Edited by: Srikantan S. Nagarajan, University of California, San Francisco, USA
Reviewed by: Frank van der Velde, University of Twente, Netherlands; Lars Kuchinke, International Psychoanalytic University Berlin, Germany
*Correspondence: Roberto G. de Almeida
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Sentences such as
A hallmark of linguistic communication is that sentences are often indeterminate: their
John wants a beer;
Mary began the book.
In fact, there are many possible interpretations for sentences (1a) and (1b) beyond what they say. What is not clear is the source of information that is supposed to enrich the content of these sentences beyond what their constituent words and their modes of combination provide. More specifically, how does
Thus far, there have been two prevalent theoretical views on how indeterminate sentences such as (1a) and (1b) are understood. The
With regards to the neurological correlates of indeterminate sentence comprehension, different studies point to the engagement of different neuroanatomical regions as the main source of indeterminacy resolution. For instance, magnetoencephalography (MEG) studies suggest that the ventromedial prefrontal cortex (vmPFC) is the main site of indeterminacy resolution—in fact, the site of semantic coercion (Pylkkänen and McElree,
While our main goal is to establish the neurological resources deployed in the resolution of indeterminate sentences, our empirical investigation also aims to contribute to a better understanding of the theoretical underpinnings of indeterminacy—whether sentences are resolved by semantic coercion or pragmatic processes. We thus begin by discussing what is at stake in the investigation of indeterminate sentence comprehension: how the brain might compose meanings of sentences.
The process of understanding a sentence requires at a minimum that the meaning of its constituent words or morphemes be put together according to its structure—what is known as
The coercion theory by and large adopts a view known as
In contrast, the pragmatic-inferential theory assumes that the initial representation of a sentence is only a function of the meaning of its constituent words and how they are structured together—in syntax or logical form—a position commonly referred to as
In summary, while what we called coercion theory takes type-shifting and interpolation to be key elements of enrichment—with varying degrees of contribution from other knowledge systems (see e.g., Traxler et al.,
There have been numerous behavioral studies investigating how indeterminate sentences might be processed. These have involved experimental paradigms such as self-paced reading (McElree et al.,
The secretary began the memo before the annual sales conference (indeterminate);
The secretary typed the memo before the annual sales conference (preferred);
The secretary read the memo before the annual sales conference (non-preferred);
The secretary began [
While these studies have been useful in calling attention to the phenomenon, their results have been conflicting (see e.g., de Almeida,
Perhaps more important for our current purposes are studies employing cognitive neuroscience methods, which can complement behavioral studies while also potentially helping us dissociate the very source of behavioral differences. Most relevant to the present study were the studies by Pylkkänen and McElree (
In their MEG study, Pylkkänen and McElree (
The journalist began the article after his coffee break (
The journalist astonished the article after his coffee break (
The journalist wrote the article after his coffee break (
They found that, relative to the other conditions, indeterminate sentences produced a unique response in what they called the anterior midline field (AMF), hypothesized to be at the vmPFC. This response occurred at 350–500 ms after the presentation of the NP
Most recently, Husband et al. (
Husband et al. (
Although we regard these data as informative, the neurological underpinnings and, more importantly, the source of indeterminacy resolution remain unresolved. One possible explanation for the difference between the MEG and fMRI results is that the proposed AMF activation represents core processes occurring in medial frontal regions other than the vmPFC. If this is indeed the case, additional fMRI data are needed to explore these regions in greater detail. In addition, although Pylkkänen and McElree (
The primary goal of the present fMRI study was to determine the brain areas recruited in attempting to resolve indeterminate sentences. We reasoned that the neuroanatomical signature of indeterminate sentences would be fundamentally different from that of determinate sentences on the assumption that indeterminate sentences might trigger the search for implicatures akin to what is triggered when sentences flout a conversational maxim (Grice,
Although our main hypotheses are not tied to specific neuroanatomical regions—for we aim to find differences in the neuronal correlates between indeterminate and other types of sentences—we will discuss rather briefly the literature on the neuroanatomy of language processing and how it helps us lay out our hypotheses. Numerous reviews and meta-analytic studies have shown that large neuroanatomical regions beyond the classical linguistic areas (e.g., Broca’s and Wernicke’s) are involved in linguistic processes serving comprehension and production (e.g., Bookheimer,
While linguistic processes involved in language comprehension appear to rely on the LH default language network, there are several issues with how these processes map onto higher mechanisms of language interpretation. For instance, the neuroanatomical resources involved in pragmatic processes are less than clear. Studies with RH-damaged patients have shown diminished comprehension of implicit requests, irony, and metaphors (e.g., Champagne-Lavau and Joanette,
While hemispheric asymmetry in language processing is clear, many have questioned the so-called “right-hemisphere hypothesis”, i.e., the hypothesis that the RH is primarily involved in high-level, pragmatic processes (for a review see e.g., Stemmer,
Results from these studies with figurative language, which arguably require inferences or the search for what is implicated, are compatible with those that employed semantically or pragmatically odd sentences, which also involve reinterpretation or the detection of a mismatch in semantic composition (e.g., Ni et al.,
The picture that emerges from the literature on neurological implementation of linguistic processes allows us to hypothesize that regions engaged in pragmatic and high-level cognitive processes would be more involved in the comprehension of indeterminate sentences (e.g.,
We should note that these hypotheses can only be laid down in broad strokes, for we cannot distinguish between sources of indeterminacy resolution without a clear understanding of what types of
In addition to examining the networks activated by indeterminate sentences relative to preferred controls, we sought to inform the pragmatic hypothesis by observing how indeterminate sentences pattern relative to anomalous sentences, such as
Our norming study was framed by three main goals. First, we wanted to gather acceptability rating data for the 648 sentences employed in the fMRI experiment to ensure that our canonical sentences would be rated within the normal range in contrast with the anomalous conditions. Our second goal was to obtain RT data for each sentence, segment by segment, to allow us to contrast our materials with those employed in the psycholinguistics literature. And our third goal was to obtain a behavioral complement to our fMRI experiment. The latter was designed to elicit natural language processing without the complication of a secondary task, be it psychomotor (e.g., button-pressing in self-paced reading) or cognitive (grammaticality ratings). Sentence rating tasks in particular may be problematic because they require participants to engage in a metalinguistic mode of processing, thus confounding the signal of online comprehension processes. To date, both the MEG (Pylkkänen and McElree,
The experimental sentences were created by first asking a group of 60 students to fill in the blanks of frames such as
Sentence type | Sample | |||||
---|---|---|---|---|---|---|
Preferred | The author wrote the book | 107 | 4.76 | 0.33 | – | – |
Full-VP | The author started writing the book | 107 | 4.54 | 0.46 | 0.63 | 0.35 |
Non-preferred | The author read the book | 107 | 4.44 | 0.59 | 0.68 | 0.48 |
Indeterminate | The author started the book | 107 | 3.54 | 1.06 | 0.84 | 1.46 |
Syntactically anomalous | The author yawned the book | 107 | 1.23 | 0.27 | 0.55 | 6.42 |
Pragmatically anomalous | The author drank the book | 107 | 1.46 | 0.49 | 0.64 | 5.15 |
A group of 89 students who did not participate in the other tasks was asked to judge the acceptability of the sentences on a 5-point scale. They all gave written informed consent and participated for course credit as part of the Concordia Psychology Participant Pool. Table
In order to evaluate the degree to which each condition departed from the canonical preferred condition, we calculated mean-difference effect sizes (
Another group of 83 participants, all of whom gave informed consent, completed a word-by-word self-paced reading task. The six sentence conditions and a set of 65 filler sentences were presented in random order. Among the fillers, 25 sentences were followed by Yes/No questions to ensure that the participants remained attentive throughout the task.
Reading time data for all six conditions are summarized in Table
Verb type | Sentence position | ||
---|---|---|---|
Verb | Determiner |
Noun |
|
Preferred ( |
355 (86) | 333 (66) | 454 (186) |
Non-preferred ( |
359 (87) | 336 (70) | 470 (192) |
Indeterminate ( |
365 (95) | 342 (68) | 480 (192) |
Full VP ( |
377 (95) | 348 (65) | 476 (227) |
Syntactically anomalous ( |
360 (96) | 365 (99) | 515 (229) |
Pragmatically anomalous ( |
365 (99) | 347 (68) | 492 (227) |
At the verb position, there was no difference between sentences in the participants analysis,
At the determiner position, both participants and items analyses revealed statistically significant main effects,
There was also a main effect of sentence at the noun position,
These RT data are largely in keeping with effects observed in the psycholinguistics literature, which typically demonstrates that indeterminate sentences take longer to process post-verbally than preferred sentences (e.g., McElree et al.,
In addition to replicating the RT effects found in other behavioral studies, we conducted additional analyses to further characterize our materials and guide hypotheses. Table
Sentence type | By participants | By items | |
---|---|---|---|
Preferred | −25.61 | ||
Non-preferred | −10.16 | ||
Full-VP | −4.27 | ||
Syntactically anomalous | 34.87 | ||
Pragmatically anomalous | 12.01 |
These results converge with our ratings data, which showed a continuum of acceptability judgments from preferred sentences (most felicitous) to syntactically anomalous sentences (least felicitous), and that indeterminate sentences lie closer to the felicitous end of this spectrum. Having collected both off-line and on-line response measures for our materials, we set out to conduct an fMRI experiment requiring participants to passively read the stimuli, thus allowing us to track language comprehension processes without the potential contaminations of an extraneous task.
As we have described above, our principal hypotheses concern patterns of activation for indeterminate sentences compared with preferred sentences and pragmatic violations. But we have also included several conditions that would allow us to explore secondary hypotheses regarding the nature of indeterminate sentence processing. We now elaborate on our main hypotheses and the contrasts with each condition.
We have designed the present experiment aiming to understand the pattern of activation for indeterminate sentences and thus gain insights into the nature of the neurocognitive resources employed in the resolution of indeterminacy. Given the inconsistent neuroanatomical correlates found in the two studies employing fMRI and MEG, we sought out first to establish the map of indeterminacy resolution. In addition we aimed to gather support for either the coercion or the pragmatic theory. Support for the coercion theory would be rather restricted to greater linguistic operations either at the L-IFG (Husband et al.,
Preferred sentences represent the canonical form. They are employed as the standard control condition for indeterminate sentences, and have been shown to be processed more easily than indeterminate sentences (e.g., McElree et al.,
Our acceptability judgments showed that what we called pragmatically anomalous sentences are regarded as infelicitous compared to preferred and indeterminate sentences. However, although they engendered numerically longer RTs relative to indeterminate sentences (
Although syntactically well formed, non-preferred sentences describe activities that are less strongly associated with the agent in the sentence, and are therefore rated lower than preferred sentences. Although they are grammatical, their interpretation requires accessing non-dominant meanings, which makes them more demanding than preferred sentences (de Almeida,
Full-VP sentences are both syntactically well formed and pragmatically felicitous. However, our RT data show that they take longer to process than preferred sentences at the object position and that they are not significantly faster than indeterminate sentences. Full-VP sentences are structurally and semantically more complex then preferred sentences, and thus might require additional computations. These factors may have increased processing times, even though the sentences were judged to be felicitous. Accordingly, we predicted that full-VP sentences would recruit more linguistic resources than preferred sentences as a function of their complexity—in particular due to the need to compose the more complex VP. They should therefore diverge from indeterminate sentences pragmatically: rather than leaving the nature of the event to be inferred, they make it explicit.
These sentences were formed by using non-alternating intransitive verbs with complements. These sentences were judged to be the least felicitous and have generated the longest processing latencies. There are at least two possibilities for how the parser might deal with such structural violations: (1) pursue effortful repair processes; or (2) reject the sentence as ungrammatical without additional effort. Accordingly, syntactically anomalous sentences may show increased patterns of activation reflecting post-linguistic repair processes, or rather, display minimal patterns of activation reflecting early rejection—at the verb-object—by the parser. Support for “early rejection” would be obtained if most sentence types, but particularly indeterminate and pragmatically anomalous sentences, engage pragmatic resources more so than syntactically anomalous sentences. Support for a “repair” hypothesis, thus, would pattern these sentences with pragmatically anomalous and indeterminate sentences.
Eighteen Concordia University students (14 females) participated in this experiment. They ranged in age from 18 to 38 years (
We employed the 648 sentences developed in our norming study, with the same distribution of materials into six lists, and the same fillers and questions.
A 3 Tesla Whole Body MR System (MAGNETOM Trio, Siemens Medical Systems, and Erlangen, Germany) was used for image acquisition. Before the fMRI run, 160 3D FLASH structural images were acquired in slices of 1.2 mm thickness in the sagittal plane (256 mm × 256 mm) yielding a spatial resolution of 1 mm × 1 mm × 1.2 mm for the anatomical volume. Time to repetition (TR) for the anatomical scan was 2300 ms and time to echo (TE) was 2.99 ms. The whole brain fMRI scan employed an echo-planar imaging (EPI) sequence measuring the blood oxygenation level dependent (BOLD) signal. A total of 31 functional slices per volume were acquired for each subject, in each run. These slices, which were acquired in the transversal plane, interleaved and, in ascending order, were 3 mm thick, at an inplane resolution of 3 mm × 3 mm (matrix size 64 × 64) and in a field of view (FOV) of 192 mm × 192 mm, with a 0.75 mm gap between them in order to avoid cross talking. The spatial resolution of functional images was 3 mm × 3 mm × 3.75 mm. A complete scan of the whole brain was acquired in 2000 ms (TR); the flip angle was 75°, TE = 30 ms, and a total number of 550 volumes were acquired during one functional run. Each subject participated in two functional runs, for which we used the online automatic motion correction sequence, implemented prospective and retrospective by the scanner (MOCO series).
Sentences were presented visually on a projector placed at the head of the fMRI tunnel, which could be observed by the participants through a mirror placed on the head coil. A computer running E-prime (Schneider et al.,
BrainVoyager QX (Brain Innovation B.V., Maastricht, Netherlands) software was used for fMRI data preprocessing and analysis. The functional bi-dimensional images of every subject were preprocessed to correct for the difference in time slice acquisition (slice scan time correction). In addition to linear detrending, a high-pass filter of three cycles per time course (frequency domain) was applied to the corrected 2D slices. The functional series was then preprocessed to correct for possible motion artifacts in any plane of the tridimensional space and to ensure that movements in any plane did not exceed 3 mm. The motion correction was performed in BrainVoyager by an algorithm which aligns the subsequent functional volumes to the first one. Then, the six movement parameters (three translations, three rotations) are displayed graphically, thus allowing us to verify the magnitude of the movement during the scanning session. In our case, no subject moved their head more than 3 mm or 3° along or around any of the three spatial axes. As for co-registration and spatial normalization, we employed the standard procedure in BrainVoyager. To this end, the functional volume was first spatially aligned with the raw anatomical volume in two steps: (1) an initial alignment based on the information stored in the header of the DICOM file about the position of the slices relative to the center of the scanner; and (2) a fine tuning or rigid body alignment which was done manually by controlling the translation and rotation of the functional volume relative to the anatomical one (see Goebel et al.,
We used a rapid event-related block design to analyze our data. The time-course of each trial was separated in two periods, pre-verb and post-verb (Figure
In order to identify the neuronal substrates engaged specifically in processing indeterminate sentences in contrast with other sentence types, we employed a second analysis with the following procedure: (a) the areas identified in the first analysis for the indeterminate sentence type were defined as regions of interest (ROIs); and (b) in each of these ROIs we assessed the number of voxels for which the difference between predictors (post-verb > pre-verb) was significantly higher for the indeterminate than for other sentence types; for this analysis we employed the same statistical threshold (
The contrast of interest (post vs. pre-verb) indicates that each sentence type activates a large network of clusters in both hemispheres (for the full set of significantly activated regions per condition, see Table
Left hemisphere regions | Talairach coordinates | Volume (mm3) | Maximum |
Right hemisphere regions | Talairach coordinates | Volume (mm3) | Maximum |
||||
---|---|---|---|---|---|---|---|---|---|---|---|
Insula | −31 | 22 | 2 | 167 | 4.59 | Fusiform gyrus (BA 37) | 40 | −51 | −15 | 479 | 4.90 |
Postcentral gyrus (BA 40) | −29 | −35 | 54 | 119 | 4.32 | Lingual gyrus (BA 17) | 20 | −94 | −10 | 213 | 4.62 |
Precentral gyrus (BA 6) | −44 | −6 | 47 | 569 | 4.92 | Medial frontal gyrus (BA 6) | 1 | 0 | 50 | 2033 | 5.03 |
Sub-gyral (BA 20) | −38 | −16 | −18 | 162 | 4.83 | Middle occipital gyrus (BA 19) | 45 | −75 | −6 | 460 | 4.86 |
Thalamus (Medial | −7 | −17 | 8 | 2071 | 5.43 | Thalamus | 13 | −17 | 12 | 194 | 4.80 |
Dorsal Nucleus) | |||||||||||
Claustrum | −29 | 16 | 5 | 325 | 4.61 | Insula (BA 13) | 33 | 17 | 6 | 537 | 5.13 |
Inferior parietal lobule (BA 40) | −53 | −43 | 24 | 1193 | 5.23 | Middle occipital gyrus (BA 19) | 46 | −76 | −6 | 1073 | 6.34 |
Medial frontal gyrus (BA 6) | −5 | −4 | 54 | 179 | 4.50 | Superior frontal gyrus (BA 46) | 4 | 12 | 55 | 150 | 4.87 |
Middle frontal gyrus (BA 46) | −43 | 15 | 23 | 3060 | 5.59 | Superior parietal lobule (BA 7) | 30 | −55 | 43 | 205 | 4.58 |
Cingulate gyrus (BA 32) | −13 | 17 | 23 | 2311 | 7.31 | Cingulate gyrus (BA 24) | 11 | 12 | 31 | 2250 | 8.07 |
Inferior frontal gyrus (BA 45) | −39 | 21 | 14 | 1143 | 5.07 | Cingulate gyrus (BA 24) | 20 | −12 | 42 | 231 | 5.36 |
Inferior parietal lobule (BA 40) | −38 | −36 | 40 | 492 | 4.80 | Claustrum | 26 | 24 | 5 | 245 | 5.11 |
Middle temporal gyrus (BA 39) | −48 | −57 | 10 | 265 | 4.78 | Claustrum | 31 | 13 | 0 | 253 | 4.90 |
Precentral gyrus (BA 4) | −18 | −21 | 54 | 534 | 5.22 | Lentiform nucleus | 11 | 3 | 3 | 922 | 5.47 |
(Lat. Globus Pallidus) | |||||||||||
Precentral gyrus (BA 6) | −38 | −13 | 61 | 128 | 4.53 | Lingual gyrus (BA 17) | 17 | −89 | −4 | 258 | 4.59 |
Superior frontal gyrus (BA 6) | −1 | 5 | 63 | 2707 | 6.34 | Middle frontal gyrus (BA 6) | 37 | −5 | 50 | 142 | 4.57 |
Thalamus (Medial | −5 | −12 | 10 | 1963 | 5.52 | Superior temporal gyrus (BA 22) | 54 | −29 | 3 | 117 | 4.98 |
Dorsal Nucleus) | Supramarginal gyrus (BA 40) | 34 | −42 | 30 | 375 | 5.32 | |||||
Fusiform gyrus (BA 19) | −26 | −77 | −11 | 748 | 6.01 | Fusiform gyrus (BA 37) | 42 | −50 | −10 | 115 | 4.42 |
Inferior parietal lobule (BA 40) | −36 | −36 | 38 | 171 | 4.57 | Insula (BA 13) | 35 | 14 | 7 | 1467 | 5.46 |
Insula (BA 13) | −34 | 14 | 8 | 845 | 4.90 | Superior parietal lobule (BA 7) | 31 | −54 | 40 | 856 | 4.62 |
Middle temporal gyrus (BA 22) | −53 | −36 | 7 | 5396 | 7.25 | Superior temporal gyrus (BA 22) | 48 | −23 | 1 | 700 | 4.97 |
Middle temporal gyrus (BA 39) | −53 | −71 | 11 | 150 | 5.03 | Medial frontal gyrus (BA 6/BA 32) | 0 | 12 | 42 | 1584 | 5.97 |
Posterior cingulate (BA 23) | −1 | −31 | 23 | 170 | 4.97 | Thalamus (Medial Dorsal Nucleus) | 9 | −19 | 9 | 897 | 5.44 |
Precentral gyrus (BA 44) | −49 | 5 | 9 | 431 | 5.04 | ||||||
Precentral gyrus (BA 6) | −50 | −2 | 30 | 120 | 4.75 | ||||||
Superior frontal gyrus (BA 10) | −31 | 57 | 24 | 564 | 5.14 | ||||||
Superior parietal lobule (BA 7) | −23 | −67 | 41 | 367 | 4.74 | ||||||
Superior temporal gyrus (BA 38) | −54 | 7 | −7 | 512 | 6.14 | ||||||
Thalamus | −9 | −21 | 2 | 4288 | 7.08 | ||||||
Insula (BA 13) | −35 | 16 | 12 | 3214 | 6.61 | Fusiform gyrus (BA 37) | 42 | −52 | −16 | 739 | 7.63 |
Middle occipital gyrus (BA 18) | −28 | −79 | −10 | 126 | 4.33 | Inferior occipital gyrus (BA 19) | 45 | −73 | −5 | 568 | 5.51 |
Superior temporal gyrus (BA 21) | −52 | −17 | −3 | 235 | 4.97 | Insula (BA 13) | 31 | 18 | 11 | 592 | 5.16 |
Thalamus (Medial Dorsal Nucleus) | −8 | −14 | 8 | 143 | 4.56 | Precuneus (BA 7) | 22 | −56 | 34 | 1088 | 5.88 |
Thalamus (Ventral Lateral Nucleus) | 10 | −9 | 8 | 886 | 5.33 | ||||||
Insula (BA 13) | −35 | 14 | 12 | 381 | 4.77 | Angular gyrus (BA 39) | 32 | −61 | 33 | 159 | 4.82 |
Superior frontal gyrus (BA 6) | −1 | 21 | 61 | 403 | 5.52 | Insula (BA 13) | 34 | 16 | 11 | 1208 | 6.09 |
Thalamus | −7 | −30 | −2 | 142 | 4.29 | Medial frontal gyrus (BA 32) | 3 | 7 | 43 | 4818 | 6.99 |
Middle occipital gyrus (BA 19) | 49 | −75 | −8 | 168 | 4.54 |
In Figure
The general picture that emerges from this descriptive analysis is consistent with previous findings vis-à-vis the lateralization of linguistic and non-linguistic resources involved in sentence interpretation. In addition, these findings suggest that indeterminate sentences recruit computational resources that surpass those involved in the interpretation of both canonical and anomalous constructions, with both linguistic and non-linguistic processes contributing to interpretation. The novelty of our (post-verb > pre-verb) approach is that it isolates verb-object noun composition as the source of neuronal activity for each sentence type. This method specifically addresses how the different verb-noun combinations affect interpretive processes, permitting us to isolate neurological structures associated uniquely with indeterminacy.
Figure
In the R-STG, indeterminate sentences yielded statistically higher activation than preferred, syntactically anomalous and pragmatically anomalous sentence types. However, indeterminate sentences did not yield higher activation relative to the non-preferred and full-VP sentences. More specifically, from a total volume of 700 voxels that surpassed the statistical threshold in the R-STG, there were 74 voxels that were significantly more activated for indeterminate sentences compared to preferred sentences (average
In the R-IFG, indeterminate sentences also yielded statistically higher activation than preferred in 128 voxels (average
Indeterminate sentences yielded greater activation in L-IFG (Broca’s area) than syntactically and pragmatically anomalous conditions, but no differences were found at this ROI between indeterminate and the three other sentence types—preferred, non-preferred and full-VP. One possible interpretation of these results is that the two anomalous conditions engage less so the L-IFG because they require different forms of repair. In the case of the syntactically anomalous condition, it is possible that an early rejection of its ungrammatical verb-complement combination requires little effort from the parser. As for the pragmatically anomalous condition, the greater involvement of RH regions, as shown by our laterality indices, might suggest that repair of these sentences lies beyond Broca’s area.
A total of 169 voxels in the L-IFG showed more activation for the contrast post-verb > pre-verb in indeterminate relative to pragmatically anomalous sentences (average
Our final analysis focused on the spatial overlap of the activation maps for indeterminate, preferred and pragmatically anomalous sentences in the five prefrontal and temporal ROI (IFG and STG bilaterally and ACC; see Figure
This pattern of activation suggests that indeterminate sentences share properties of both canonical and pragmatically anomalous sentences. On the one hand, indeterminate and preferred constructions mutually activate the STG bilaterally, suggesting that the two sentence types may undergo a qualitatively similar semantic analysis, consistent with studies showing bilateral STG activation for canonical sentences (e.g., Friederici et al.,
The present study provides new evidence for the neurological underpinnings of the process of indeterminate sentence interpretation. We found that indeterminate sentences engage a wide network involving left, right, and medial-frontal regions of the brain. More specifically, compared to preferred sentences, indeterminate sentences required greater involvement of R-IFG (BAs 44, 45), bilaterally the STG (primarily BA 22) as well as the ACC (BAs 24, 32). In addition, our results also show that indeterminate sentences patterned with our pragmatically anomalous sentences (
Overall, what emerges from our study is that indeterminate sentences engage more areas than control sentences (see Table
The primary goal of our study was to obtain a general activation map for indeterminate sentences. Given the inconsistent results found in other studies (Pylkkänen and McElree,
Overall, our results show that indeterminate sentences recruit a vast network involving both temporal and frontal regions bilaterally. Although indeterminate sentences—consistent with linguistic processes—are clearly left-lateralized, the alleged mismatch between verb and NP complement in cases such as
While Husband et al.’s (
If indeed each of these regions participates in the resolution process, this challenges a view of indeterminacy that links the resolution uniquely to the L-IFG as Husband et al. (
Although our study was not designed specifically to replicate Pylkkänen and McElree’s (
In summary, the present fMRI results point to a neuroanatomical source of coercion effects compatible with a pragmatic view of indeterminate sentence interpretation (e.g., de Almeida,
It is important to note that pragmatic enrichment triggered by a syntactic gap (
If coercion effects are indeed
Thus far, no studies have provided conclusive evidence for coercion
A standing issue with regards to the semantics-pragmatics interface is the division of labor between computations that are linguistic, mandatory and those that are subject to extra-linguistic contextual factors. Coercion theory assumes that an alleged verb-noun mismatch requires extra semantic computations. The view we articulate—which is in fact compatible with that of others (e.g., Egg,
However, despite their analogs patterning overall, critical differences emerged in the activation of these two sentence types, with indeterminate sentences activating a much broader cortical network. This greater activation suggests that neurological resources involved in sentence interpretation are sensitive to differences between these sentence types. A sentence such as
Finally, two other contrasts are informative with regards to sentence processing mechanisms more generally. First, our syntactically and pragmatically anomalous sentences showed dissociative patterns of activation as indicated by the laterality index. Whereas pragmatically anomalous sentences showed greater RH than LH activation, syntactically anomalous sentences showed the reverse pattern. In addition, when compared to one another, the absolute volume of activation was greater in the LH for syntactically anomalous sentences and greater in the RH for pragmatically anomalous sentences. These differences in activation might reflect possibly different interpretation strategies that are triggered when the parser encounters syntactic vs. pragmatic violations. Specifically, the diminished activation in the RH for syntactically anomalous relative to pragmatically anomalous as well as indeterminate sentences, suggests the possibility that syntactic violations are rejected by the syntactic parser, whereas the other sentence types trigger more effortful repair processes. Second, perhaps the most unexpected result of our experiment was the spread of activation for full-VP sentences in the RH. In principle, full-VP sentences leave little open for further pragmatic interpretation, and accordingly we predicted that they would pattern with preferred sentences rather than indeterminate sentences in the RH. However, the opposite trend was observed. Notably, the post-verb > pre-verb contrast method we employed sets full-VP sentences apart from the other conditions specifically in terms of their semantic-compositional complexity. The combination between aspectual and event verbs in full-VP sentences may trigger other computations at the linguistic-cognitive interface. For instance,
Yet another alternative is that full-VP sentences put the focus on the main event verb—
On a final note, a major issue arising from the results of this study is how to account for the large clusters of LH activation associated with indeterminate sentences. We have assumed that the process of indeterminate sentence interpretation is obtained by pragmatic inferences, and in fact our prediction that RH and ACC structures would be more engaged in indeterminacy resolution was largely supported. We assume that the inferences that are triggered to resolve (or attempt to resolve) indeterminacy are computations over semantic/conceptual representations. They do not involve lexical items but their denotations, the concepts bearing on sentence meaning and beyond. It has been shown that the left temporal lobe is part of a “semantic network” which involves possibly categorically organized concepts in the temporal pole and extends posteriorly up to the supramarginal gyrus. As we discussed above, there is ample evidence for the role of the temporal poles in semantic processes (e.g., Damasio et al.,
Our second largest LH cluster for indeterminate sentences was at the thalamus. We are only beginning to understand the role that the thalamus plays in language comprehension and semantic processing, but there are indications that the thalamus is engaged in the detection of syntactic and semantic/pragmatic anomalies (Wahl et al.,
Overall, our results show that indeterminate sentences engage neurological substrates that go beyond those required to interpret determinate sentences—producing a hemodynamic response that is more compatible with a view that takes pragmatic inferences to be triggered beyond classical semantic composition. While nobody denies that inferential-pragmatic processes might be a consequence of earlier syntactic and semantic computations, the crux of the matter is what these syntactic and semantic computations yield. The coercion theory assumes that much of the process of indeterminate sentence interpretation should be resolved by earlier, mostly linguistic processes of type-shifting and semantic interpolation—with reduced pragmatic activity compared to determinate sentences. Our view, in contrast, is that the earlier linguistic computations leave indeterminate sentences unresolved, with a greater role played by pragmatic computations in search of what is intended.
Clearly, our data—as those of other neuroimating studies—cannot distinguish between hypotheses concerning the nature of indeterminate resolution without an understanding of the actual computations performed by activated neuronal tissue. It has proven difficult to reconcile neuroimaging and psycholinguistic data with linguistic-theoretical constructs aiming to understand how language representations and processes are implemented in the brain. In the case of neuroimaging studies, in particular, it has often been the case that neuroanatomical correlates of language processing have been hard to pinpoint due to numerous methodological variables (see, e.g., Indefrey and Cutler,
Concordia University Human Research Ethics Committee (UHREC), Comite d’éthique de la Recherche (CER-IUGM). All participants gave informed consent, both for the behavioral normative task and for participation in the fMRI experiment.
RGA is the main author of the manuscript and the principal responsible for the conception and design of the study, theoretical background and general discussion; LR led the acquisition, analysis, and writing of the norming study, and contributed to fMRI data acquisition and analysis, and to manuscript editing; CM contributed to the design of the study, the preparation of materials, data acquisition and manuscript editing; OL led the analysis and reporting of the fMRI data, and contributed to manuscript editing; VDD contributed to the conception of the work, design and materials; GJ contributed to the design of materials and manuscript editing; BG contributed to the theoretical background and manuscript editing.
This study was supported by grants from the Social Sciences and Humanities Research Council of Canada (SSHRC) and the Natural Sciences and Engineering Research Council of Canada (NSERC) to RGA and by a Major Collaborative Research Initiative grant from SSHRC to Gary Libben (director), Gonia Jarema, Eva Kehayia, Bruce Derwing, Lori Buchanan and RGA.
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.
We thank the attendants of the Architectures and Mechanisms of Language Processing conference in Barcelona (2009), where preliminary data reported in the present article were presented. We are also indebted to Laura Evans, Brigitte Stemmer, and Karin Stromswold for suggestions and corrections to an earlier version of the present manuscript.
The Supplementary Material for this article can be found online at:
1A thorough review of the numerous theoretical positions on how semantic coercion, type coercion, or type shifting work is beyond the scope of the present article (see e.g., Partee,
2We restrict our review to studies that have employed the same kinds of sentences as ours. Although other cognitive neuroscience studies were also concerned with the general phenomenon of coercion, they either employed other sentence types—which might involve different linguistic processes (e.g., Pylkkänen et al.,
3It should be noted that some studies have shown equal involvement of both hemispheres in metaphor comprehension (Rapp et al.,
4We refer to these sentences as “pragmatically anomalous” because, although they contain what are regarded as
5This alpha level represents the adjusted threshold of statistical significance for pairwise contrasts that yield a 0.05 family-wise type I error rate, following the guidelines outlined in Kline (