dissimilar to the self engaged dorsal mPFC. Krienen et al. (2010) clarified Mitchell et al.'s findings by demonstrating that the driver of activation in mPFC was closeness rather than similarity *per se*, suggesting that the familiarity of repeated exposure to individuals drives their self-relevance.

Converging on this idea, a series of studies investigating selfreflection in different cultures have provided support for the notion that in individuals whose cultures are more interdependent, the same ventral mPFC region does not differentiate thinking about self from thinking about close family members (like participants' own mothers) (Zhang et al., 2006; Zhu et al., 2007; Chen et al., 2013), but that this does not necessarily hold true in Western, more independent cultures (Kelley et al., 2002; Kjaer et al., 2002; Heatherton et al., 2006; Vanderwal et al., 2008). These cross-cultural findings are best interpreted in the context of recent criticisms suggesting that standard delineations between Western and Eastern cultures are not as clear-cut as has been suggested (Martinez Mateo et al., 2013). In this context, Moran et al. (2011) provide data that clarify the distinction between independent and interdependent cultures. In their paper, consideration of one's mother's personality traits,but not her physical characteristics produced activation levels midway between those of thinking about one's own traits versus those of former US President, George W. Bush. To the degree that we represent the traits of a close other as being like our own (rather than their physical characteristics), this suggests again that "selfness" may be driving this difference in ventral mPFC). Considered as a unit, these lines of research reveal a quantitative dimension along which social targets of greater familiarity activate ventral mPFC to a greater degree, with the self sitting at the top as the most familiar social target of all.

A further prediction of the notion that the CMS are specialized for *social* processing (and that the self is a powerful subset of such processing) is that we might be able to differentiate their relative contributions along lines in which thinking about ourselves and thinking about others naturally cleave. To the degree that our representations of ourselves are first-person, and our representations of others are third-person, one would imagine that neural systems implicated in social processing that preferentially receive *visual* information would be more responsive to third-person representations. Based on the patterns of connectivity that we introduced at the beginning of this paper, it should be clear that the regions of pCC implicated in the default mode (and in self-reflection) are strongly linked to regions that create complex visual representations. Indeed, Raichle et al. (2001) advocate for a domain-general role for the pCC regions in providing complex visual representations to consciousness. Other work in cognitive neuroscience supports and extends this view, showing via meta-analysis that pCC regions participate in a network engaged in autobiographical memory, prospective future thinking, and navigation (Spreng et al., 2009). All such tasks require complex visual representation, and it is interesting that mPFC did not emerge in this meta-analysis. More direct evidence in support of the idea that pCC supports the third- rather than firstperson representations more common in thinking about others rather than the self comes again from the meta-analysis of Denny et al. (2012). In their paper, they found across 107 studies that the precuneus was more active when participants thought about others than when they thought about themselves. Single-study evidence of the idea that visual rather than conceptual representations of people engage pCC comes from Moran et al. (2011), who showed that thinking about social targets' appearance (e.g., Does George W. Bush have a beard?) versus thinking about their character traits (e.g., Is George W. Bush kind?) produces more activation in pCC. This relationship also held true when the social target was the self. Direct investigations of adopting third- versus first-person perspectives have also shown greater pCC involvement during third-person perspective taking (Ruby and Decety, 2001).

## **IS MEDIAL PREFRONTAL CORTEX A HUB FOR INTEGRATING INTERNAL AND EXTERNAL INFORMATION?**

Our second possibility is that the ventral mPFC region identified by Heatherton (2011) serves as a hub that integrates internal and external information into a conscious workspace. On this view, self-reflection would be the canonical task for such a region because it so strongly requires the flexible and ongoing integration of our own knowledge about ourselves with our ever-changing knowledge gained from our sense organs about how we are interacting with the environment, and about how social actors in our environment think about us. Thinking about those social actors independent from ourselves (theory of mind) would drive this machinery to a lesser degree (but still more than thinking about non-social aspects of the world) because rapid and complex integration of sensory, external, and non-sensory conceptual knowledge is required to understand others' goals, intentions, and beliefs, whereas such dynamic processing is much less necessary for thinking about tools or cars or jewelry. This sort of integration into a conscious workspace is also a hallmark of the cognitive processes engaged during "rest," and engendered by the default mode of brain functioning.

# **IS MEDIAL PREFRONTAL CORTEX SPECIALIZED FOR DIRECTING CONSCIOUS THOUGHT PROCESSES?**

Finally, our third possibility is that the ventral mPFC region identified in self-reflection tasks is specialized for helping to decide in which direction our thought processes should proceed. The convergence of heavily processed external sensory inputs with internally generated inputs would also support this view, which of course is not mutually exclusive with the view that mPFC serves as a hub for integration of information from disparate neural processing units. To the degree that deciding where our thoughts should go is a representational process, and that reflection on those thoughts (and our enduring personality traits) is a metarepresentational version of the same process, one would imagine that a system with such functional-anatomic properties would be well-placed to perform both conscious direction of thoughts and self-reflection. That rest and self-reflection so consistently overlap (Qin and Northoff, 2011; Whitfield-Gabrieli et al., 2011) suggests that being free to direct our own thoughts (i.e., not responding directly to the environment or an experimenter-provided task) is a state that mimics the natural process observed when we are asked to reflect directly on our own selves. A prediction of this viewpoint is that decision-making might be tied to activity in the CMS, and indeed research shows that CMS activity predicts freely made decisions up to 7 s before participants indicate becoming aware of the decision having been made (Soon et al., 2008). This third possibility thus may account for the still-puzzling observation that the mPFC is perhaps the most important actor in the brain's default mode network, which itself perhaps serves as a proxy for our ongoing conscious awareness of both our internal and external words. This conjecture awaits empirical investigation however, not least because sampling the ongoing representational processes of the default mode requires disrupting such processes.

# **CONCLUSION**

In summary, we have speculated about several different explanations for the observation that the CMS are observed so consistently to participate in self-reflection. Neuroanatomical connectivity suggests that these regions are heteromodal association areas that derive much of their inputs from upstream regions associated with social information processing, and that pCC in particular gains its inputs from regions of the brain responsible for complex visual representations. Because these regions are associated with social processing, are developed strongly in humans relative to other animals, and humans travel in much larger social networks than do other animals, we speculate that they may form the basis of a special neurocognitive system evolved for social processing. More fundamental characterizations of this system suggest that the anterior midline structure, mPFC, is in fact a domain-general region dedicated as a hub of information processing about the internal and external worlds, and relatedly, that the purpose of such a confluence of representations is to direct our conscious awareness from one moment to the next, switching flexibly between representations of our internal mental life and of the world around us. On this view, mPFC's seeming specialization for social information processing merely reflects its response to stimuli (self and others) that drive the integration of internal and external information sources more strongly than non-social stimuli.

Much research remains to be done to gain greater understanding of how and why the self, other social targets, and the default mode of thought are related to one another, and why they so reliably involve the CMS. Initial support for the idea that mPFC regions might be *necessary* for self-reflection comes from a study with patients with ventral mPFC damage at the site implicated by Kelley et al. (2002) as being maximally involved in self-reflection (Philippi et al., 2012). These patients did not show the self-reference effect in memory, suggesting that mPFC is necessary for encoding information in relation to oneself. Emerging advances in TMS may allow researchers to target more closely these regions for temporary, reversible lesions, or for theta-burst stimulation for temporary increases in excitability of these regions (Vernet et al., 2013). Such studies could provide more controlled

#### **REFERENCES**


evidence to determine whether these regions are *necessary* for reflection about self and other. In parallel, advances in real-time fMRI techniques (deCharms et al., 2004; Hinds et al., 2011) allow for the exquisite control of presentation parameters, such that we can manipulate when participants are asked to reflect on self and others to moments when activation in either mPFC or pCC are high or low, and determine with a great degree of accuracy what effects natural fluctuations in the default mode at any given moment might have on our abilities to accurately represent ourselves.

#### **ACKNOWLEDGMENTS**

This work was supported by a grant from the National Institutes of Health (R01MH059282) to Todd F. Heatherton.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 02 May 2013; paper pending published: 24 June 2013; accepted: 04 July 2013; published online: 17 July 2013. Citation: Moran JM, Kelley WM and Heatherton TF (2013) What can the organization of the brain's default mode network tell us about self-knowledge? Front. Hum. Neurosci. 7:391. doi: 10.3389/fnhum.2013.00391*

*Copyright © 2013 Moran, Kelley and Heatherton. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.*

# Associative account of self-cognition: extended forward model and multi-layer structure

# **Motoaki Sugiura1,2\***

1 Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

2 International Research Institute of Disaster Science, Tohoku University, Sendai, Japan

#### **Edited by:**

Niall W. Duncan, University of Ottawa, Canada

#### **Reviewed by:**

David Rudrauf, Institut National de la Santé et de la Recherche Médicale, France Francesca Ferri, University of Ottawa,

Canada

#### **\*Correspondence:**

Motoaki Sugiura, Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Seiryo-machi 4-1, Aoba-ku, Sendai 980-8575, Japan e-mail: motoaki@idac.tohoku.ac.jp

The neural correlates of "self" identified by neuroimaging studies differ depending on which aspects of self are addressed. Here, three categories of self are proposed based on neuroimaging findings and an evaluation of the likely underlying cognitive processes. The physical self, representing self-agency of action, body-ownership, and bodily selfrecognition, is supported by the sensory and motor association cortices located primarily in the right hemisphere. The interpersonal self, representing the attention or intentions of others directed at the self, is supported by several amodal association cortices in the dorsomedial frontal and lateral posterior cortices. The social self, representing the self as a collection of context-dependent social-values, is supported by the ventral aspect of the medial prefrontal cortex and the posterior cingulate cortex. Despite differences in the underlying cognitive processes and neural substrates, all three categories of self are likely to share the computational characteristics of the forward model, which is underpinned by internal schema or learned associations between one's behavioral output and the consequential input. Additionally, these three categories exist within a hierarchical layer structure based on developmental processes that updates the schema through the attribution of prediction error. In this account, most of the association cortices critically contribute to some aspect of the self through associative learning while the primary regions involved shift from the lateral to the medial cortices in a sequence from the physical to the interpersonal to the social self.

**Keywords: self, self-recognition, self-awareness, body-ownership, self-agency, social cognition, associative learning, neuroimaging**

# **INTRODUCTION**

A sporadic quest for the neural basis of "self"using functional neuroimaging appears to have emerged at the end of the last century. A number of researchers were interested in the cognitive processes related to physical self-awareness during action and consequential sensation (McGuire et al., 1996a; Blakemore et al., 1998; Fink et al., 1999), whereas others investigated the self-relevance of memory and knowledge (Fink et al., 1996; Craik et al., 1999; Kelley et al., 2002). An initial study evaluating stimulus-independent thought (McGuire et al., 1996b) drew attention to the relevance of spontaneous neural activity during a conscious resting state (Raichle et al., 2001) to the self-related cognitive process (Gusnard et al., 2001). The subsequent surge in studies of self-face recognition (Keenan et al., 2000; Kircher et al., 2000; Sugiura et al., 2000) rested primarily on an evolutionary or developmental perspective. Perceptions of others' communicative intentions toward the self (Kampe et al., 2003) and perspective-taking (Vogeley et al., 2004) appear to be other independent issues. It did not take long for researchers to realize that the cortical regions supporting selfspecific or self-relevant activation were far from consistent across studies.

The response of researchers to this chaotic situation has also varied considerably. Some have been pessimistic regarding the existence of a special neural system for the self (Gillihan and Farah, 2005; Platek et al., 2008), whereas others have remained optimistic and attempted to identify such a system by sorting out how previous studies have addressed the concept of self. One such approach highlighted cortical midline structures (Northoff and Bermpohl, 2004; Northoff et al., 2006), another focused on the right lateral cortices (Keenan et al., 2000; Feinberg and Keenan, 2005), and yet another tried to reconcile these two views (Uddin et al., 2007).

This paper attempts to provide a unified framework for the neural underpinnings of the self in the context of a pessimistic stance toward the existence of a self-specific neural system. First, neuroimaging studies investigating self-related processes are reviewed, and the concepts of the self and their related brain networks are roughly categorized into three areas. Then, a unique characteristic or computational architecture that is potentially common to the processes of the three categories is proposed. Furthermore, I propose a layer structure characterized by cross-layer dynamics that operates across these three categories. Finally, the manner in which self is related to midline brain regions in this model is discussed. The proposed model is an updated version of one that was previously presented (Sugiura, 2011).

# **THREE CATEGORIES OF SELF AND NEUROIMAGING FINDINGS**

The concepts of self or self-related processes addressed in previous neuroimaging studies may be divided into three categories: the physical self, the interpersonal self, and the social-value of the self. This categorization takes into account the presumably developmental context in which self-awareness is experienced as well as the distribution of reported self-relevant activation. The known basic functional characteristics of the relevant activated regions will be briefly discussed.

#### **PHYSICAL SELF**

One prominent category of self is the body-grounded self that dissociates one's physical existence from the external environment. Research on this category often focuses on the ability to dissociate self from non-self, such as one's own face from another's face, one's own body from another's body, one's own action from another's action, and one's own voice from another's voice. This category of self is conceptually unambiguous and experimental manipulation is often clear. The concept of self in this category may overlap with that of James' description of "physical self" (James, 1890) or other researchers' descriptions of "ecological self" (Neisser, 1988) and "minimal self" (Gallagher, 2000). This category of self is of central interest to psychologists studying animals and infants. There is a strong expectation of the existence of specialized neural regions underpinning self-recognition that stems from the fact that only a few species of animals show evidence of visual self-recognition in the mirror (Gallup, 1982; Suddendorf and Collier-Baker, 2009).

Neuroimaging studies investigating the cortical foundation of the physical self have adopted three major experimental approaches. The first approach is to contrast brain activation during the perception of a visual or auditory stimulus relevant to one's own body with activation during the perception of perceptually similar but self-irrelevant stimuli. Studies using this approach present subjects with a picture or video clip of a face or body (Kircher et al., 2000; Platek et al., 2004, 2006; Sugiura et al., 2005a, 2006, 2008, 2012; Uddin et al., 2005; Devue et al., 2007; Kaplan et al., 2008; Ferri et al., 2012; Oikawa et al., 2012), or a recorded voice (Nakamura et al., 2001); the required task is either explicit or implicit recognition (e.g., passive viewing or performance of an unrelated task). The second approach addresses the sense of body-ownership or of body-location drift, which is illusorily induced by a synchronous sensory stimulation including tactile stimuli (Ehrsson et al., 2004, 2005; Tsakiris et al., 2007; Ionta et al., 2011). Contrasting the synchronized and desynchronized conditions can isolate the cortical activation related to such a sense. The third approach deals with the sense of self-agency or self-attribution concerning one's own actions. Studies have identified neural activation in response to modulated visual feedback during hand action or manipulation of a cursor or agent on a computer (Fink et al., 1999; Farrer et al., 2003, 2008; Leube et al., 2003; David et al., 2007; Schnell et al., 2007; Corradi-Dell'Acqua et al., 2008; Spengler et al., 2009; Yomogida et al., 2010), auditory feedback during speech (McGuire et al., 1996a; Hashimoto and Sakai, 2003; Fu et al., 2006), and tactile feedback while tickling oneself (Blakemore et al., 1998). Some studies have manipulated self-agency simply by instruction (Farrer and Frith, 2002; Schnell

et al., 2007), whereas others have examined effects of the trial-bytrial fluctuation in subjective awareness in response to the same stimuli (David et al., 2007; Farrer et al., 2008).

Although the regions reportedly involved in this activation vary across studies and approaches, they include primarily the sensory and/or motor association cortices (**Figure 1**) and depend on the sensory modality of the stimulus used. Activation of the visual association cortices, including the ventral and dorsal pathways (**Figures 1A,B**, respectively), has been reported in studies using visual stimuli to address visual self-face or self-body recognition (Kircher et al., 2000; Sugiura et al., 2005a, 2006, 2008, 2012; Uddin et al., 2005; Platek et al., 2006; Kaplan et al., 2008; Ferri et al., 2012; Oikawa et al., 2012), the illusory sense of body-ownership or location (Ehrsson et al., 2004; Tsakiris et al., 2007; Ionta et al., 2011), and the violation or awareness of action-agency (Fink et al., 1999; David et al., 2007; Corradi-Dell'Acqua et al., 2008; Farrer et al., 2008; Spengler et al., 2009; Yomogida et al., 2010). Auditory association cortices (**Figure 1C**) are activated during the perception of manipulated feedback of self-voice during speaking aloud (McGuire et al., 1996a;Hashimoto and Sakai, 2003; Fu et al., 2006). Activation of somatosensory association cortices (**Figure 1D**) has been reported in studies using tactile input to manipulate the agency of self-tickling actions (Blakemore et al., 1998) or to induce an illusory sense of body-ownership or location (Ehrsson et al., 2004; Tsakiris et al., 2007; Ionta et al., 2011).

Activation of motor association cortices is frequently reported in studies in which a subject's motor action plays a critical role in self-relevance. These regions include the dorsal and ventral aspects of the premotor cortex (**Figures 1E,F**, respectively) and several medial motor association cortices, such as the supplementary motor area (SMA; **Figure 1G**) and cingulate motor area (**Figure 1H**). Examples of such studies include those in which subjects executed motor action while self-agency was manipulated (Farrer and Frith, 2002; Farrer et al., 2003, 2008; David et al., 2007; Schnell et al., 2007; Corradi-Dell'Acqua et al., 2008; Spengler et al., 2009; Yomogida et al., 2010).

However, the involvement of sensory or motor association cortices sometimes has no apparent relevance to the sensory processing of the stimulus or motor output during the task. Such involvement requires explanation in terms of the internal representation of the physical self. For example, activation of somatosensory and premotor cortices has often been reported in studies investigating self-face or self-body recognition using pictures (Uddin et al.,2005; Platek et al.,2006; Sugiura et al.,2006,2008,2012; Ferri et al.,2012). The visual–somatosensory association cortex in the intraparietal sulcus (**Figure 1I**), which has been implicated in the visuospatial motor control of extremities, has been found to be activated in many studies on self when the task is relevant to bodily action either directly (Fink et al., 1999; Ehrsson et al., 2004, 2005; Farrer et al., 2008) or indirectly (e.g., self-face or self-body recognition using pictures involving expressions or actions) (Sugiura et al., 2005a, 2006, 2008, 2012; Oikawa et al., 2012). Additionally, many of these activated areas overlap with regions receiving vestibular input, such as the medial temporal (MT) or medial superior temporal (MST) areas, the ventral intraparietal area (VIP), areas 2v and 3aV, and premotor regions (Smith et al., 2012; zu Eulenburg et al., 2012). The insula (**Figure 1J**), known to include primary and

including the supplementary motor area [SMA, **(G)**] and anterior cingulate cortex [ACC, **(H)**]}; and intraparietal sulcus **(I)**. The bottom left panel shows the schema within the opened Sylvian fissure in the right hemisphere to expose the insular cortex **(J)**. Examples of neuroimaging data: activation specifically observed during self-face recognition in picture [**(K)** (Sugiura et al., 2012)]; activation during speech with manipulated auditory feedback of own voice [**(L)** (Hashimoto and Sakai, 2003)]; activation during violated self-agency of control of avatar in computer game [(**M)** (Yomogida et al., 2010)]; and awareness of self-agency of control of cursor in computer game [**(N)** (Farrer and Frith, 2002)].

association cortices for interoception (sense of the physiological conditions of the entire body) and to be involved in a wide range of subjective feelings (Craig, 2002, 2009), is also activated without the manipulation of interoceptive input. Activation of this region was observed during the recognition of self-face or self-body in a picture (Kircher et al., 2000; Devue et al., 2007; Ferri et al., 2012), the sense of action self-agency (Farrer and Frith, 2002; Farrer et al., 2003; Leube et al., 2003; David et al., 2007; Corradi-Dell'Acqua et al., 2008), and the sense of body-ownership (Ehrsson et al., 2004; Tsakiris et al., 2007). These findings may be explained by the fact that bodily self-recognition is grounded by the experience of bodily action accompanied by visual, somatosensory, vestibular, and interoceptive feedback. These interpretations in terms of the representational role of the sensory and motor association cortices will be detailed in Section "Physical Self and Sensorimotor Schema."

It is interesting to note that some of these parietal sensory association and frontal premotor cortices coincide with the visual–motor association system known as the mirror neuron system (MNS). This apparently contradicts the incompatible concept of "self-specific" and the MNS; which is resolved in the proposed model (See Physical Self and Sensorimotor Schema). Mirror neurons are a class of neurons that have been observed to discharge when a monkey performs a goal-directed motor act as well as when a monkey observes another individual performing the same or a similar motor act (Rizzolatti et al., 2001; Nelissen et al., 2011). In humans, the MNS has been identified as a homolog of the frontoparietal network of mirror neurons in monkeys and is considered to play a critical role in action understanding, imitation, and communication (Rizzolatti and Craighero, 2004; Iacoboni, 2005). Therefore, this system is primarily conceptualized as a mechanism involved in recognizing and interacting with others.

Moreover, these studies reported the activation of several amodal association cortices. Activation of the right lateral prefrontal cortex, specifically the inferior and middle frontal gyri, has often been reported during the recognition of self-face or selfbody (**Figure 1K**) (Platek et al., 2004, 2006; Sugiura et al., 2005a, 2006, 2008, 2012; Uddin et al., 2005; Devue et al., 2007; Kaplan et al., 2008), voice (Nakamura et al., 2001), action-agency violation (**Figure 1L**) (Fink et al., 1999; Hashimoto and Sakai, 2003; David et al., 2007; Schnell et al., 2007; Farrer et al., 2008), and bodyownership (Ehrsson et al., 2004, 2005; Tsakiris et al., 2007). The manipulation of sensory-feedback for action often activates the temporoparietal junction (TPJ), the posterior part of the superior temporal sulcus (pSTS), and the medial prefrontal cortex (MPFC) (McGuire et al., 1996a; Farrer and Frith, 2002; Farrer et al., 2003, 2008;Hashimoto and Sakai, 2003; Leube et al., 2003; Fu et al., 2006; Spengler et al., 2009; Yomogida et al., 2010), which are typically considered multimodal or amodal association cortices that are implicated in conceptual rather than perceptual processes. These findings will be discussed separately from sensory or motor association cortices in Section "Multi-Layer Structure and Cross-Layer Dynamics."

#### **INTERPERSONAL SELF**

When an individual notices that he or she is being looked at or hears his/her own name being called, he/she becomes aware that the attention or intentionality of another person is directed at him/her. This awareness is a basic mindset during social interaction. This aspect of self is obviously distinct from the physical self because it inherently requires the existence of another person. An influential inventory, the Self-Consciousness Scale (Fenigstein et al., 1975), particularly its public subscale, has been developed to measure the degree to which an individual has this type of awareness.

The activation related to this awareness is observed in several amodal association cortices in the medial frontal and lateral posterior cortices (**Figure 2A**). Although varying widely across studies, activation has been identified in the MPFC encompassing the adjacent anterior cingulate cortex (ACC) (Kampe et al.,2003; Schilbach et al., 2006; Steuwe et al., 2012), the TPJ/pSTS (Pelphrey et al., 2004a; Schilbach et al., 2006; Steuwe et al., 2012), the anterior temporal cortex (ATC) (Kawashima et al., 1999; Calder et al., 2002; Kampe et al., 2003; Wicker et al., 2003), the insula (Kawashima et al., 1999; Calder et al., 2002; Schilbach et al., 2006), and the

cerebellum (George et al., 2001; Wicker et al., 2003; Schilbach et al., 2006) during the perception of directed, rather than averted, eye-gaze. Activation of the MPFC/ACC, TPJ/pSTS, and ATC has also been reported in studies that compare activation during the hearing of one's own name with the hearing of others' names (**Figure 2B**) (Kampe et al., 2003; Perrin et al., 2005; Tacikowski et al., 2011). Activation is also observed in these regions when subjects believe that they are interacting with a real person rather than engaging in a similar but non-real interaction (**Figure 2C**) (Rilling et al., 2004; Jeong et al., 2011). Additionally, subjects who score higher on the Self-Consciousness Scale (Fenigstein et al., 1975) show a larger degree of activation in the dorsal part of the MPFC (dMPFC) during a simple sensorimotor (deviant letter detection) task (Eisenberger et al., 2005).

However, previous studies have rarely treated self-awareness as a central concept related to the interpretation of activation in these cortical regions. These regions have often been recognized as a cortical network supporting the inference of another's mental state, namely,mentalizing or theory of mind (ToM) (Gallagher and Frith, 2003; Frith and Frith, 2006; Senju and Johnson, 2009; Spreng et al., 2009). Furthermore, it has been proposed that this network plays a role in the development of event schemata in general, including person-schema and self-schema (Krueger et al., 2009). The assumed properties of this network provide the basic reasoning for labeling this category of self the "interpersonal self," which will be detailed in Section "Interpersonal Self and Interpersonal Schema."

It is worth noting that some of these regions are deactivated rather than activated during self-face recognition. Activation in the TPJ/pSTS or its surrounding cortices is decreased while viewing the self-face compared with familiar or unfamiliar faces (Sugiura et al., 2005a, 2008; Uddin et al., 2005; Devue et al., 2007; Morita et al., 2008), which indicates a clear neural dissociation between physical and interpersonal selves.

#### **SOCIAL-VALUE OF SELF**

Self-reflection typically includes thoughts about one's social-value such as "Am I good-natured?" or "Am I good-looking?" or "Am I intelligent?" or "Am I successful in my career?" Most of the attributes assigned to the self carry some social-value, and individuals are typically aware of the gap between one's current self and one's ideal self (Festinger, 1954; Higgins, 1987). This type of socialvalue is an important aspect of the "social self" according to James (1890) and is assumed to be an important determinant of human behavior [e.g., Self-Efficacy Theory (Bandura, 1982)]. To experimentally address this type of self in neuroimaging studies, self-trait (e.g., personality trait, ability) judgment tasks are typically utilized. Additionally, the perception of the evaluation of self by others, even the perception of others who have a high or low level of an attribute that is significant to the self (Gutierres et al., 1999), is known to affect self-value. Although this type of self resembles the interpersonal self in that it is highly relevant to the existence of another person, the "person" is typically generalized to people or society rather than confined to a specific person. Furthermore, the interpersonal self does not necessarily involve social-value. It is therefore reasonable to categorize self-value separately from interpersonal self.

Indeed, the cortical regions implicated in self-value have, at least in part, a different distribution than do those implicated in the interpersonal self. Specifically, tasks that are assumed to manipulate the social-value of self typically activate the ventral part of the MPFC (vMPFC) and the posterior part of the cingulate cortex (PCC) or its adjacent medial parietal cortex (i.e., the precuneus) (**Figure 3A**). Activation of these regions has been reported during self-trait judgment, specifically when contrasted with trait-valence judgment (Craik et al., 1999; Schmitz et al., 2004) or other trait judgments (**Figure 3B**) (Craik et al., 1999; Kelley et al., 2002; Heatherton et al., 2006; D'Argembeau et al., 2007). Similarly, activation in these regions has been identified when contrasting self-descriptive and non-descriptive trait adjectives (Kircher et al., 2002; Macrae et al., 2004) and when the trait adjective is correlated with self-descriptiveness (Moran et al., 2006). Moreover, the perception of the evaluation of self by others activates these regions (Izuma et al., 2008), particularly in subjects whose self-evaluation is vulnerable to evaluation by others (Somerville et al., 2010). Interestingly, the perception of the evaluation of self by familiar others activates the dMPFC (Korn et al., 2012), which is thought to be the neural correlate of the interpersonal self, rather than vMPFC. This may be explained by the fact that this experimental manipulation affects mental representations of the self in relation to specific others rather than those related to the value of the self, illustrating the conceptual difference between the interpersonal self and the social-value of the self.

Like the physical self, the social self dissociates self and other, but it does so in a different way. The social self encompasses any people or objects that are relevant or behaviorally significant to the self, which are considered "other" in terms of the physical self. The vMPFC and PCC are activated during name and face recognition of oneself and friends relative to recognition of unfamiliar people (Sugiura et al.,2008;Tacikowski et al.,2012), and the vMPFC is correlated with the amount of self-referential thought (D'Argembeau et al., 2005). On the other hand, activation of these regions is often absent when self-trait judgment is compared with trait judgment about familiar people, such as friends and relatives (Schmitz et al., 2004; Benoit et al., 2010). Self-face recognition involves activation of the vMPFC when the number of other faces in the other trials in the task sequence is increased, probably due to the self-value processing induced by social comparison (Sugiura et al., 2012). In a similar task design using young female subjects, activation of the PCC for self-face was enhanced when the female faces in other trials were less attractive, particularly when the subject's self-esteem was high (Oikawa et al., 2012).

Again, these cortical regions are unlikely to be utilized exclusively for the processing of social-value. The vMPFC and the medial orbitofrontal cortex (mOFC),which is sometimes regarded as identical with or adjacently distinct from the vMPFC, are known to represent the value of objects in general and to play critical roles in value-based decision making (Rangel et al., 2008; Rushworth et al., 2011). This general region comprises a reward system that operates in conjunction with other deep structures, such as the

An example of neuroimaging data: activation during self-trait judgment about the personality trait adjective [**(B)**; (Kelley et al., 2002)].

striatum and the midbrain dopamine system, which are sometimes activated during self-trait judgment (Kircher et al., 2002; Moran et al., 2006; Benoit et al., 2010) or perception of selfevaluation by others (Izuma et al., 2008; Korn et al., 2012). The relationship between the reward system and self-related processes is a matter of recent discussion (Northoff and Hayes, 2011). The PCC and the adjacent precuneus are involved in a wide range of highly integrated processes, such as visuospatial imagery, episodicmemory retrieval, and self-referential processes (Wagner et al., 2005; Cavanna and Trimble, 2006). This set of midline cortical regions is also considered to be a major component of the default mode network that is active during a conscious resting state and deactivated during the execution of attention-demanding tasks (Gusnard et al., 2001; Raichle et al., 2001).

#### **OTHER ASPECTS OF SELF**

One may consider memory, especially autobiographical memory, as a critical factor of self. Numerous functional imaging studies have investigated the neural activity specifically observed during the retrieval of an autobiographical memory. The medial prefrontal and parietal cortices, including the cingulate cortex and the lateral temporal and parietal regions with some regions lateralized to the right (Svoboda et al., 2006; Buckner and Carroll, 2007; Spreng et al., 2009) exhibit activation during such a task. These areas overlap with the cortical regions proposed to be the neural underpinnings of the three categories of self. This suggests that autobiographical memory is not merely a single essential factor but rather the "all-star" of self-related cognitive processes.

Some researchers assume perspective-taking to be a key concept in the distinction of self from other. However, the findings of neuroimaging studies investigating this issue may also be explained by the framework of the three categories of self, particularly the physical and interpersonal selves. Many neuroimaging studies compare first-person (1P) and third-person (3P) perspectives to address this issue. Cortical activation is typically more prominent in a 3P rather than a 1P perspective, but activation of associated brain regions varies widely across studies. These findings were somewhat clarified when perspective-taking was divided into visuospatial and mental perspectives, and activation was assumed to reflect the increased cognitive load related to the non-canonical nature of the 3P perspective. Greater activation for 3P visuospatial perspective-taking relative to 1P visuospatial perspective-taking is typically reported in the visual association and premotor cortices (Vogeley et al., 2004; David et al., 2006, 2008a), which overlap with the neural correlates of the physical self. This finding may be explained by the cognitive load involved in the imaginary physicallocation change (i.e., moving self-body) required to obtain a noncanonical 3P viewpoint. Regarding mental perspective-taking, a greater activation for the 3P relative to the 1P perspective is frequently reported in the pSTS/TPJ and dMPFC (Ruby and Decety, 2001, 2003, 2004; David et al., 2008a; Schnell et al., 2011; Ramsey et al., 2013), which overlap with the neural correlates of the interpersonal self. This overlap appears to be reasonable because taking the mental perspective of others (intention, emotion, belief) is synonymous with ToM. On the other hand, many of these studies have reported a greater activation in the 1P compared with the 3P perspective in the MPFC and PCC, which are the proposed neural correlates of the social self. It is often difficult to conclusively attribute this finding to self-cognition, since it is usually explained by either behavioral significance (i.e., the social self) or differential default mode activity (Gusnard et al., 2001; Raichle et al., 2001) due to differences in task difficulty (McKiernan et al., 2003).

#### **HYPOTHESIS: THREE LAYERS OF INTERNAL SCHEMA**

In the preceding section, the self was divided into three individual categories that differ according to the related supporting cognitive processes and neural substrates. The current section, however, proposes a common characteristic or computational architecture that underlies the processes of these three categories. In short, the common characteristic is a forward prediction model, which is a rather common and classical conceptualization in models of the physical self. It has been assumed that the physical self is the product of an associative learning process based on the repeated experiences of bodily motion and sensory-feedback.

Here, a novel attempt will be made to adapt the forward prediction model to the interpersonal and social selves with the intention of explaining all categories of self within the framework of associative learning. A critical component of this adaptation is the internal schema that denotes the association between the neural-representation of the output plan and the feedback input (**Figures 4A,B**); this schema is assumed to exist for each target of the output and is modified depending on context. In this view, the self may be defined as a label for the capability of forward prediction (**Figure 4B**) in any system that has such characteristics. Neuroimaging findings appear to be explained by top-down and bottom-up attention to the schema that is typically driven by task requirements and prediction error, respectively.

Conceptually, the schema is the basis for all cognitive operations, including perception and behavioral control. The schema is used as an inverse model to plan output (**Figure 4C**) or even to represent each element of the external environment and may be used to simulate a schema of the mind of another; that is, to infer the internal process of others based on the observed output of that person. Given the diverse utility of the schema, the self is only a phenomenon that is occasionally experienced during its functioning, while reflecting the very basic characteristics of the schema. Additionally, a hierarchical layer structure of the three categories of self and the dynamics across the layers are also important features of the proposed model. The hierarchical structure stems from the developmental relationship between the three schemata and serves as the basis of cross-layer interaction, which may be critical for the integrity of the three self-concepts.

#### **PHYSICAL SELF AND SENSORIMOTOR SCHEMA**

The concept of the forward model was first applied to explain the sense of self-agency in action. The sense of self-agency, or the self-attribution of action, is widely assumed to have been derived from the consistency between the sensory input that results from action and the prediction emerging from the action intention or collateral output from the motor system (**Figure 4B**) (Wegner and Wheatley, 1999; Sato and Yasuda, 2005; David et al., 2008b). One is convinced that the observed action of one's own hand is actually performed by oneself because the action is somatically experienced (i.e., somatosensory perception) and looks (i.e., visual perception) as predicted. Frith and colleagues (Frith et al., 2000; Frith, 2005) incorporated this conceptualization into a detailed cognitive model by extending the model of feed-forward motor control (Wolpert et al., 1995) to explain the impairment in the sense of self-agency, or the delusion of control, which is a characteristic symptom of schizophrenia. In this model, the prediction of sensory input as a consequence of action is based on intended motor commands and cancels actual input. Subjectively, a successful cancelation is experienced as one's unawareness of the sensory consequences of one's own actions and is exemplified as the attenuated sensation of self-generated tickling (Weiskrantz et al., 1971; Blakemore et al., 1999). In functional neuroimaging, this cancelation is detected as an attenuation of the activation related to sensory processing when sensory input is caused by self-generated action rather than being externally produced (Blakemore et al., 1998). More frequently, in fact, this functioning is captured as an increase in activation during the violation of action self-agency due to experimental manipulation (McGuire et al., 1996a; Fink et al., 1999; Hashimoto and Sakai, 2003; Fu et al., 2006; David et al., 2007; Corradi-Dell'Acqua et al., 2008; Farrer et al., 2008; Spengler et al., 2009; Yomogida et al., 2010).

Here, the concept of a sensorimotor schema, or the learned association between one's motor plan and the feedback sensory input (**Figure 4D**), is introduced. The sensorimotor schema exists for each effector or movement coordinated by multiple muscles and is adaptively modified depending on physical context, including posture and the external physical environment. The evidence that the schema is indeed constructed through associative learning has been experimentally provided; the repeated experience of an action and its effect on an object on a computer monitor later produce the sense of action self-agency for that virtual effector, and the related neural responses are similar to those seen in previous studies of action self-agency (Schnell et al., 2007; Spengler et al., 2009; Yomogida et al., 2010). The sensorimotor schema allows for the generalization of the forward model to different phenomena of the physical self, such as the sense of body-ownership and self-face recognition in non-contingent images (e.g., static images, prerecorded videos). It has been shown that body-ownership requires a pre-existing internal representation of the position of the limbs (Tsakiris and Haggard, 2005; Costantini and Haggard, 2007). Given that such a representation is constructed and continuously updated by matching the feed-forward prediction and re-afferent sensory input during active movement (Synofzik et al., 2006;Tsakiris et al.,2006), this representation is closely related to or identical with a sensorimotor schema. Self-face recognition ability in a non-contingent image is also likely to depend on a sensorimotor schema. Infants seem to consolidate the visual representation of one's own face into long-term memory during the experience of viewing a contingent self-face in the mirror; this idea is supported by the observation that self-face recognition first develops in a contingent and then in a non-contingent image (Bigelow, 1981). Therefore, the unique characteristic of the visual representation of the self-face seems to be realized by its association with the experience of action self-agency or body-ownership and, thus, with a sensorimotor schema.

The activation of sensory and motor association cortices related to the physical self is parsimoniously explained by attention to the sensorimotor schema. In this situation, it is advantageous to separate top-down from bottom-up attention. Top-down attention is induced by a variety of experimental manipulations in which the use of information in the schema is necessary or advantageous. Activation of sensory or motor association cortices is observed when perceived motion is explicitly required to be self-produced (Farrer and Frith, 2002) or when the task demands monitoring of one's own motor action control (Ogawa and Inui, 2007; Schnell et al., 2007). On the other hand, bottom-up attention is typically driven by prediction error, which may contribute to a recalibration of the schema. This line of interpretation most likely refers to neural activation in response to manipulated sensory-feedback, that is, a violation of self-agency in action (McGuire et al., 1996a; Blakemore et al., 1998; Fink et al., 1999; Farrer et al., 2003, 2008; Hashimoto and Sakai, 2003; Fu et al., 2006; David et al., 2007; Schnell et al., 2007; Corradi-Dell'Acqua et al., 2008; Spengler et al., 2009; Yomogida et al., 2010). Activation while experiencing a sense of body-ownership (Ehrsson et al., 2004, 2005; Tsakiris et al., 2007; Ionta et al., 2011) and bodily self-recognition in a non-contingent image (Uddin et al., 2005; Platek et al., 2006; Sugiura et al., 2006, 2008, 2012) may be attributed to either type of attention. The commonality of attention and consciousness may explain the activation of these regions in terms of top-down access to information in the schema. The activation is also attributable

to prediction error when perceptual input differs from what was expected: illusion-induced body-ownership may be imperfect, and some strange feelings may remain if the presented self-face picture is somewhat different from what one usually sees in the mirror while one remains sure that the face is one's own.

The sensorimotor schema explains not only self-cognition but also any cognitive operation related to one's physical interaction with the external environment. In fact, the forward model, as adapted to self-cognition, was originally developed for motor control (Wolpert et al., 1995), and the concept of sensorimotor schema was adopted from that model. The sensorimotor schema, or the association of the motor plan with sensory-feedback, may be used as an inverse model to calculate the motor plan to obtain the intended sensory-feedback (**Figure 4C**). This idea is consistent with the conceptual framework of ideomotor theory, which assumes a common coding of action and consequential perception (Prinz, 1997). Furthermore, the sensorimotor schema may play a critical role in an individual's mental representation of the physical environment. A person can have intention and a motor plan for interaction with many objects in the immediate external environment (e.g., gazing, reaching), and an essential property of the physical environment is this potential interaction, which may be represented in the sensorimotor schema. This notion is compatible with thefact that the cortical areas implicated in sensory or spatial attention overlap primarily with those supporting the sensorimotor schema (Downar et al., 2000; Corbetta and Shulman, 2002).

Furthermore, the sensorimotor schema seems to be exploited to simulate the schema of others; that is, it can be used to infer the intention or action goals of others. The schema may gain the simulation ability by associating one's own motor output with the perceived contingent motor action of others in an interactive situation where the self and others share an intention or action goal. Such an interactive environment is common in the daily relationship between infants and their caretakers (Kaye and Fogel, 1980; Cohn and Tronick, 1988). This view is consonant with the hypothesis that the MNS is forged by sensorimotor association learning (Heyes, 2010). Further, this view implicate that the mirror neurons are a subcomponent of the simulation-capable sensorimotor schema that associates one's own motor actions not only with the same action but also with different but related actions of others. This is supported by the fact that, in the cortical areas reported to accommodate mirror neurons in primates, there are a greater number of "counter-mirror neurons," which code other's actions that are different from, but related to, one's own actions (Gallese et al., 1996). Also, in a human neuroimaging study, activation of such regions was greater during observation of other's actions that were complimentary (i.e., in joint action) to one's own actions than during observation of immitative actions (Newman-Norlund et al., 2007). Additionally, activation during the observation of another's actions is not limited to the classic human MNS (i.e., inferior parietal and frontal cortices) but has also been identified in multiple visual and motor association cortices (Caspers et al., 2010).

#### **INTERPERSONAL SELF AND INTERPERSONAL SCHEMA**

The existence of forward prediction during an individual's social interaction may be empirically or intuitively plausible. An implicit expectation about the range of possible responses usually arises in situations in which one individual greets another. This is why people become surprised at an unexpected response or the lack of a response from the other person. The range of expected responses greatly differs depending on the identity of the responder (i.e., degree of familiarity and various demographic factors such as age, gender, cultural background, and situational context). The range of expected responses is likely to be updated after repeated experiences of prediction error with a specific familiar person or a specific type of unfamiliar persons.

In this context, it appears reasonable to assume the existence of an interpersonal schema that represents a link between one's social action (i.e., output plan) and the expected responses (i.e., feedback) of others (**Figure 4E**). The schema is constructed following repeated exploratory social interactions in daily life; that is, through associative learning involving one's own social actions toward a person and the feedback (**Figures 4A,B**). The schema exists for each familiar person or for a specific type of people and is adaptively modified depending on social contextual cues such as time, place, and occasion. These characteristics are comparable to those of the sensorimotor schema in terms of the way the schema develops, that the schema exists for each target of output, and that it is modified depending on context.

Several neuroimaging findings support the conceptualization of the interpersonal schema as the basis of the interpersonal self. Activation related to the interpersonal self appears to be explained by either top-down or bottom-up attention related to the interpersonal schema in a way that is similar to the relationship between the physical self and the sensorimotor schema. It appears reasonable to regard awareness that another's attention or intention is directed at oneself as an example of top-down attention to the interpersonal schema. In other words, activation of several medial and lateral posterior cortices during the perception of self-directed eye-gaze (Calder et al., 2002;Kampe et al., 2003;Wicker et al., 2003; Pelphrey et al., 2004a; Schilbach et al., 2006; Steuwe et al., 2012), hearing one's own name being called (Kampe et al., 2003; Perrin et al., 2005; Tacikowski et al., 2011), or real-time interaction with others (Rilling et al., 2004; Jeong et al., 2011) may reflect one's top-down attention to the representation of the other's potential response to one's own social action. Bottom-up attention is also represented by neural activation in this region in response to prediction error or the perception of an unexpected social response as feedback to one's own action. During a simple two-player strategy game, when the subject believes that the opponent is responding based on the prediction of the subject's next action, the prediction error of the perceived opponent's action induces activation in these regions (Hampton et al., 2008).

Furthermore, the functioning of the interpersonal schema is not specific to self-cognition but also relates to any cognitive operation associated with interpersonal interaction. The schema may be used as an inverse model to calculate the behavioral plan of social action toward another person to obtain an intended social response (**Figure 4C**). Accordingly, the neural correlates of the schema are more activated during speech production toward a virtual agent than during an overt description of the situation (Sassa et al., 2007). An individual can have an intention and a plan of social interaction (or of no interaction) in relation to many people in the immediate social environment. An essential property of the immediate social environment is this potential, which is represented in the interpersonal schema. A similar notion, referred to as "social attention," is thought to be supported by the same cortical network (Nummenmaa and Calder, 2009). Furthermore, the simulation capacity of the interpersonal schema, or the inference of the intention and plan of another's social action based on perceived action, may partially overlap with ToM and may explain the overlap of their neural correlates (Gallagher and Frith, 2003; Frith and Frith, 2006; Spreng et al., 2009). However, it is important to note that ToM addresses both the social and non-social beliefs and intentions of others. According to a theory of the role of this network in the development of event schemata in general, the MPFC is assumed to support an abstract dynamic summary representation in the form of event simulators, and its interaction with posterior cortical areas is assumed to comprise knowledge of social events (Krueger et al., 2009). Activation of the implicated cortical regions has been reported in studies evaluating the detection of prediction-violating behavior or objects in the absence of selfinvolvement or social context (Grezes et al., 2004; Pelphrey et al., 2004b; Wakusawa et al., 2009). Thus, the mature interpersonal schema functions independent of self-cognition and comprises one aspect of a cognitive system supporting higher social and nonsocial processes. Nevertheless, working from the perspective that the evolution of intelligence in primates has been driven by social demand (Humphrey, 1976; Byrne and Whiten, 1988), it is tempting to assume that the initial interpersonal schema is the origin of the entire system.

#### **SOCIAL-VALUE SCHEMA**

Forward prediction is also plausible during the evaluation of one's own social-value. People are surprised when they receive an extremely high or low evaluation for a certain behavior; that is, an individual is relatively unaware of having obtained an evaluation when the evaluation is within the predicted range. It is assumed that humans have multiple self-concepts and that selfvalue is dependent on social role (e.g., parent, friend, worker) (Stryker and Statham, 1985; Markus and Cross, 1990; Roberts and Donahue, 1994). Thus, it appears reasonable to assume a specific range of the predicted evaluation for each contextual role, and this is updated through the feedback of prediction error.

It is assumed herein that the social-value schema represents a link between one's social behavior (i.e., output plan) and the predicted evaluation of this behavior (i.e.,feedback) (**Figure 4F**). This schema is constructed for each contextual role through repeated experiences with social evaluations, which result in the learning of associations between one's own social behaviors and the evaluative feedback they elicit (**Figures 4A,B**). Again, these characteristics are comparable to those of the sensorimotor or interpersonal schemas in terms of the way the schema develops, that the schema exists for each target of output, and that it is modified depending on context. This idea is congruent with the known general roles of the neural correlates of this schema: the vMPFC (as well as the ACC and mOFC) represents values (Rangel et al., 2008;Rushworth et al., 2011), and the PCC (and precuneus) processes the different aspects of social or autobiographical contexts (Addis et al., 2004; Gilboa et al., 2004; Chiao et al., 2009) and different types of perspectives (Vollm et al., 2006; Mano et al., 2009).

Neuroimaging findings relevant to the social-value of the self are likely explained by either top-down or bottom-up attention related to the social-value schema. The activation of the vMPFC and PCC during self-trait judgment (Craik et al., 1999;Kelley et al., 2002; Schmitz et al., 2004; Heatherton et al., 2006; D'Argembeau et al., 2007), perception of self-descriptive trait adjectives (Kircher et al., 2002; Macrae et al., 2004; Moran et al., 2006), and perception of self-evaluation by others (Izuma et al., 2008; Somerville et al., 2010) may reflect top-down attention to the social-value schema. Activation of these regions in terms of bottom-up attention in response to unexpected evaluations of one's behavior was found in a study using monetary rewards for a simple estimation game involving a pair of players. These regions exhibited greater activation when the payment to the two players was unequal for the same correct performance (i.e., prediction error in evaluation) than when it was equal (Fliessbach et al., 2007).

The functioning of the social-value schema is also not specific to self-evaluation but operates for any cognitive operation related to social-value. The schema may be used as an inverse model to calculate the behavioral plan for obtaining an intended social evaluation (**Figure 4C**). The activation of the vMPFC and PCC during moral judgment is greater when the situation is more realistic (i.e., relevant to the real-life evaluation of self), such as when the decision is situation-based rather than rule-based (Robertson et al., 2007) or when the potential victim of the decision is humanized by mentalizing manipulation (Majdandzic et al., 2012). In daily life, we are intermittently engaged in such behavioral planning on the basis of the social-value of the self, while it is interrupted during execution of a specific attention-demanding task. This appears to be a plausible explanation for the activation of these areas during the conscious resting state (Gusnard et al., 2001; Raichle et al., 2001). Furthermore, the simulation capacity of the social-value schema (i.e., the making of inferences regarding the intentions and plans related to another's social behavior) may explain the activation of these regions during social-value judgments about others (Craik et al., 1999; Schmitz et al., 2004; Sugiura et al., 2004; Ochsner et al., 2005; Benoit et al., 2010). Given the general role of the vMPFC and PCC in value-based decision making (Rangel et al., 2008;Rushworth et al., 2011) and their specific roles in highly integrated visuospatial and memory retrieval processes (Wagner et al., 2005; Cavanna and Trimble, 2006), respectively, it seems fair to consider the social-value schema as only a subcomponent of the functioning of this neural system.

#### **MULTI-LAYER STRUCTURE AND CROSS-LAYER DYNAMICS**

It is further proposed that the three categories of self, or internal schemata, comprise a hierarchical layered structure in that the maturation of one layer, or schema, serves as the basis for the development of the next layer. Additionally, the prediction error generated in one layer may result in an updating of the schema not only in that layer but also in adjacent layers. These cross-layer dynamics may be, in part, responsible for both the integrity of the categories and the ambiguity across the three self-concepts.

The self-layers are assumed to develop in the following order: sensorimotor, interpersonal, and social-value. The development of a higher layer is dependent on the maturation of the internal schema in a lower layer; here, the maturation of the schema

denotes the acquisition of the potential to simulate the schema of others.

In terms of the sensorimotor schema, the acquisition of the potential to infer the intention or action goal of others corresponds to an infant's discovery of an "other" or an agent who has a similar mental mechanism to the self. This discovery of an other is the very basis of the development of the interpersonal schema that requires the execution of social action toward the other and the understanding of the other's social response. In fact, a similar concept to this simulation potential has been conceptualized in a recent hierarchical self-model as the Bodily Social Self (BSS), which links Phenomenal Self and Narrative Self (Farmer and Tsakiris, 2012); the former seems to correspond to self-bodydedicated (premature) physical self, and the latter to interpersonal self and social-value of self, together, in the proposed model. This simulation capacity, or the BSS, is included in the physical self in this neural-representation model because both types of self are accommodated by the sensorimotor schema. The maturation process, the acquisition of a simulation capacity by the sensorimotor schema, is assumed to develop in the first 6 months of life in infants (Kaye and Fogel, 1980; Cohn and Tronick, 1988), and its failure to develop has been proposed as responsible for the impaired development of sociality in autism (Gergely, 2001).

The next step of development is triggered by the maturation of the interpersonal schema. The acquisition of a simulation capacity, ToM or mentalizing ability, by the interpersonal schema enables one to conceive of the representation of self in another's mind. The collection of such self-representations in many others' minds allows abstraction of the value of self to construct the socialvalue schema. This internalization process is taken for granted in developmental theories of social self-concepts, with the process, presumably, peaking in adolescence (Cooley, 1902; Mead, 1934; Harter, 1985). Accordingly, self-dominant activation during judgment about significant social attributes is observed in the vMPFC in adults and in the dMPFC in adolescents (Pfeifer et al., 2007). This probably reflects the ongoing self-value abstraction process in the interpersonal schema.

The cross-layer functioning of the error-based updating of the schema adds tremendous complexity to one's self-related experiences as well as to the interpretation of neuroimaging findings. For example, prediction error in the sensory-feedback in response to an action by a subject may produces a sense or belief that the action is performed by another person rather than a feeling of strangeness in one's own action; that is, error-based updates do not influence the sensorimotor schema but the interpersonal schema. Indeed, the experimental manipulation of sensory-feedback during the moving of a hand by a subject or during the manipulation of an agent on a computer monitor activates the TPJ/pSTS and dMPFC (McGuire et al., 1996a; Farrer and Frith, 2002; Farrer et al., 2003, 2008;Hashimoto and Sakai, 2003; Leube et al., 2003; Fu et al., 2006; Spengler et al., 2009; Yomogida et al., 2010), which are implicated in the interpersonal schema. An abnormal functioning of this cross-layer error-attribution (i.e., attribution to other) is considered to explain several symptoms of schizophrenia, including the delusion of control (Frith et al., 2000; Frith, 2005).

Another example is the case in which prediction error in the self-value layer influences the interpersonal schema. Unexpectedly high or low evaluation of the self by another is assumed to cause change in self-value but, alternatively, may be attributed to an idiosyncratic viewpoint or attitude of the evaluator (interpersonal schema). One example may be a case in which one thinks "his recognizing me as stupid is not because I am stupid, but because he is stupid." In the experimental setting, feedback evaluation toward the self is typically provided by a small number of alleged evaluators, and it is highly likely that cross-layer attribution does occur. This consideration is congruent with data identifying neural responses that are positively correlated with self-value prediction error (i.e., discrepancy between a subject's own evaluation of the self and the evaluation by others) in the major components of the interpersonal schema (Korn et al., 2012).

The implementation of hierarchical layer structure and crosslayers error-attribution, in addition to the association-based generation of the internal schema and its prediction-error-based update *per se*, makes this model conform to the Hierarchical Bayesian model based on the free-energy principle (Friston, 2010). This conformity may suggest a future potential sophistication of this model in the Bayesian framework. The proposed model may, therefore, provide an example of successful adoption of this comprehensive framework to cognitive processes that cover perception to higher-level cognition accompanying empirical data.

Several cortical areas may play a unique role in the coordination of functioning across multiple layers. Specifically, the right lateral prefrontal cortex may have a role in resolving conflicts in different layers. This region is activated during sensory-feedback manipulation when it obviously conflicts with motor control (Fink et al., 1999) or when agency-attribution judgment (i.e., self or other) is required (David et al., 2007; Schnell et al., 2007; Farrer et al., 2008). It has been proposed that this region is responsible for an impaired belief-validation process during the mirrored-self misidentification (mirror sign) due to a failure to resolve the conflict between self-face recognition and contingency detection when either process is abnormal (Coltheart, 2007, 2010). Apparently consistent with this view, activation in the right lateral prefrontal cortex is frequently reported during the recognition of self-face or self-body in non-contingent images (Platek et al., 2004, 2006; Sugiura et al., 2005a, 2006, 2008, 2012; Uddin et al., 2005; Devue et al., 2007; Kaplan et al., 2008). Moreover, this region responds to behavior that violates social norms (i.e., error in the interpersonal layer) (Wakusawa et al., 2009) or when there are discrepancies between a subject's self-evaluation and the evaluation by others (i.e., error in the social-value layer) (Korn et al., 2012).

In summary, the concept of an internal schema with three layers operating under the assumption of cross-layer dynamics provides a relatively simple integrated conceptual framework for the selfconcept. In this framework, associative learning and the hierarchical structure of the cortical network appear sufficient to explain the wide range of behavioral, developmental, and neuroimaging findings related to self-cognition.

#### **ROLE OF MIDLINE STRUCTURES**

In the proposed model, a majority of the association cortices in both lateral and medial structures critically contribute to some aspect of self. This view may be inconsistent with the notion of a special role for the midline regions in self-cognition, which might be implied by this topic. Based on the size of areas included, however, it is possible to characterize the contribution of the midline regions in the following manner: they are most relevant to the social-value layer, less relevant to the interpersonal layer, and least relevant to the sensorimotor layer. This characterization is largely congruent with the view that has previously been discussed (Uddin et al., 2007).

Within the proposed conceptual framework, the primary interest regarding midline structures concerns the functional demarcation of the neural correlates of each schema. The border of the cortical correlates for each self-layer parallels the functional segregation of the midline structures.

In the frontal lobe, the border between the cortical correlates of the sensorimotor and interpersonal schema may be reasonably defined as the border between the premotor cortex (Brodmann area 6) and the posterior part of the prefrontal cortex (Brodmann area 8) given the motor-associated and amodal nature of these schemata, respectively. A review of neuroimaging findings evaluating the dorsal part of the medial frontal lobe suggests that the border is a few centimeters rostral to the vertical plane crossing through the anterior commissure (AC). Clusters of activation peaks related to attention to action or to sensation are located posteriorly, and those related to concepts are located anteriorly (Seitz et al., 2006). The location of this functional border appears largely congruent with the cytoarchitectonic border between area 6 and area 8 (Geyer, 2004). The border between the regions for the interpersonal and social-value schema, on the other hand, has been defined only functionally. Previous reviews have consistently demonstrated a functional inhomogeneity of the MPFC as the dorsal and ventral regions tend to be involved in cognitive and emotional processes, respectively. However, the proposed level of a horizontal plane for that border has varied across studies (i.e., from running through the AC to 20 mm above the AC) (Amodio and Frith, 2006; Van Overwalle, 2009).

In the medial parietal lobe, the extent of the cortical correlates of the social-value schema remains inconclusive but may encompass the entire precuneus and PCC. This region contains multiple functional subareas that are specialized for the processing of particular components of the implicated roles in this region, such as episodic-memory retrieval, visual imagery, and the representation of a personally familiar place (Sugiura et al., 2005b; Wagner et al., 2005; Cavanna and Trimble, 2006; Summerfield et al., 2009; Zhang and Li, 2012). Although all of these processes appear to be relevant in some way to the processing of contextual roles, a detailed account of the association of these processes with respect to the concept of the social-value schema is extremely premature.

# **CONCLUSION**

The framework proposed herein is an attempt to rescue the integrated construct of self from the pessimistic view arguing against the existence of self-specific neural system. The concepts of self appear to be parsimoniously arranged into three categories according to the contexts of awareness and development as well as the implicated cortical regions. According to the proposed model, the internal schema, which represents the learned associations between behavioral output and feedback input, enables the system to engage in forward prediction and explains the sense of

self in all three categories. Importantly, the internal schema is not exclusively dedicated to self-cognition but is the very basis of the cognitive system underpinning interaction with a physical or social environment. Additionally, the schemata for these three categories of self comprise a hierarchical layer structure in terms of their developmental and updating processes.

The sensorimotor schema, namely, the association of a motor plan with feedback sensory input acquired through exploratory motor activity, is supported by sensory and motor association cortices and results in a sense of a physical self representing selfagency of action, body-ownership, and bodily self-recognition. As the schema matures, it becomes capable of simulating the intention or action goals of others. This allows one to explore and experience social interaction in which the interpersonal schema, or the association of one's own social action with subsequent social responses that serve as feedback, is developed in the amodal association cortices of the dMPFC and lateral posterior cortices (e.g., pSTS/TPJ and ATC). While allowing for the experience of the interpersonal self, which is the awareness of self-directed attention or the intention of others, the interpersonal schema also matures to accommodate the representation of the self in another's mind. The collection of such self-representations in many others' minds enables the development of the social-value schema, which evaluates one's social

## **REFERENCES**


behavior and feedback evaluation. This schema, supported by the vMPFC and PCC, enables the operation of the social self and represents the self as a collection of context-dependent social-values.

The model proposed herein explains the large variety of activated regions that have been reported by studies addressing selfrelated cognitive processes as well as their involvement in nonself-related processes. It also provides a unique perspective on the relationship between self-cognition and the cognitive system involved in one's interaction with the physical or social environment. In particular, the assumed layer structure provides for the development, complexity, and integrity of three categories of the self. This view understands the different, but not mutually exclusive, roles of the midline and lateral cortical regions in selfcognition in terms of the different medial–lateral distribution of the three internal schemas. With respect to midline structures, due to the different sizes of the areas that each internal schema occupies, the characteristics of the self may be ranked as follows in term of prominence: social-value self, interpersonal self, and physical self.

# **ACKNOWLEDGMENTS**

The preparation of this manuscript was supported in part by KAKENHI (25560347) from MEXT.


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**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 04 June 2013; paper pending published: 03 July 2013; accepted: 16 August 2013; published online: 30 August 2013.*

*Citation: Sugiura M (2013) Associative account of self-cognition: extended forward model and multi-layer structure. Front. Hum. Neurosci. 7:535. doi: 10.3389/fnhum.2013.00535*

*This article was submitted to the journal Frontiers in Human Neuroscience.*

*Copyright © 2013 Sugiura. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# A pattern theory of self

# **Shaun Gallagher 1,2\***

<sup>1</sup> Department of Philosophy, University of Memphis, Memphis, TN, USA

<sup>2</sup> School of Humanities, University of Hertfordshire, Hatfield, Hertfordshire, UK

#### **Edited by:**

Niall W. Duncan, University of Ottawa, Canada

#### **Reviewed by:**

Niall W. Duncan, University of Ottawa, Canada Michela Summa, Klinik für allgemeine Psychiatrie, Germany

#### **\*Correspondence:**

Shaun Gallagher, Department of Philosophy, University of Memphis, Clement Hall 331, Memphis, TN 38156, USA e-mail: s.gallagher@memphis.edu

I argue for a pattern theory of self as a useful way to organize an interdisciplinary approach to discussions of what constitutes a self. According to the pattern theory, a self is constituted by a number of characteristic features or aspects that may include minimal embodied, minimal experiential, affective, intersubjective, psychological/cognitive, narrative, extended, and situated aspects. A pattern theory of self helps to clarify various interpretations of self as compatible or commensurable instead of thinking them in opposition, and it helps to show how various aspects of self may be related across certain dimensions. I also suggest that a pattern theory of self can help to adjudicate (or at least map the differences) between the idea that the self correlates to self-referential processing in the cortical midline structures of the brain and other narrower or wider conceptions of self.

**Keywords: self, pattern theory, cortical midline structures, first-person perspective**

# **INTRODUCTION: VARIATIONS ON THE SELF**

From a philosophical perspective, any claim to explain something called "the self" immediately raises a host of problems. On the one hand, although many philosophers are perfectly comfortable talking about "the self," what they have to say about this concept usually turns out to be controversial. For example, that the self is socially constructed (Gergen, 2011) or a product of narrative (Schechtman, 2011), and nothing more; that the self is strictly minimal, on the order of 3 s in duration, and nothing more (Strawson, 1999a); that the self as such doesn't exist at all, plus a lot more about a replacement concept called a "self model" (Metzinger, 2003). Such deflationary and reductionist accounts tend to be reactions against something like a traditional Cartesian notion of the self as a substantial (soul-like) entity, and some of them can be understood as variously inspired by Humean, Buddhist, or neuroscientific perspectives.

On the other hand, and pursuing a different strategy, some philosophers prefer to avoid the phrase "the self" by pluralizing it with important modifiers between "the" and "self." Thus we find a multitude of variations, once cataloged, with references, by Strawson (1999b) as follows:

[T]he cognitive self, the conceptual self, the contextualized self, the core self, the dialogic self, the ecological self, the embodied self, the emergent self, the empirical self, the existential self, the extended self, the fictional self, the full-grown self, the interpersonal self, the material self, the narrative self, the philosophical self, the physical self, the private self, the representational self, the rock bottom essential self, the semiotic self, the social self, the transparent self, and the verbal self (cf. e.g., James, 1890; Stern, 1985; Dennett, 1991; Gibson, 1993; Neisser, 1994; Cole, 1997; Butterworth, 1998; Gazzaniga, 1998; Legerstee, 1998; Gallagher and Marcel, 1999; Pickering, 1999; Sheets-Johnstone, 1999).

Trying to improve on this list would likely lead to nitpicking about terms, but we may want to add "the neural self,""the synaptic self"

(LeDoux, 2002); or what we might call "the midline self" [in reference to self-referential processes in the cortical midline structures (CMS) (Northoff and Bermpohl, 2004)]. The list of variations is likely not complete. Someone might think that the question is: "Which is it?" – which one is *the* self? Or perhaps, which one is the primary meaning of self? It's not clear, however, that one has to choose just one variation. Many of these concepts of self were developed in the plural. James (1890), for example, distinguished between the physical self, the social self, and the private self. Neisser (1988) discussed five types of self-knowledge corresponding to the ecological self, the interpersonal self, the conceptual self, the extended self, and the private self. Despite the terminology suggesting a plurality of selves, however,Neisser (1991) carefully refers to them as aspects of self – e.g., the ecological aspect of self.

In this paper I propose to stay plural about the concept of self, and to follow Neisser's more careful vocabulary referencing different aspects of self. In this regard, however, I want to argue that we should not think of such aspects as aspects *of* "the self," as if they are simply modifying something that has its own independent existence. Rather, I propose that we think of these aspects as organized in certain patterns, and that a particular variation of such a pattern constitutes what we call a self. In the following sections I'll try to make this idea clear, and I'll try to indicate some advantages of thinking of self in this way.

In part, this approach is motivated by various issues that relate to the theory of self as involving CMS and self-referential processing, as developed by Northoff and others (Northoff and Bermpohl, 2004; Northoff et al., 2006). Some critical studies, for example, have suggested that in terms of brain processes, the self is both everywhere and nowhere in the brain (Gillihan and Farah, 2005; Vogeley and Gallagher, 2011). Others challenge the idea that the self correlates to CMS processing, and argue that such processes are not self-specific because activation in these areas also corresponds to non-self discrimination (Legrand and Ruby, 2009). Although I think some of these criticisms raise important points, I argue here that midline processes do tell us something important about the

notion of self and may correlate with specific aspects that are part of the pattern that we call self.

# **PATTERN THEORIES**

Let me first say that in talking about pattern theories I do not mean to associate a pattern theory of self with "Pattern Theory" in mathematics (Grenanderm, 1994). This kind of mathematical formalism may or may not be a helpful tool for the analysis of the specific patterns that I will discuss. I remain neutral on that point. In any case, one can understand the notion of pattern at stake here without having to understand Pattern Theory in this sense. Furthermore, although there are numerous theories that are referred to as "pattern theories," e.g., pattern theory of pain (Goldscheider, 1894; Sinclair, 1955), dynamic pattern theory of motor control (Kelso, 1995), etc. these theories don't necessarily share the same general principles, and at the most general level the concepts of pattern represented in the different theories may be incommensurable with each other. Accordingly, since, for purposes of economy I want to avoid starting from scratch in developing a pattern theory of self, I will follow a strategy that allows me to point to an already established theory, one that can operate as a heuristic model for our purposes – i.e., one in which the concept of pattern is used in a way that is not incommensurable with what I take to be the pattern theory of self. Although we could think of psychological discussions of pattern recognition as a kindred notion, more specifically I suggest that we consider what I'll call a pattern theory of emotion to be a good model for a pattern theory of self. There are two reasons why a pattern theory of emotion may be a good model in this regard: (1) it reflects a commensurable concept of pattern (i.e., it refers to the same kind of pattern that I think is relevant to the notion of self, and (2) it may contribute directly to a pattern theory of self since, as I'll suggest, affect is one aspect that forms part of the pattern of self.

The pattern theory of emotion claims that emotions are complex patterns of bodily processes, experiences, expressions, behaviors and actions, and as such they are "individuated in patterns of characteristic features" (Izard, 1972; Izard et al., 2000; Mendoça, 2012; Newen et al., under review). On a pattern theory, "emotion" is a cluster concept that includes a sufficient number of characteristic features. Taken together, a certain pattern of characteristic features constitutes an emotion, although no individual feature by itself may be necessary to constitute an emotion. This means, as Newen et al. (under review) point out, there are borderline cases where it is not clear whether some complex cluster of aspects counts as an emotion.

Izard et al. (2000) develop this idea under the title of differential emotions theory (DET), maintaining that emotions operate as complex systems that emerge from dynamic interactions of constituent neuro-hormonal, motoric, and experiential processes (Izard, 1972). Emotion patterns draw from components that are set up as evolutionary adaptations. In the emergence of any particular emotion, however, organism-environment transactions play a role. Individual emotions may also combine or co-assemble with other emotions to form new emotion patterns that may stabilize over repeating occurrences. On this view, discrete emotions are dynamically self-organizing in that "recursive interactions among component processes generate emergent properties" (Izard et al., 2000, p. 15). Different emotions are constituted by different patterns of processes that yield behavioral performances that vary from one individual to another, and within individuals over time. Importantly, such behaviors should not be regarded simply as an expression of an emotion, but rather are part (an emerging feature) of the pattern that constitutes the emotion.

Newen et al. (under review) provide a catalog of different features that may contribute to specific patterns that constitute emotions. They include:


I would add to this list:

(7) Situational aspects: following Dewey, who, in his critique of James, points out that emotions are not reducible to a set of bodily states, but also, since the body is always coupled to an environment, always include situational aspects. The unit of analysis should always be organism-environment. Situational aspects, and the fact that emotional experiences and behaviors are always situated, are part of the pattern (Mendoça, 2012, 2013). In this regard it is not just the intentional object, but also the situation reflected in the intentional structure of the emotion, that helps to disambiguate emotional expressions. Importantly, situations are almost always social and/or cultural and such factors contribute constitutively to what an emotion is.

Such aspects are variables that can take different values and weights in the dynamic constitution of an emotion. Some values are more or less likely to occur together. In this respect we can distinguish typical patterns of aspects and values and define an emotion as involving some variation of that pattern. Newen et al. are careful to note that to say a particular feature is constitutive of an emotion does not mean that it is an essential component. On the pattern theory of emotion such features are not constitutive in the essentialist sense. One can have a token of the same type of emotion lacking a particular characteristic feature, although there may be some minimal number of characteristic features and their values that are sufficient to constitute a particular pattern that counts as that emotion.

A feature f is constitutive for a pattern X if it is part of at least one set of features which is minimally sufficient for a token to belong to a type X. "Minimally sufficient"means that these features are jointly sufficient for the episode to be of type X, but if one of them would be taken away the episode would not count as a instance of type X anymore (Newen et al., under review).

It is possible, of course, to include other aspects or characteristics in the list above. One may want to include more than just autonomic processes under a broad heading of embodied processes,for example. One may want to list certain brain patterns as part of an emotion pattern. I think, however, that the list provides sufficient detail to indicate the kind of pattern theory that we want to consider. Let me just note that one of the advantages of this theory of emotion is that it becomes very easy to say that we can perceive emotions in others. If emotions are constituted by features that may include bodily expressions, behaviors, action expressions, etc., then emotion perception can be considered a form of pattern recognition (Newen et al., under review; Gallagher and Varga, in press).

# **A PATTERN THEORY OF SELF**

In a way similar to the construction of a pattern theory of emotion, I want to suggest that we can develop a pattern theory of self. On such a view, what we call self consists of a complex and sufficient pattern of certain contributories, none of which on their own is necessary or essential to any particular self. This is not a pattern theory of "*the* self." Rather, what we call "self" is a cluster concept which includes a sufficient number of characteristic features. Taken together, a certain pattern of characteristic features constitute an individual self. It seems possible that this would allow us to identify borderline cases where it is not clear whether some complex cluster of aspects would count as a self – here one might think of Dissociative Identity Disorder and the idea that there may be

more than one self involved in such cases. On this view selves operate as complex systems that emerge from dynamic interactions of constituent aspects. It may also be the case that self-patterns draw from components that, like the components of emotion, are set up as evolutionary adaptations. Indeed, emotion-related aspects may contribute to the constitution of a self<sup>1</sup> . Different selves are constituted by different patterns, but within one individual these patterns may change over time.

One important issue concerns the level of analysis at which we put the pattern theory of self to work. There are three possible levels to think about. First, one can think of the pattern theory of self as operating like a meta-theory that defines a schema of possible theories of self, each of which would itself be a pattern theory. For example, the meta-theory can claim that elements *a* through *g* are all possible aspects that can be included in any particular pattern theory of self. Such a meta-theory would aim to provide a complete list of such elements and to map out all possible pattern theories of self. Accordingly, at this level there would be no claims made about necessary or sufficient conditions for constituting a self. Second, however, any particular theory of self can be a pattern theory, and one pattern theory can differ from another pattern theory by specifying different aspects (from among *a* through *g* ) to be included as aspects of self. In this respect, one can think of a pattern theory of self as defining the self at the level of a type, and at this level the theory might specify necessary or sufficient conditions, indicating, for example, that *a* and *b* are necessary but not sufficient for selfhood. Finally, however, one can think that in any particular instance, at the level of a particular token, a pattern theory of self can apply to an individual self. A particular self may manifest or include a pattern of only aspects *a* through *d* and be considered a self even if all aspects defined by the relevant pattern theory of self are not included. The analysis in this paper remains on the meta-theoretical level unless otherwise noted.

What features can contribute to specific patterns that constitute a self? To philosophers it will come as no surprise that what gets included in this list is open to contentious debate. Keep in mind, however, that, remaining at the level of meta-theory, we are not talking about necessary conditions. A particular theory of self may exclude some of these conditions, and a particular self may lack a particular characteristic feature as defined here and still be considered a self. Here is a tentative list. I do not claim that it is complete. Under each heading I offer some un-systematic notes to indicate the scope of each aspect (or set of aspects).


<sup>1</sup> In this respect we may start to think of the self as a meta-pattern of various constituent patterns or sets of patterns.

a first-person perspective, the self/non-self distinction in the various sensory-motor modalities available to it (e.g., kinesthesia, proprioception, touch, vision). Such aspects contribute to an experiential and embodied sense of ownership (the "mineness" of one's experience, as well as of one's body and movement), and a sense of agency for one's actions (Gallagher, 2000, 2012a; Rochat, 2011).


family structure and environment where we grew up; cultural and normative practices that define our way of living, and so on (see Gergen, 2011).

Such aspects are variables that can take different values and weights in the dynamic constitution of a self. This pattern theory of self will not solve all philosophical problems of course. One may want to know which of these aspects are necessary or essential, and this might be specified by a particular pattern theory of self. As such theories get applied to individuals, for example, it seems possible that one may experience life in a less continuous or coherent way than others do, thereby minimizing the narrative aspect, without minimizing the sense of self or self-identity (Strawson, 2004). One may also lose a sense of agency, as in some schizophrenic symptoms, without losing a sense of ownership or other aspects that define a self (Gallagher, 2005). One might lose the ability to recall one's past life, as in some cases of amnesia and Alzheimer's disease, and may also undergo character or personality change; in such cases one's self-identity may continue to be supported by one's minimal bodily and experiential aspects, as well as by intersubjective relations and/or extended aspects in one's surroundings. This is not to say that such changes do not result in a modulation of selfexperience or self-identity, but rather, since self is not reducible to any one of these aspects, it is a modulation rather than a complete loss. There may be various states of existence or pathologies associated with each of these aspects such that the aspect in question is eliminated or seriously modified.

On the one hand, we can think of a particular pattern theory of self where no one feature is constitutive in an essentialist sense. If someone lacks memory or a sense of agency, or perhaps lacks both, she continues as a self if there are a sufficient number of aspects still intact. On the other hand, we can think of a different particular pattern theory of self where certain aspects are defined as necessary. Beyond such differences, there are still a number of questions outstanding for any particular pattern theory of self. Is there some minimal number of aspects, or some specific combinations of aspects sufficient to constitute a particular pattern that counts as self? Is there a hierarchical relation among these aspects? For example, if someone lacked certain minimal experiential aspects, would their lives still reflect a narrative structure? Different answers to these questions define different variations of a pattern theory of self. It would be difficult to talk of a pattern, or a self, however, if only one aspect is claimed as necessary and sufficient for selfhood. Indeed, if that were the claim, the "aspect" would no longer be an aspect (of a self, or of a pattern); it would *be* the self. The pattern theory of self rules out this kind of reduction, *a priori*, although it does not rule out various answers to the questions mentioned above. At the level of the meta-theory one can also ask: how many different patterns are viable?

# **SOME BENEFITS OF A PATTERN THEORY OF SELF AND ITS RELEVANCE TO CMS PROCESSES**

One benefit of the pattern theory of self is that we can more clearly understand various interpretations of self as compatible or commensurable instead of thinking them in opposition. For example, different definitions of personhood can be accommodated or can be viewed as different interpretations that place different weights

on some aspects rather than others. If with Locke we define person to mean "a thinking intelligent being, that has reason and reflection, and can consider itself as itself, the same thinking thing, in different times and places; which it does only by that consciousness with is inseparable from thinking, and, as it seems to me, essential to it . . ." (Locke, 1690/1979, 318), then we can see clearly that this notion of person focuses on psychological aspects of self and ignores other aspects. Other definitions of personhood may emphasize bodily continuity, the importance of social role or legal standing. Differences in definitions of personhood, however, do not necessarily imply differences in definition of self. We may disagree about where to lay the emphasis in defining personhood, but continue to agree that a self is composed of some pattern of aspects, some of which are relevant to the notion of personhood, and others which are not. When we focus on or emphasize a certain pattern or organization of aspects from a certain vantage point (an interpretation which may be tied to social roles, or to causal, legal or moral responsibility, to or certain cultural practices, etc.), we can easily understand self to accommodate different concepts of person, or moral agent, or experiential subject, or physical individual, or mental entity, etc. The pattern theory of self, at the meta-level, remains neutral with respect to these interpretations, and in some respects defines the field of reference or common ground on which such debates about personhood or moral agency or other interpretations of self can take place.

Another advantage is that the pattern theory helps us to see that the various aspects of self may be related in important ways. Many of the particular elements included in the various aspects are themselves complex features of existence that may not be conceptually bound to just one aspect. Thus, for example, the sense of agency in some basic way may be tied to motor control and the sensory-motor operations of the body, but it is also related to social and cultural norms and expectations (which may place limitations on agency) and to psychological/cognitive processes of deliberation and decision-making (Gallagher, 2012a). Something like the sense of agency is interwoven into several aspects of self. To the extent that something like this applies to other elements, then it will be difficult to make the case that there is one and only one aspect that defines self in all cases.

It is in this respect that the pattern theory of self may help to make sense out of some of the controversies surrounding the notion that self is related to cortical midline regions. One claim made in connection with what I'll call the midline theory of self (or for short, the midline self) is that there is a common element that unites different aspects of self, an integrative glue that holds the pattern together, and that this common element is a processing of stimuli as self-referential (Northoff et al., 2006). The notion of self-referential is then defined in terms of pre-reflective experience, which is found across a diversity of contexts, "autobiographical, social, spatial," and various others. It is also noted that in any particular case pre-reflective self-referential experience has an affective or emotional dimension. In these regards the notion of self-referential experience includes a number of aspects that can be accommodated by the pattern theory of self. One problem that arises, however, is that pre-reflective experience is extremely difficult to operationalize in experimental settings. Thus Northoff et al. (2006) in discussing experimental data shift the focus to processes that involve reflection or judgment, such as a trait adjective judgment task. For example, in a study by Kelley et al. (2002) subjects are asked to judge whether trait adjectives (e.g.,"polite") more closely described "the participants themselves (self-referential), the current U.S. President (other-referential), or a given case (case-referential)" (Northoff et al., 2006, p. 441). Such experiments activate a variety of brain areas – medial cortex, ventro-, and dorsolateral prefrontal cortex, lateral parietal cortex, bilateral temporal poles, insula, and subcortical regions, including brain stem, colliculi, periaqueductal gray (PAG), and hypothalamus/hypophysis (Northoff et al., 2006, p. 441). Northoff argues that based on a review of recent brain-imaging studies, there are certain core areas commonly activated for self-referential behavior, the so-called CMS. The studies reviewed, however, included only those comparing self- and non-self-related tasks – that is, tasks where subjects had to discriminate between self and non-self – a point that motivated the critique by Legrand and Ruby.

Legrand and Ruby (2009) suggested that there are cognitive processes common to all of the tasks involved in the Northoff et al. review, namely a reflective process of differentiating self and non-self and often involving non-domain specific inferential processing and memory recall. This means that the activated CMS are not dedicated exclusively to self since processes related to non-self, and often to other persons are involved. Indeed, Legrand and Ruby demonstrate "that the main brain regions recruited for others' mind representation are also and precisely the main brain regions reported in self studies and that this overlap extends beyond the brain areas usually pointed out . . ." (p. 254). The self-referential processes at stake in these studies are not self-specific in the technical sense proposed by Legrand and Ruby as being (1) exclusively about self (and not about non-self) and (2) non-contingently (i.e., necessary for the process to be) about self. They suggest that only one thing actually meets the self-specificity requirements: the first-person perspectival nature of experience. First-person perspective is exclusively self-related (since it does not apply to the non-self) and non-contingent (since changing or losing the firstperson perspective amounts to changing or losing the self–non-self distinction).

On the one hand, Legrand and Ruby want to specify one necessary condition of selfhood; on the other hand, this does not rule out that there are other relevant aspects of self that are important: "We do not claim that all there is to the self can be subsumed under a single process but propose that both basic and complex forms of self have to rely at least partly on self-specific processes . . ." (2009, p. 279). Whether or not first-person perspective is a necessary condition of selfhood (see, Gallagher, 2012b for a positive answer in agreement with Legrand and Ruby), the disclaimer about subsuming self under a single process is important.

The important move here is to admit that there are multiple processes that may count as self-related, even if not self-specific, and that they can be constitutive of self over and above first-person perspective. That sends us back to a pluralist approach, and it also opens up a theoretical space for the idea that processes associated with CMS, among other aspects, are relevant to what we call self. Indeed, Northoff et al. (2006) (also Northoff et al., 2011; Qin and Northoff, 2011) point to multiple processes that contribute to different aspects of self. These are processes in the verbal domain (as

in trait adjective judgment tasks), spatial domain (egocentric vs. allocentric); memory domain (in relation to self-referential information); emotional domain (self-related vs. non-self-related); facial recognition domain (self vs. non-self); social domain (where, according to Northoff et al.'s simulation theory approach, understanding of others depends on self-simulations); and domains that involve agency and ownership. All of these domains have a place within the pattern theory of self. Processes that pertain to memory and face recognition are clearly part of what we referred to as psychological/cognitive aspects. Those that pertain to language (verbal domain) may also be cognitive or may include narrative aspects. Processes pertaining to the emotional domain belong to affective aspects; those that pertain to spatial domain are closely related to first-person perspective, but nicely fit with minimal embodied aspects, while those that pertain to agency and ownership are part of the minimal experiential aspects. Social domain processes are clearly part of the intersubjective aspects. More generally, given that all of these processes reflect a self/non-self matrix, they demonstrate how the minimal embodied aspect of self/nonself differentiation is interwoven into the various other aspects of self. It has also been suggested, however, that minimal experiential aspects of self, connected with basic self-awareness, are interwoven with all other aspects of self, and moreover, that this minimal self-referential awareness survives damage to critical areas in the CMS (Philippi et al., 2012).

Accordingly, the concept of a midline self points to a specific pattern that includes a significant set of interconnected aspects, but not all of the aspects identified in the previous section. The midline

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theory of self is one particular pattern theory of self. Whether the aspects reflected in self-referential processing in CMS constitute "the core of our self," as Northoff et al. claim, is of course open to debate. One could go more minimal and claim that the core is, as Legrand and Ruby suggest, a very minimal embodied aspect, or go wider to include aspects that may go beyond CMS related processes, such as extended and situated aspects, or very basic aspects of self-awareness that survive damage to CMS areas (Philippi et al., 2012).

That extended and situated aspects, as well as other aspects included in a pattern theory of self, may enter into a definition of self also suggests an important proviso on the type of approach taken by researchers who are looking specifically at neural processes that reflect these different self-referential behaviors. The patterns at stake in a pattern theory of self are not reducible to neuronal patterns, or patterns of brain activation. This is the case not only for extended and situated aspects, but also for aspects that relate to one's body, emotional, and intersubjective life, cognitive and narrative dimensions, and so forth. In each case more factors than just brain processes are involved. Although we can expect that brain processes will in some way reflect the way a self is constituted across these different factors, who we are, or what self is, is more than the brain. In this respect, and at the very least, the pattern theory of self helps to map out more precisely what the possibilities are for a non-reductionist, non-deflationary theory of self that is also not inflated into a traditional Cartesian theory of the self as a substantial (soul-like) entity.


**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 11 May 2013; paper pending published: 14 June 2013; accepted: 18 July 2013; published online: 01 August 2013. Citation: Gallagher S (2013) A pattern theory of self. Front. Hum. Neurosci. 7:443. doi: 10.3389/fnhum.2013.00443 Copyright © 2013 Gallagher. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*