Skip to main content

MINI REVIEW article

Front. Hum. Neurosci., 03 February 2016
Sec. Brain Health and Clinical Neuroscience
Volume 10 - 2016 | https://doi.org/10.3389/fnhum.2016.00020

The Interface between Neuroscience and Neuro-Psychoanalysis: Focus on Brain Connectivity

  • 1Department of Neuroscience, Imaging and Clinical Sciences and Institute for Advanced Biomedical Technologies—ITAB, University G. d’Annunzio, Chieti-Pescara, Italy
  • 2Institute of Psychiatry, University G. d’Annunzio, Chieti-Pescara, Italy
  • 3Dynamic and Clinical Psychology, Sapienza University of Rome, Rome, Italy
  • 4National Health Service (NHS), Department of Mental Health, Psychiatric Service of Diagnosis and Treatment, Hospital “G. Mazzini”, Teramo, Italy
  • 5Department of Neuroscience, Reproductive Sciences and Odontostomatology, Federico II University of Naples, Naples, Italy
  • 6New York State Psychiatric Institute (NYSPI), Columbia University, New York, NY, USA
  • 7Department of Neuroscience, Institute of Psychiatry and Clinical Psychology, Catholic University of the Sacred Heart, Rome, Italy

Over the past 20 years, the advent of advanced techniques has significantly enhanced our knowledge on the brain. Yet, our understanding of the physiological and pathological functioning of the mind is still far from being exhaustive. Both the localizationist and the reductionist neuroscientific approaches to psychiatric disorders have proven to be largely unsatisfactory and are outdated. Accruing evidence suggests that psychoanalysis can engage the neurosciences in a productive and mutually enriching dialogue that may further our understanding of psychiatric disorders. In particular, advances in brain connectivity research have provided evidence supporting the convergence of neuroscientific findings and psychoanalysis and helped characterize the circuitry and mechanisms that underlie higher brain functions. In the present paper we discuss how knowledge on brain connectivity can impact neuropsychoanalysis, with a particular focus on schizophrenia. Brain connectivity studies in schizophrenic patients indicate complex alterations in brain functioning and circuitry, with particular emphasis on the role of cortical midline structures (CMS) and the default mode network (DMN). These networks seem to represent neural correlates of psychodynamic concepts central to the understanding of schizophrenia and of core psychopathological alterations of this disorder (i.e., ego disturbances and impaired primary process thinking).

Introduction

Current etiological models of mental disorders are complex and multifactorial. The dichotomy between biological and psychological interpretations is outdated. The advent of non-invasive techniques to explore brain functioning has renewed interest in the interplay between biological and psychological factors, originally put forward in Freud’s (1895) “Project for a Scientific Psychology” but dismissed due to lack of sufficient scientific evidence (Panksepp, 1998; Solms and Solms-Kaplan, 2000; Solms and Turnbull, 2002; Fonagy, 2003; Schore, 2003; Solms, 2004; Mancia, 2006b).

Neuroscientific research has recently moved away from the traditional field of cognitive sciences (language, memory, attention, perception, etc.) towards the study of mental disorders, in order to investigate possible modifications in neural patterns related to clinical improvements following psychotherapeutic interventions (Kandel, 1998; Demertzi et al., 2009; Cozolino, 2010; Toyokawa et al., 2011).

Kandel (1989) was the first to highlight that learning processes can permanently modify and reinforce synaptic connections. He later focused on gene-environment interaction research and theorized a novel biological approach to psychiatry and psychotherapy, in which the latter is conceived as a learning process that can, therefore, determine changes in genes and modify the strength of synaptic connections (Kandel, 1999, 2005). Several subsequent studies have demonstrated that successful talk-based interventions may lead to significant brain changes (Beauregard, 2007). More recently, a number of studies investigated brain activation during cognitive or perceptual tasks, with the aim of identifying neural correlates of various psychopathological conditions (McGuire et al., 1994; Viinamaki et al., 1998; Dierks et al., 1999; Furmark et al., 2002; Paquette et al., 2003; Rauch, 2003; Linden, 2006; Karlsonn, 2011; Leichsenring and Rabung, 2011). The use of sophisticated neuroimaging techniques in these studies has led to a shift in the conceptualization of mental disorders, removing the emphasis on the alterations of specific brain areas and highlighting alterations in their interactions within larger neural networks.

Brain connectivity studies thus appear to be particularly promising in elucidating the complex architecture of structural and functional brain networks underlying psychological functions. Though psychiatric diagnostic categories are essentially objective and symptom-based, subjective elements (i.e., the patient’s perception of his own self and of others) are essential to a comprehensive study of mental disorders. Panksepp and Solms (2012) underscored how neuropsychoanalysis has drawn attention to the first-person experience in the neuroscientific approach to the mind, thus improving our understanding of the emotional subjective level in psychiatric disorders and promoting more patient-tailored interventions. Neuropsychoanalysis has focused on linking psychodynamic concepts to specific neuronal mechanisms. Among others, memory (Kandel, 1998; Mancia, 2004, 2006a,b), dreams (Solms, 1997, 2000; Solms and Turnbull, 2002; Mancia, 2004; Hobson, 2009; Northoff, 2011), affect (Panksepp, 1998), defense mechanisms (Fonagy, 2003; Northoff and Boeker, 2006; Feinberg, 2011; Northoff, 2011), the Self and Ego functions have been singled out as major areas of interest. Brain connectivity research has provided evidence supporting the notion that the study of the Self and Ego functions is particularly relevant to the understanding of schizophrenia; in the present paper we will, therefore, focus primarily on these two areas.

The Neuroscience-Psychoanalysis Interface

The interconnection between psychoanalysis and neuroscience goes beyond evidence of efficacy alone. Psychoanalytic theories represent an important conceptual framework for neuroscientific findings and similarly, neuroscience may help provide the neurobiological foundations to psychoanalytic concepts.

Identifying neural correlates of specific psychodynamic mechanisms may help plan psychotherapy and other treatments for psychiatric disorders. Neuropsychoanalysis acknowledges the deep evolutionary roots of the human mind and of emotional disorders, and favors a more coherent understanding of primary-process brain affective networks (Panksepp, 2011). The psychoanalytic perspective on mental functioning can guide neuroscientific research toward a better understanding of basic psychodynamic concepts, such as the Ego, defence mechanisms, dream functions and projection of mental states (Luciani et al., 2014), as well as enhance knowledge in the fields of memory, trauma, attachment, empathy, the self. Specific topics (e.g., neural correlates of emotions and empathy) are nowadays considered important new areas of investigation (Panksepp, 1998; Gallese, 2008; Panksepp and Biven, 2012).

Theoretically, psychoanalysis anticipated the neuroscientific approach postulating the existence of hierarchical systems comprising complex mental functions resulting from interactions between interconnected brain regions. Functional neuroimaging provides a promising avenue for the study of these functional networks, though new experimental studies that consider the psychoanalytic approach to mental functioning are needed. To this end, numerous neuropsychoanalytic studies promoting a dialogue between psychoanalysis and neuroscience and investigating neuroscientific theories that can be enhanced by psychoanalytic metapsychology have been conducted (for a review, see Fotopoulou et al., 2012). In the present article, we focused on two concepts in particular, the “Self” and the “Ego functions and the unconscious”, with the ultimate goal of shedding light on specific aspects of schizophrenia. This choice was largely motivated by the fact that neuroscientific research has provided evidence supporting the notion that the study of the Self and Ego functions is particularly relevant to the understanding of schizophrenia. This implies a clinical endeavor to focus on the subjective experience of symptoms and on how perception of one’s self influences perception of the outside world. From a technical standpoint this also implies investigating the complex functioning of specific brain networks.

Brain Connectivity

Over the last few years, several neuroimaging studies explored brain connectivity. Technically, there are three types of connectivity: (i) anatomical connectivity, defined as patterns of anatomical links between neuronal populations or anatomically defined brain regions; (ii) functional connectivity, defined as patterns of statistical correlations between distinct activated brain areas; and (iii) effective connectivity, defined as causal interactions between specific groups of neurons (Friston, 1994). The relationship between these different types of connectivity is one of the most interesting and innovative fields of experimental neuroscience. This inevitably raises the following question: “how does brain connectivity research contribute to neuropsychoanalysis?”

This new perspective provokes worthwhile questions and debate and may help further our understanding of complex mental phenomena such as consciousness, the influences of different contexts on meaning attribution, the representation of the self and of others (Molnar-Szakacs and Uddin, 2013; Ionta et al., 2014; Li et al., 2014; Rudorf and Hare, 2014; Touskova and Bob, 2015). Recent reviews (van Veluw and Chance, 2014; Murray et al., 2014) evidenced that different connectivity patterns are involved in self-representation and in the representation of others: in 193 studies healthy subjects were administered self-related tasks (Molnar-Szakacs and Uddin, 2013), while in 106 studies others-related tasks were used (Li et al., 2014). Meta-analytic connectivity modeling (van Veluw and Chance, 2014) showed selective activation of the pregenual anterior cingulate during self-related tasks and selective activation of the posterior cingulate and precuneus during others-related tasks. This meta-analysis also highlighted a shared connectivity pattern between self- and others-related tasks at the ventromedial prefrontal cortex and at the medial orbitofrontal cortex, thus providing neuroscientific evidence of the intricate relationship between representations of the self and of others. These findings may give new insight into disorders such as autism, schizophrenia and borderline personality disorder, in which the representations of the self and of others are dysfunctional or disrupted (van Veluw and Chance, 2014). It is worth noting that while modifying self-representation in relation to others is a challenging process, the interchange between self and other representations spontaneously takes place during transference-countertransference interactions in transference-focused psychotherapies as well as in other social relations. Such clinical evidence suggests that, rather than the distinct conceptualizations, the interactive dynamic relationship between self and other representations is central, (Kernberg et al., 2008; Yeomans et al., 2013). Future studies should investigate whether specific interactions between self and other representations are associated with specific brain connectivity patterns, and whether changes in these representations, as detectable in the transference dynamics, bring about modifications in brain connectivity.

The Self

In recent years, neuroscientific work has called attention to the study of the Self, previously confined to philosophy and psychology (Gallagher, 2000; Damasio, 2003; Kircher and David, 2003). Damasio (1999, 2003) and Panksepp (1998, 2003) suggested the existence of a “proto-self” in the sensory and motor domains. A “minimal self” (Gallagher, 2000; Gallagher and Frith, 2003) or a “core or mental self” (Damasio, 1999, 2003), an “autobiographical self” (Damasio, 1999, 2003) and a “narrative self” (Gallagher, 2000; Gallagher and Frith, 2003) have also been described. Beyond differences in definitions, it is possible to identify “self-related processes”, which comprise stimuli that are experienced as strongly related to one’s own person. It is very important to consider the self-stimulus relationship: the process of relating stimuli to the self should not be considered an isolated phenomenon, but rather as embedded in a larger, more complex process that depends on the environmental context (Clark, 1999; Northoff, 2004).

The Cortical Midline Structures (CMS) are brain areas related to self-referential experiences (Kelley et al., 2002). However, specific features of the self are also related to other cerebral regions (i.e., self-agency to right posterior insula and right inferior parietal cortex, self-ownership to right parietal and ventromedial prefrontal cortex; Northoff, 2004). The self therefore results from the integration of different areas, which necessarily involves neural connectivity. Northoff (2012) suggested that CMS might represent the neural correlate of the “core self”, defined by Damasio as the continuous interaction between intero- and exteroceptive stimuli that allow to perceive the self as a unit. CMS are activated in resting state conditions, and deactivated during cognitive tasks (Gusnard and Raichle, 2001; Raichle et al., 2001). Such physiological situation is linked to the psychological condition in which the core self is replaced and masked by cognitive activity, with a subjective experience of “permanent self” that represents a permanent baseline status for other psychological activities.

According to Northoff’s theory, neuroscientific research may go beyond the function and localization-based approach, moving from the “Neural Correlates of Psychodynamics” (NCC) to the “Neural Predisposition of Psychodynamics” (NPP), which refers to the neural condition of mental contents. NPP, in terms of empirical brain function, may refer to resting state activity and its “spatiotemporal structure”, which is the result of two main characteristics of resting state activity, namely low frequency fluctuations and functional connectivity patterns. The “virtual” concept of “Spatiotemporal Structure” may be compared to the Freudian approach to the “Psychological Structure” of the psychic apparatus, in that both are related to a process and an organization rather than a physical or psychological entity. The psychological predisposition of psychodynamic processes based on the Freudian psychological structure may also be related to resting state spatiotemporal structure and the so-called neural predisposition. From this point of view, resting state activity, with its spatiotemporal features that include functional connectivity between brain regions, could represent a model associated with Freudian Ego functions and dreams (for an overview, see Northoff, 2012).

Neuroscience looked into various aspects of the Self. In studies on schizophrenia, the relationship between the Self and the other has been particularly emphasized. Since the beginning of the 19th Century, phenomenology attributed a crucial role to the self and its pre-reflective attunement to the external world in schizophrenic psychopathology (Bleuler, 1911/1950; Minkowski, 1927). More recently, schizophrenia research has focused on abnormalities of the self (so-called ego-disturbances) and schizophrenia has been primarily characterized as a disorder of the self-other relationship (Parnas et al., 2002; Kircher and David, 2003; Nelson et al., 2009). Several empirical findings suggest that altered self-experience may result in an abnormal self-other relationship (Bentall et al., 1991; Ihnen et al., 1998; Peled et al., 2000; Voss et al., 2010; Morgan et al., 2011). Aberrant neural connectivity has been proposed as a basic feature of schizophrenic pathophysiology (Volkow et al., 1988; Meyer-Lindenberg and Weinberger, 2006). Neuroimaging research suggests aberrant structural and functional connectivity in schizophrenic patients (Walterfang et al., 2006; Skudlarski et al., 2010; Woodward et al., 2011; Fornito et al., 2012). However, the links between neural connectivity and social dysfunction are still poorly understood. Ebisch et al. (2013) performed a neuroimaging study with a social perception task on first episode schizophrenic patients, with the aim of highlighting brain functioning and its correlation with prodromal symptoms and self-other distinction abilities. The results of this study showed aberrant activation in the posterior insula, with impaired self-other distinction and reduced activation in the ventral premotor cortex, which negatively correlated with self-experience disturbances. These findings portray dysfunctional social perception in schizophrenia as a complex impairment involving multiple neural processing levels (Ebisch et al., 2013). Further connectivity analyses evidenced aberrant functional interactions of the posterior insula and the ventral premotor cortex with the posterior cingulate cortex (PCC), a midline region that plays a major role in mediating self-experience, suggesting an imbalance in the processing of internally and externally guided information and its abnormal integration with self-referential processing (Ebisch et al., 2014). This study provided insights on how impairments in the self-other relationship in schizophrenia may relate to altered functional interaction patterns.

Other investigations of resting state activity and functional connectivity in schizophrenia evidenced that resting state functional connectivity within the CMS and the default mode network (DMN) tends to increase. On the other hand, functional connectivity of the Control Executive Network (CEN) is reduced in schizophrenia (Hoptman et al., 2010; Karbasforoushan and Woodward, 2012). The stronger resting state activity and functional connectivity within the CMS and the DMN could be viewed as functional correlates of a greater focus on internal mental contents that are more related to the self. Conversely, stronger resting state activity and functional connectivity within the lateral regions and the CEN are related to an increase in external mental contents and awareness (Vanhaudenhuyse et al., 2011). The opposite functioning between DMN and CEN may represent the neural correlate of internal and external mental content. The confusion between internal and external mental contents that typically characterizes schizophrenic symptoms such as thought insertion, thought withdrawal, passivity symptoms and auditory hallucinations (Sommer et al., 2012) might be related to an imbalance between the two networks. Even though the exact meaning of the resting state abnormalities for psychiatric symptoms remains unclear, Northoff (2015) suggests a direct link between abnormalities of the resting state spatiotemporal structure and psychopathological symptoms such as ego disturbances and auditory hallucinations.

Given that the CMS may well represent the neural correlate of the “core self”, it is likely that abnormal activity in the CMS underlies anomalous self-perception and self-other relationship in schizophrenia. This hypothesis warrants further investigation in studies that link specific network alterations with the distinct subjective experiences of the pathological condition. In fact, in schizophrenia altered perception of internal and external stimuli reflects qualitative disturbances in discriminating between one’s own self and others. Future research on schizophrenia should take into account neuropsychoanalytic conceptualizations and focus on the study of the “Spatiotemporal Structure”, in order to further explore the basic and subjective aspects of this disorder. In fact, psychoanalysis’ contention that the self-others relationship is central to psychological development and change suggests that basic neural mechanisms (such as CMS functioning) may be affected over time by relational experiences and the environment in general. In this view, psychoanalytic theory may provide a valuable theoretical basis for neuroscientific studies on the self and its subjective experiences.

The Ego Functions and The Unconscious

To date, structural and functional correlates for the psychodynamic notion of unconscious processes (i.e., mental processes and contents that are defensively removed as a result of conflicting attitudes) have not been identified. In recent years, there has been an increasing interest, in unconscious processes; neuroscientific studies have, in fact, tested subliminal perceptions, implicit cognition, emotion processing and interoceptive perceptions with empirical methods (Stein et al., 2006; Craig, 2009). Though many studies indicate that unconscious processes influence awareness (for a review, see Berlin, 2011), the cognitive view of the unconscious differs from the psychodynamic notion of unconscious, which encompasses affect and motivation (Turnbull and Solms, 2007). Psychoanalytic theory holds that we are partly unaware of what we really feel. Studies on both healthy and brain-injured subjects demonstrated that even when a stimulus is not consciously perceived, it modulates neural activity and generates an emotional response. Custers and Aarts (2010) reviewed studies demonstrating the existence of an “unconscious will”, by which we persevere a goal regardless of conscious awareness.

In light of Freud’s distinction between primary and secondary processes (the functioning of the unconscious and the Ego, respectively), Carhart-Harris and Friston (2010) postulated that Freud’s description of ego functioning and development corresponds to the DMN functioning and its reciprocal exchanges with other brain networks. Freud (1895, 1900) described the secondary process as “bound” and “inhibited”, whereas the primary process is “free” and “motile”. The functional connectivity of the DMN appears to differ in childhood as compared to adulthood, and is altered in many brain disorders (Ouchi and Kikuchi, 2012). Possibly, loss of top-down control over limbic activity in hierarchically lower systems mirrors loss of ego control over the primary process. Freud held that the mode of normal waking consciousness depends on the existence of an equilibrium between the pressing forces of the primary process (entailed by the id) and the counter forces of the secondary process (entailed by the ego). This description is in line with current models of cognition based on hierarchical Bayesian inference and free energy, where backward connections from higher cortical areas work to reduce the free energy of lower areas (Carhart-Harris and Friston, 2010). From a clinical point of view, this approach provides novel insight on the pathogenesis of schizophrenia. An altered functional connectivity between limbic and cortical nodes of the DMN may predict symptoms of ego disturbance or primary process thinking in schizophrenia, mainly in the prodromal phase when these symptoms are prevalent (Parnas and Handest, 2003).

The displacement of energy from a “reservoir” to activity such as control of the external world is consistent with the functioning of the DMN and its relation with the dorsal attention system during goal-directed actions (Raichle et al., 2001). Considering that disease severity positively correlates with DMN connectivity, reduced task-evoked suppression of DMN activity observed in schizophrenia may be associated with reduced engagement with the external world (Whitfield-Gabrieli et al., 2009).

Conclusions

A rich body of literature suggests that abnormalities in the interactions of brain network components play a vital role in psychiatric disorders, and damage to specific functional connectivity networks can result in corresponding psychopathology. Studies on brain connectivity in schizophrenia and depressive disorders have improved knowledge on how complex alterations in brain functioning and neural network interaction underlie these disorders. Both the localizationist and the reductionist neuroscientific approaches to psychiatric disorders are outdated. While structural models of mind functioning appear to be insufficient, psychoanalytic theory provides a more appropriate organizational model of the mind, that matches recent neuroscientific findings on intrinsic brain networks. Many correlations between neuroscience and the theories of psychoanalysis have, in fact, been validated, and considerable progress has been made toward identifying neural correlates of abnormal self-processing in different psychiatric disorders, as maintained by psychoanalytic conceptualizations.

Psychoanalysis anticipated the neuroscientific approach postulating the existence of hierarchical systems comprising complex mental functions resulting from interactions between interconnected brain regions. To this respect, the Freudian “Psychological Structure” appears to be consistent with the neuroscientific approach based on brain connectivity. The CMS and their networks (right posterior insula, right inferior parietal cortex, ventromedial prefrontal cortex) may represent neural correlates of the “core self”, defined as the continuous interaction between intero- and exteroceptive stimuli, allowing the self to feel as a unit (Northoff, 2012). CMS are activated in resting state condition and deactivated during cognitive tasks.

Ego functioning most likely corresponds to the activation of the DMN and its reciprocal exchanges with other brain networks. An altered functional connectivity between cortical and limbic nodes of the DMN may predict symptoms of ego disturbance, such as alterations of primary process thinking in schizophrenia or attribution of negative emotions to the self in depressive disorders.

Taken together, this evidence suggests that brain connectivity research supports the convergence of neuroscientific findings and psychoanalysis, allowing for a new understanding of some fundamental concepts and symptomatic configurations. 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. Linking these neuroscientific findings and psychoanalytic theoretical models may result in new experimental paradigms and allow for investigation of the functional changes in the brain following psychotherapy, thus ultimately improving treatments.

Though the heuristic potential of psychoanalysis may support new acquisitions on brain connectivity, there is still much to investigate to fully understand mental functioning in both physiological and pathological conditions. The progress in neuroimaging techniques and the use, besides fMRI, of other techniques such as MEG, TMS and EEG (also combined with fMRI) will surely contribute to a deeper understanding. On the other hand, dynamic brain processes underlying mental functioning are not likely to be fully understood by means of neuroimaging techniques alone. Neuroscientific studies would benefit from more appropriate experimental paradigms that emphasize subjectivity and from interpretation of data that takes into account the complexity of the human mind.

Author Contributions

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

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.

The Review Editor Angela Iannitelli declare that, despite being affiliated with the same institution as the Author Carlo Lai, the review process was handled objectively.

The Reviewer Francesca Ferri declare that, despite having collaborated with the authors Anatolia Salone, Domenico De Berardis and Massimo Di Giannantonio, the review process was handled objectively.

References

Beauregard, M. (2007). Mind does really matter: evidence from neuroimaging studies of emotional self-regulation, psychotherapy and placebo effect. Prog. Neurobiol. 81, 218–236. doi: 10.1016/j.pneurobio.2007.01.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Bentall, R. P., Baker, G. A., and Havers, S. (1991). Reality monitoring and psychotic hallucinations. Br. J. Clin. Psychol. 30, 213–222. doi: 10.1111/j.2044-8260.1991.tb00939.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Berlin, H. A. (2011). The neural basis of the dynamic unconscious. Neuropsychoanalysis 13, 5–31. doi: 10.1080/15294145.2011.10773654

CrossRef Full Text | Google Scholar

Bleuler, E. (1911/1950). Dementia Praecox or The Group of Schizophrenias. New York: International University Press.

Google Scholar

Carhart-Harris, R. L., and Friston, K. J. (2010). The default-mode, ego functions and free-energy: a neurobiological account of Freudian ideas. Brain 133, 1265–1283. doi: 10.1093/brain/awq010

PubMed Abstract | CrossRef Full Text | Google Scholar

Clark, A. (1999). An embodied cognitive science? Trends Cogn. Sci. 3, 345–351. doi: 10.1016/s1364-6613(99)01361-3

PubMed Abstract | CrossRef Full Text | Google Scholar

Cozolino, L. (2010). The Neuroscience of Psychotherapy. New York, NY: W. W. Norton and Co.

Craig, A. D. (2009). How do you feel-now? The anterior insula and human awareness. Nat. Rev. Neurosci. 10, 59–70. doi: 10.1038/nrn2555

PubMed Abstract | CrossRef Full Text | Google Scholar

Custers, R., and Aarts, H. (2010). The unconscious will: how the pursuit of goals operates outside of conscious awareness. Science 329, 47–50. doi: 10.1126/science.1188595

PubMed Abstract | CrossRef Full Text | Google Scholar

Damasio, A. R. (1999). The Feeling of What Happens: Body and Emotion in the Making of Consciousness. New York, NY: Harcourt Brace.

Damasio, A. (2003). Feelings of emotion and the self. Ann. N Y Acad. Sci. 1001, 253–261. doi: 10.1196/annals.1279.014

PubMed Abstract | CrossRef Full Text | Google Scholar

Demertzi, A., Liew, C., Ledoux, D., Bruno, M. A., Sharpe, M., Laureys, S., et al. (2009). Dualism persists in the science of mind. Ann. N Y Acad. Sci. 1157, 1–9. doi: 10.1111/j.1749-6632.2008.04117.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Dierks, T., Linden, D. E. J., Jandl, M., Formisano, E., Goebel, R., Lanfermann, H., et al. (1999). Activation of Heschl’s gyrus during auditory hallucinations. Neuron 22, 615–621. doi: 10.1016/s0896-6273(00)80715-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Ebisch, S. J., Mantini, D., Northoff, G., Salone, A., De Berardis, D., Ferri, F., et al. (2014). Altered brain long-range functional interactions underlying the link between aberrant self-experience and self-other relationship in first-episode schizophrenia. Schizophr. Bull. 40, 1072–1082. doi: 10.1093/schbul/sbt153

PubMed Abstract | CrossRef Full Text | Google Scholar

Ebisch, S. J., Salone, A., Ferri, F., De Berardis, D., Romani, G. L., Ferro, F. M., et al. (2013). Out of touch with reality? Social perception in first-episode schizophrenia. Soc. Cogn. Affect. Neurosci. 8, 394–403. doi: 10.1093/scan/nss012

PubMed Abstract | CrossRef Full Text | Google Scholar

Feinberg, T. E. (2011). Neuropathologies of the self: clinical and anatomical features. Conscious. Cogn. 20, 75–81. doi: 10.1016/j.concog.2010.09.017

PubMed Abstract | CrossRef Full Text | Google Scholar

Fonagy, P. (2003). Psychoanalysis today. World Psychiatry 2, 73–80.

PubMed Abstract | Google Scholar

Fornito, A., Zalesky, A., Pantelis, C., and Bullmore, E. T. (2012). Schizophrenia, neuroimaging and connectomics. Neuroimage 62, 2296–2314. doi: 10.1016/j.neuroimage.2011.12.090

PubMed Abstract | CrossRef Full Text | Google Scholar

Fotopoulou, A., Pfaff, D., and Conway, M. A. (2012). From the Couch to the Lab: Trends in Psychodynamic Neuroscience. Oxford: Oxford University Press.

Google Scholar

Freud, S. (1895). Project for a Scientific Psychology. Standard Edn. (Vol. 1). London: Vintage.

Freud, S. (1900). The Interpretation of Dreams. London: Penguin.

Google Scholar

Friston, K. J. (1994). Functional and effective connectivity in neuroimaging: a synthesis. Hum. Brain. Mapp. 2, 56–78. doi: 10.1002/hbm.460020107

CrossRef Full Text | Google Scholar

Furmark, T., Tillfors, M., Marteinsdottir, I., Fischer, H., Pissiota, A., Långström, B., et al. (2002). Common changes in cerebral blood flow in patients with social phobia treated with citalopram or cognitive-behavioral therapy. Arch. Gen. Psychiatry 59, 425–433. doi: 10.1001/archpsyc.59.5.425

PubMed Abstract | CrossRef Full Text | Google Scholar

Gallagher, S. (2000). Philosophical conceptions of the self: implications for cognitive science. Trends Cogn. Sci. 4, 14–21. doi: 10.1016/s1364-6613(99)01417-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Gallagher, H. L., and Frith, C. D. (2003). Functional imaging of ‘theory of mind’. Trends Cogn. Sci. 7, 77–83. doi: 10.1016/s1364-6613(02)00025-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Gallese, V. (2008). Empathy, embodied simulation and the brain: commentary on Aragno and Zepf/Hartmann. J. Am. Psychoanal. Assoc. 56, 769–781. doi: 10.1177/0003065108322206

PubMed Abstract | CrossRef Full Text | Google Scholar

Gusnard, D. A., and Raichle, M. E. (2001). Searching for a baseline: functional imaging and the resting human brain. Nat. Rev. Neurosci 2, 685–694. doi: 10.1038/35094500

PubMed Abstract | CrossRef Full Text | Google Scholar

Hobson, J. A. (2009). REM sleep and dreaming: towards a theory of protoconsciousness. Nat. Rev. Neurosci. 10, 803–813. doi: 10.1038/nrn2716

PubMed Abstract | CrossRef Full Text | Google Scholar

Hoptman, M. J., Zuo, X. N., Butler, P. D., Javitt, D. C., D’angelao, D., Mauro, C. J., et al. (2010). Amplitude of lowfrequency oscillations in schizophrenia: a resting state fMRI study. Schizophr. Res. 117, 13–20. doi: 10.1016/j.schres.2009.09.030

PubMed Abstract | CrossRef Full Text | Google Scholar

Ihnen, G. H., Penn, D. L., Corrigan, P. W., and Martin, J. (1998). Social perception and social skill in schizophrenia. Psychiatry Res. 80, 275–286. doi: 10.1016/s0165-1781(98)00079-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Ionta, S., Martuzzi, R., Salomon, R., and Blanke, O. (2014). The brain network reflecting bodily self-consciousness: a functional connectivity study. Soc. Cogn. Affect. Neurosci. 9, 1904–1913. doi: 10.1093/scan/nst185

PubMed Abstract | CrossRef Full Text | Google Scholar

Kandel, E. R. (1989). Genes, nerve cells and the remembrance of things past. J. Neuropsychiatry Clin. Neurosci. 1, 103–125. doi: 10.1176/jnp.1.2.103

PubMed Abstract | CrossRef Full Text | Google Scholar

Kandel, E. R. (1998). A new intellectual framework for psychiatry. Am. J. Psychiatry 155, 457–469. doi: 10.1176/ajp.155.4.457

PubMed Abstract | CrossRef Full Text | Google Scholar

Kandel, E. R. (1999). Biology and the future of psychoanalysis: a new intellectual framework for psychiatry revisited. Am. J. Psychiatry 156, 505–524.

PubMed Abstract | Google Scholar

Kandel, E. R. (2005). “From metapsychology to molecular biology,” in Psychiatry, Psychoanalysis and the New Biology of Mind, ed. D. Klein (Washington, DC: American Psychiatry Pub), XV–XXVI.

Google Scholar

Karbasforoushan, H., and Woodward, N. D. (2012). Resting-state networks in schizophrenia. Curr. Top. Med. Chem. 12, 2404–2414. doi: 10.2174/156802612805289863

PubMed Abstract | CrossRef Full Text | Google Scholar

Karlsonn, H. (2011). How psychotherapy changes the brain. Psychiat. Times 28, 21–23.

Kelley, W. M., Macrae, C. N., Wyland, C. L., Caglar, S., Inati, S., and Heatherton, T. F. (2002). Finding the self? An event-related fMRI study. J. Cogn. Neurosci. 14, 785–794. doi: 10.1162/08989290260138672

PubMed Abstract | CrossRef Full Text | Google Scholar

Kernberg, O. F., Yeomans, F. E., Clarkin, J. F., and Levy, K. N. (2008). Transference focused psychotherapy: overview and update. Int. J. Psychoanal. 89, 601–620. doi: 10.1111/j.1745-8315.2008.00046.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Kircher, T., and David, A. (2003). The Self in Neuroscience and Psychiatry. Cambridge: Cambridge Univ Press.

Google Scholar

Leichsenring, F., and Rabung, S. (2011). Long-term psychodynamic psychotherapy in complex mental disorders: update of a meta-analysis. Br. J. Psychiatry 199, 15–22. doi: 10.1192/bjp.bp.110.082776

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, W., Mai, X., and Liu, C. (2014). The default mode network and social understanding of others: what do brain connectivity studies tell us. Front. Hum. Neurosci. 8:74. doi: 10.3389/fnhum.2014.00074

PubMed Abstract | CrossRef Full Text | Google Scholar

Linden, D. E. (2006). How psychotherapy changes the brain- the contribution of functional neuroimaging. Mol. Psychiatry 11, 528–538. doi: 10.1038/sj.mp.4001816

PubMed Abstract | CrossRef Full Text | Google Scholar

Luciani, M., Cecchini, M., Altavilla, D., Palumbo, L., Aceto, P., Ruggeri, G., et al. (2014). Neural correlate of the projection of mental states on the not-structured visual stimuli. Neurosci. Lett. 573, 24–29. doi: 10.1016/j.neulet.2014.05.008

PubMed Abstract | CrossRef Full Text | Google Scholar

Mancia, M. (2004). The dream between neuroscience and psychoanalysis. Arch. Ital. Biol. 142, 525–531.

PubMed Abstract | Google Scholar

Mancia, M. (2006a). Implicit memory and early unrepressed unconscious: their role in the therapeutic process (how the neurosciences can contribute to psychoanalysis). Int. J. Psychoanal. 87, 83–103. doi: 10.1516/d43p-8upn-x576-a8v0

PubMed Abstract | CrossRef Full Text | Google Scholar

Mancia, M. (2006b). Psychoanalysis and Neuroscience. Milan: Springer.

Google Scholar

McGuire, P. K., Bench, C. J., Frith, C. D., Marks, I. M., Frackowiak, R. S., and Dolan, R. J. (1994). Functional anatomy of obsessive-compulsive phenomena. Br. J. Psychiatry 164, 459–468. doi: 10.1192/bjp.164.4.459

PubMed Abstract | CrossRef Full Text | Google Scholar

Meyer-Lindenberg, A., and Weinberger, D. R. (2006). Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nat. Rev. Neurosci. 7, 818–827. doi: 10.1038/nrn1993

PubMed Abstract | CrossRef Full Text | Google Scholar

Minkowski, E. (1927). La Schizophrénie. Psychopathologie des Schizoides et de Schizophrénes. Paris: Payot.

Molnar-Szakacs, I., and Uddin, L. Q. (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

PubMed Abstract | CrossRef Full Text | Google Scholar

Morgan, H. L., Turner, D. C., Corlett, P. R., Abasalo, A. R., Adapa, R., Arana, F. S., et al. (2011). Exploring the impact of ketamine on the experience of illusory body ownership. Boil. Psychiatry 69, 35–41. doi: 10.1016/j.biopsych.2010.07.032

PubMed Abstract | CrossRef Full Text | Google Scholar

Murray, R. J., Debbané, M., Fox, P. T., Bzdok, D., and Eickhoff, S. B. (2014). Functional connectivity mapping of regions associated with self- and other-processing. Hum. Brain Mapp. 36, 1304–1324. doi: 10.1002/hbm.22703

PubMed Abstract | CrossRef Full Text | Google Scholar

Nelson, B., Fornito, A., Harrison, B. J., Yücel, M., Sass, L. A., Yung, A. R., et al. (2009). A disturbed sense of self in the psychosis prodrome: linking phenomenology and neurobiology. Neurosci. Biobehav. Rev. 33, 807–817. doi: 10.1016/j.neubiorev.2009.01.002

PubMed Abstract | CrossRef Full Text | Google Scholar

Northoff, G. (2004). Cortical midline structures and the self. Trends Cogn. Sci. 8, 102–107. doi: 10.1016/j.tics.2004.01.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Northoff, G. (2011). Neuropsychoanalysis in Practice: Brain, Self and Objects. New York: Oxford University Press.

Google Scholar

Northoff, G. (2012). Psychoanalisis and the brain-why did Freud abandon neuroscience? Front. Psychol. 3:71. doi: 10.3389/fpsyg.2012.00071

PubMed Abstract | CrossRef Full Text | Google Scholar

Northoff, G. (2015). Is schizophrenia a spatiotemporal disorder of the brain’s resting state? World Psychiatry 14, 34–35. doi: 10.1002/wps.20177

PubMed Abstract | CrossRef Full Text | Google Scholar

Northoff, G., and Boeker, H. (2006). Principles of neuronal integration and defense mechanisms: a neuropsychoanalytic hypothesis. Neuropsychoanalysis 8, 69–84. doi: 10.1080/15294145.2006.10773514

CrossRef Full Text | Google Scholar

Ouchi, Y., and Kikuchi, M. (2012). A review of the default mode network in aging and dementia based on molecular imaging. Rev. Neurosci. 23, 263–268. doi: 10.1515/revneuro-2012-0029

PubMed Abstract | CrossRef Full Text | Google Scholar

Panksepp, J. (1998). Affective Neuroscience: The Foundations of Human and Animal Emotions. New York: Oxford University Press.

Google Scholar

Panksepp, J. (2003). At the interface of the affective, behavioral, and cognitive neurosciences: decoding the emotional feelings of the brain. Brain Cogn. 52, 4–14. doi: 10.1016/S0278-2626(03)00003-4

CrossRef Full Text | Google Scholar

Panksepp, J. (2011). Cross-species affective neuroscience decoding of the primal affective experiences of humans and related animals. PLoS One 6:e21236. doi: 10.1371/journal.pone.0021236

PubMed Abstract | CrossRef Full Text | Google Scholar

Panksepp, J., and Biven, L. (2012). The Archaeology of Mind: Neuroevolutionary Origins of the Human Emotions. New York: W. W. Norton and Co.

Panksepp, J., and Solms, M. (2012). What is neuropsychoanalysis? Clinically relevant studies of the minded brain. Trends Cogn. Sci. 16, 6–8. doi: 10.1016/j.tics.2011.11.005

PubMed Abstract | CrossRef Full Text

Paquette, V., Lévesque, J., Mensour, B., Leroux, J. M., Beaudoin, G., Bourgouin, P., et al. (2003). “Change the mind and you change the brain”: effects of cognitive-behavioral therapy on the neural correlates of spider phobia. Neuroimage 18, 401–409. doi: 10.1016/s1053-8119(02)00030-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Parnas, J., Bovet, P., and Zahavi, D. (2002). Schizophrenic autism: clinical phenomenology and pathogenetic implications. World Psychiatry 1, 131–136.

PubMed Abstract | Google Scholar

Parnas, J., and Handest, P. (2003). Phenomenology of anomalous self-experience in early schizophrenia. Compr. Psychiatry 44, 121–134. doi: 10.1053/comp.2003.50017

PubMed Abstract | CrossRef Full Text | Google Scholar

Peled, A., Ritsner, M., Hirschmann, S., Geva, A. B., and Modai, I. (2000). Touch feel illusion in schizophrenic patients. Biol. Psychiatry 48, 1105–1108. doi: 10.1016/s0006-3223(00)00947-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., and Shulman, G. L. (2001). A default mode of brain function. Proc. Natl. Acad. Sci. U S A 98, 676–682. doi: 10.1073/pnas.98.2.676

PubMed Abstract | CrossRef Full Text | Google Scholar

Rauch, S. L. (2003). Neuroimaging and neurocircuitry models pertaining to the neurosurgical treatment of psychiatric disorders. Neurosurg. Clin. N Am. 14, 213–223. doi: 10.1016/s1042-3680(02)00114-6

PubMed Abstract | CrossRef Full Text

Rudorf, S., and Hare, T. A. (2014). Interactions between dorsolateral and ventromedial prefrontal cortex underlie context-dependent stimulus valuation in goal-directed choice. J. Neurosci. 34, 15988–15996. doi: 10.1523/JNEUROSCI.3192-14.2014

PubMed Abstract | CrossRef Full Text | Google Scholar

Schore, A. N. (2003). Affect Regulation and the Repair of the Self. New York: W.W. Norton.

Skudlarski, P., Jagannathan, K., Anderson, K., Stevens, M. C., Calhoun, V. D., Skudlarska, B. A., et al. (2010). Brain connectivity is not only lower but different in schizophrenia: a combined anatomical and functional approach. Boil. Psychiatry 68, 61–69. doi: 10.1016/j.biopsych.2010.03.035

PubMed Abstract | CrossRef Full Text | Google Scholar

Solms, M. (1997). What is consciousness? J. Am. Psychoanal. Assoc. 45, 681–703. doi: 10.1177/00030651970450031201

CrossRef Full Text | Google Scholar

Solms, M. (2000). Dreaming and REM sleep are controlled by different brain mechanisms. Behav. Brain Sci. 23, 843–850. doi: 10.1017/s0140525x00003988

PubMed Abstract | CrossRef Full Text | Google Scholar

Solms, M. (2004). Freud returns. Sci. Am. 290, 82–88. doi: 10.1038/scientificamerican0504-82

PubMed Abstract | CrossRef Full Text | Google Scholar

Solms, M., and Solms-Kaplan, K. (2000). Clinical Studies in Neuro-Psychoanalysis. London: Karnac Books.

Solms, M., and Turnbull, O. (2002). The Brain and the Inner World: An Introduction to the Neuroscience of Subjective Experience. New York, NY: Other Press.

Google Scholar

Sommer, I. E., Clos, M., Meijering, A. L., Diederen, K. M., and Eickhoff, S. B. (2012). Resting state functional connectivity in patients with chronic hallucinations. PLoS One 7:e43516. doi: 10.1371/journal.pone.0043516

PubMed Abstract | CrossRef Full Text | Google Scholar

Stein, D. J., Solms, M., and van Honk, J. (2006). The cognitive-affective neuroscience of the unconscious. CNS Spectr. 11, 580–583.

PubMed Abstract | Google Scholar

Touskova, T., and Bob, P. (2015). Consciousness, awareness of insight and neural mechanisms of schizophrenia. Rev. Neurosci. 26, 295–304. doi: 10.1515/revneuro-2014-0063

PubMed Abstract | CrossRef Full Text | Google Scholar

Toyokawa, S., Uddin, M., Koenen, K. C., and Galea, S. (2011). How does the social environment ‘get into the mind’? Epigenetics at the intersection of social and psychiatric epidemiology. Soc. Sci. Med. 74, 67–74. doi: 10.1016/j.socscimed.2011.09.036

PubMed Abstract | CrossRef Full Text | Google Scholar

Turnbull, O. H., and Solms, M. (2007). Awareness, desire and false beliefs: freud in the light of modern neuropsychology. Cortex 43, 1083–1090. doi: 10.1016/s0010-9452(08)70706-8

PubMed Abstract | CrossRef Full Text

Vanhaudenhuyse, A., Demertzi, A., Schabus, M., Noirhomme, Q., Bredart, S., Boly, M., et al. (2011). Two distinct neuronal networks mediate the awareness of environment and of self. J. Cogn. Neurosci. 23, 570–578. doi: 10.1162/jocn.2010.21488

PubMed Abstract | CrossRef Full Text | Google Scholar

van Veluw, S. J., and Chance, S. A. (2014). Differentiating between self and others: an ALE meta-analysis of fMRI studies of self-recognition and theory of mind. Brain Imaging Behav. 8, 24–38. doi: 10.1007/s11682-013-9266-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Viinamaki, H., Kuikka, J., Tiihonen, J., and Lehtonen, J. (1998). Change in monoamine transporter density related to clinical recovery: a case—control study. Nord. J. Psychiatry 52, 39–44. doi: 10.1080/080394898422553

CrossRef Full Text | Google Scholar

Volkow, N. D., Wolf, A. P., Brodie, J. D., Cancro, R., Overall, J. E., Rhoades, H., et al. (1988). Brain interactions in chronic schizophrenic under resting and activation conditions. Schizophr. Res. 1, 47–53. doi: 10.1016/0920-9964(88)90010-2

PubMed Abstract | CrossRef Full Text | Google Scholar

Voss, M., Moore, J., Hauser, M., Gallinat, J., Heinz, A., and Haggerd, P. (2010). Altered awareness of action in schizophrenia: a specific deficit in predicting action consequences. Brain 133, 3104–3112. doi: 10.1093/brain/awq152

PubMed Abstract | CrossRef Full Text | Google Scholar

Walterfang, M., Wood, S. J., Velakoulis, D., and Pantelis, C. (2006). Neuropathological, neurogenetic and neuroimaging evidence for white matter pathology in schizophrenia. Neurosci. Biobehav. Rev. 30, 918–948. doi: 10.1016/j.neubiorev.2006.02.001

PubMed Abstract | CrossRef Full Text | Google Scholar

Whitfield-Gabrieli, S., Thermenos, H. W., Milanovic, S., Tsuang, M. T., Faraone, S. V., McCarley, R. W., et al. (2009). Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first degree relatives of persons with schizophrenia. Proc. Natl. Acad. Sci. U S A 106, 1279–1284. doi: 10.1073/pnas.0809141106

PubMed Abstract | CrossRef Full Text | Google Scholar

Woodward, N. D., Rogers, B., and Heckers, S. (2011). Functional resting-state networks are differentially affected in schizophrenia. Schizophr. Res. 130, 86–93. doi: 10.1016/j.schres.2011.03.010

PubMed Abstract | CrossRef Full Text | Google Scholar

Yeomans, F. E., Levy, K. N., and Caligor, E. (2013). Transference-focused psychotherapy. Psychotherapy (Chic) 50, 449–453. doi: 10.1037/a0033417

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: neuropsychoanalysis, neuroscience, connectivity, schizophrenia, self, unconscious

Citation: Salone A, Di Giacinto A, Lai C, De Berardis D, Iasevoli F, Fornaro M, De Risio L, Santacroce R, Martinotti G and Di Giannantonio M (2016) The Interface between Neuroscience and Neuro-Psychoanalysis: Focus on Brain Connectivity. Front. Hum. Neurosci. 10:20. doi: 10.3389/fnhum.2016.00020

Received: 06 August 2014; Accepted: 14 January 2016;
Published: 03 February 2016.

Edited by:

Michele Ribolsi, University of Rome Tor Vergata, Italy

Reviewed by:

Francesca Ferri, University of Ottawa, Canada
Angela Iannitelli, Sapienza University of Rome, Italy

Copyright © 2016 Salone, Di Giacinto, Lai, De Berardis, Iasevoli, Fornaro, De Risio, Santacroce, Martinotti and Di Giannantonio. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and 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.

*Correspondence: Anatolia Salone, asalone@unich.it

Download