Publications

In Press
Sharpe, V., Weber, K., & Kuperberg, G. R. (In Press). Impairments in probabilistic prediction and Bayesian learning can explain reduced neural semantic priming in schizophrenia. Schizophrenia Bulletin.Abstract

It has been proposed that abnormalities in probabilistic prediction and dynamic belief updating explain multiple features of schizophrenia. Here, we used EEG to ask whether these abnormalities can account for the well-established reduction in semantic priming observed in schizophrenia under non-automatic conditions. We isolated predictive contributions to the neural semantic priming effect by manipulating the prime’s predictive validity and minimizing retroactive semantic matching mechanisms. We additionally examined the link between prediction and learning using a Bayesian model that probed dynamic belief updating as participants adapted to the increase in predictive validity. We found that patients were less likely than healthy controls to use the prime to predictively facilitate semantic processing on the target, resulting in a reduced N400 effect. Moreover, the trial-by-trial output of our Bayesian computational model explained between-group differences in trial-by-trial N400 amplitudes as participants transitioned from conditions of lower to higher predictive validity. These findings suggest that, compared to healthy controls, people with schizophrenia are less able to mobilize predictive mechanisms to facilitate processing at the earliest stages of accessing the meanings of incoming words. This deficit may be linked to a failure to adapt to changes in the broader environment. This reciprocal relationship between impairments in probabilistic prediction and Bayesian learning/adaptation may drive a vicious cycle that maintains cognitive disturbances in schizophrenia.

Full Text
2021
Brothers, T., & Kuperberg, G. R. (2021). Word predictability effects are linear, not logarithmic: Implications for probabilistic models of sentence comprehension. Journal of Memory and Language , 116, 1041742. Full Text
2020
Kuperberg, G. R. (2020). Tea with milk? A Hierarchical Generative Framework of Sequential Event Comprehension. Topics in Cognitive Science , 1-43. Full Text
Wang, L., Wlotko, E., Alexander, E., Schoot, L., Kim, M., Warnke, L., & Kuperberg, G. (2020). Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG Representational Similarity Analysis. Journal of Neuroscience , 40 (16), 3278-3291. Full TextAbstract

It has been proposed that people can generate probabilistic predictions at multiple levels of representation during language comprehension. We used magnetoencephalography (MEG) and electroencephalography (EEG), in combination with representational similarity analysis, to seek neural evidence for the prediction of animacy features. In two studies, MEG and EEG activity was measured as human participants (both sexes) read three-sentence scenarios. Verbs in the final sentences constrained for either animate or inanimate semantic features of upcoming nouns, and the broader discourse context constrained for either a specific noun or for multiple nouns belonging to the same animacy category. We quantified the similarity between spatial patterns of brain activity following the verbs until just before the presentation of the nouns. The MEG and EEG datasets revealed converging evidence that the similarity between spatial patterns of neural activity following animate-constraining verbs was greater than following inanimate-constraining verbs. This effect could not be explained by lexical-semantic processing of the verbs themselves. We therefore suggest that it reflected the inherent difference in the semantic similarity structure of the predicted animate and inanimate nouns. Moreover, the effect was present regardless of whether a specific word could be predicted, providing strong evidence for the prediction of coarse-grained semantic features that goes beyond the prediction of individual words.

Brothers, T., Wlotko, E. W., Warnke, L., & Kuperberg, G. R. (2020). Going the extra mile: Effects of discourse context on two late positivities during language comprehension. Neurobiology of Language , 1 (1), 135-160. Full TextAbstract
During language comprehension, online neural processing is strongly influenced by the constraints of the prior context. While the N400 ERP response (300-500ms) is known to be sensitive to a word’s semantic predictability, less is known about a set of late positive-going ERP responses (600-1000ms) that can be elicited when an incoming word violates strong predictions about upcoming content (late frontal positivity) or about what is possible given the prior context (late posterior positivity/P600). Across three experiments, we systematically manipulated the length of the prior context and the source of lexical constraint to determine their influence on comprehenders’ online neural responses to these two types of prediction violations. In Experiment 1, within minimal contexts, both lexical prediction violations and semantically anomalous words produced a larger N400 than expected continuations (James unlocked the door/laptop/gardener), but no late positive effects were observed. Critically, the late posterior positivity/P600 to semantic anomalies appeared when these same sentences were embedded within longer discourse contexts (Experiment 2a), and the late frontal positivity appeared to lexical prediction violations when the preceding context was rich and globally constraining (Experiment 2b). We interpret these findings within a hierarchical generative framework of language comprehension. This framework highlights the role of comprehension goals and broader linguistic context, and how these factors influence both top-down prediction and the decision to update or reanalyze the prior context when these predictions are violated.
Supplementary Figures
Kuperberg, G. R., Brothers, T., & Wlotko, E. (2020). A Tale of Two Positivities and the N400: Distinct neural signatures are evoked by confirmed and violated predictions at different levels of representation. Journal of Cognitive Neuroscience , 32 (1), 12-35. Full TextAbstract
It has been proposed that hierarchical prediction is a fundamental computational principle underlying neurocognitive processing. Here we ask whether the brain engages distinct neurocognitive mechanisms in response to inputs that fulfill versus violate strong predictions at different levels of representation during language comprehension. Participants read three-sentence scenarios in which the third sentence constrained for a broad event structure, e.g. {Agent caution animate-Patient}. High constraint contexts additionally constrained for a specific event/lexical item, e.g. a two-sentence context about a beach, lifeguards and sharks constrained for the event, {Lifeguards cautioned Swimmers} and the specific lexical item, “swimmers”. Low constraint contexts did not constrain for any specific event/lexical item. We measured ERPs on critical nouns that fulfilled and/or violated each of these constraints. We found clear, dissociable effects to fulfilled semantic predictions (a reduced N400), to event/lexical prediction violations (an increased late frontal positivity), and to event structure/animacy prediction violations (an increased late posterior positivity/P600). We argue that the late frontal positivity reflects a large change in activity associated with successfully updating the comprehender’s current situation model with new unpredicted information. We suggest that the late posterior positivity/P600 is triggered when the comprehender detects a conflict between the input and her model of the communicator and communicative environment. This leads to an initial failure to incorporate the unpredicted input into the situation model, which may be followed by second-pass attempts to make sense of the discourse through reanalysis, repair, or reinterpretation. Together, these findings provide strong evidence that confirmed and violated predictions at different levels of representation manifest as distinct spatiotemporal neural signatures.
Supplementary Materials
Fields, E. C., & Kuperberg, G. R. (2020). Having your cake and eating it too: Flexibility and power with mass univariate statistics for ERP data. Psychophysiology , 57 (2), e13468. Full TextAbstract
Event-related potential (ERP) studies produce large spatiotemporal datasets. These rich datasets are key to the ability of ERP to help us understand cognition and neural processes. However, they can also present a massive multiple comparisons problem, leading to a high Type I error rate. Standard approaches to statistical analysis, which average over time windows and regions of interest, do not always control for Type I error, and their inflexibility can lead to low power to detect true effects. Mass univariate approaches offer an alternative, but have thus far been seen as appropriate only for exploratory analysis and only applicable to simple designs. Here we present new simulation studies showing that permutation-based mass univariate tests can be employed with complex factorial designs. Most importantly, we show that mass univariate approaches provide slightly greater power than traditional spatiotemporal averaging approaches when strong a priori time windows and spatial regions are used, and that power decreases only modestly when more exploratory spatiotemporal parameters are used. We argue that mass univariate approaches are preferable to traditional analysis approaches for most ERP studies.
Supplementary Materials
2019
Fields, E., Weber, K., Stillerman, B., Delaney-Busch, N., & Kuperberg, G. R. (2019). Functional MRI reveals evidence of a self-positivity bias in the medial prefrontal cortex during the comprehension of social vignettes. Social Cognitive and Affective Neuroscience , 14 (6), 613-621. Full TextAbstract

A large literature in social neuroscience has associated the medial prefrontal cortex (mPFC) with the processing of self-related information. However, only recently have social neuroscience studies begun to consider the large behavioral literature showing a strong self-positivity bias, and these studies have mostly focused on its correlates during self-related judgments and decision making. We carried out a functional MRI (fMRI) study to ask whether the mPFC would show effects of the self-positivity bias in a paradigm that probed participants’ self-concept without any requirement of explicit self-judgment. We presented social vignettes that were either self-relevant or non-self-relevant with a neutral, positive, or negative outcome described in the second sentence. In previous work using event-related potentials, this paradigm has shown evidence of a self-positivity bias that influences early stages of semantically processing incoming stimuli. In the present fMRI study, we found evidence for this bias within the mPFC: an interaction between self-relevance and valence, with only positive scenarios showing a self vs other effect within the mPFC. We suggest that the mPFC may play a role in maintaining a positively-biased self-concept and discuss the implications of these findings for the social neuroscience of the self and the role of the mPFC.

Supplementary Materials
Shetreet, E., Alexander, E. J., Romoli, J., Chierchia, G., & Kuperberg, G. R. (2019). What we know about knowing: Presuppositions generated by factive verbs influence downstream neural processing. Cognition , 184, 96-106. Full TextAbstract
Presuppositions convey information that comprehenders assume to be true, even when it is tangential to the communicator’s main message. For example, a class of verbs called ‘factives’ (e.g. realize, know) trigger the presupposition that the events or states conveyed by their sentential complements are true. In contrast, non-factive verbs (e.g. think, believe) do not trigger this presupposition. We asked whether, during language comprehension, presuppositions triggered by factive verbs are encoded within the comprehender’s discourse model, with neural consequences if violated by later bottom-up inputs. Using event-related potentials (ERPs), we examined neural activity to words that were either consistent or inconsistent with events/states conveyed by the complements of factive versus non-factive verbs while comprehenders read and actively monitored the coherence of short discourse scenarios. We focused on the modulation of a posteriorly-distributed late positivity or P600. This ERP component is produced when comprehenders constrain their discourse model such that it restricts predictions only to event structures that are compatible with this model, and new input violates these event structure predictions. Between 500-700ms, we observed a larger amplitude late posterior positivity/P600 on words that were inconsistent (versus consistent) with the events/states conveyed by the complements of factive verbs. No such effect was observed following non-factive verbs. These findings suggest that, during active discourse comprehension, the presuppositions triggered by factive verbs are encoded and maintained within the comprehender’s discourse model. Downstream input that is inconsistent with these presuppositions violates event structure predictions and conflicts with this prior model, producing the late posterior positivity/P600.
Supplementary Materials
Kuperberg, G. R., Weber, K., Delaney-Busch, N., Ustine, C., Stillerman, B., Hamalainen, M., & Lau, E. (2019). Multimodal neuroimaging evidence for looser lexico-semantic networks in schizophrenia: Evidence from masked indirect semantic priming. Neuropsychologia , 124, 337-349. Full TextAbstract
It has been hypothesized that schizophrenia is characterized by overly broad automatic activity within lexico-semantic networks. We used two complementary neuroimaging techniques, Magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI), in combination with a highly automatic indirect semantic priming paradigm, to spatiotemporally localize this abnormality in the brain. Eighteen people with schizophrenia and 20 demographically-matched control participants viewed target words (“bell”) preceded by directly related (“church”), indirectly related (“priest”), or unrelated (“pants”) prime words in MEG and fMRI sessions. To minimize top-down processing, the prime was masked, the target appeared only 140ms after prime onset, and participants simply monitored for words within a particular semantic category that appeared in filler trials. Both techniques revealed a significantly larger automatic indirect priming effect in people with schizophrenia than in control participants. MEG temporally localized this enhanced effect to the N400 time window (300-500ms) — the critical stage of accessing meaning from words. fMRI spatially localized the effect to the left temporal fusiform cortex, which plays a role in mapping of orthographic word-form on to meaning. There was no evidence of an enhanced automatic direct semantic priming effect in the schizophrenia group. These findings provide converging neural evidence for abnormally broad highly automatic lexico-semantic activity in schizophrenia. We argue that, rather than arising from an unconstrained spread of automatic activation across semantic memory, this broader automatic lexico-semantic activity stems from looser connections between the form and meaning of words.
Supplementary Materials
Delaney-Busch, N., Morgan, E., Lau, E., & Kuperberg, G. R. (2019). Neural evidence for Bayesian trial-by-trial adaptation on the N400 during semantic priming. Cognition , 187, 10-20. Full TextAbstract

When semantic information is activated by a context prior to new bottom-up input (i.e. when a word is predicted), semantic processing of that incoming word is typically facilitated, attenuating the amplitude of the N400 event related potential (ERP) – a direct neural measure of semantic processing. N400 modulation is observed even when the context is a single semantically related “prime” word. This so-called “N400 semantic priming effect” is sensitive to the probability of encountering a related prime-target pair within an experimental block, suggesting that participants may be adapting the strength of their predictions to the predictive validity of their broader experimental environment. We formalize this adaptation using a Bayesian learning model that estimates and updates the probability of encountering a related versus an unrelated prime-target pair on each successive trial. We found that our model’s trial-by-trial estimates of target word probability accounted for significant variance in the amplitude of the N400 evoked by target words. These findings suggest that Bayesian principles contribute to how comprehenders adapt their semantic predictions to the statistical structure of their broader environment, with implications for the functional significance of the N400 component and the predictive nature of language processing.

2018
Wang, L., Kuperberg, G. R., & Jensen, O. (2018). Specific lexico-semantic predictions are associated with unique spatial and temporal patterns of neural activity. eLife , 7 e39061. Full textAbstract
We used Magnetoencephalography (MEG) in combination with Representational Similarity Analysis to probe neural activity associated with distinct, item-specific lexico-semantic predictions during language comprehension. MEG activity was measured as participants read highly constraining sentences in which the final words could be predicted. Before the onset of the predicted words, both the spatial and temporal patterns of brain activity were more similar when the same words were predicted than when different words were predicted. The temporal patterns localized to the left inferior and medial temporal lobe. These findings provide evidence that unique spatial and temporal patterns of neural activity are associated with item-specific lexico-semantic predictions. We suggest that the unique spatial patterns reflected the prediction of spatially distributed semantic features associated with the predicted word, and that the left inferior/medial temporal lobe played a role in temporally “binding” these features, giving rise to unique lexico-semantic predictions.
Supplementary Material: Figures Supplementary Materials: Author Response Supplementary Material: Chinese/ English Stimuli
Rabagliati, H., Delaney-Busch, N., Snedeker, J., & Kuperberg, G. R. (2018). Spared bottom-up but impaired top-down effects during naturalistic language processing in schizophrenia: Evidence from the visual world paradigm. Psychological Medicine , 49 (58), 1335-1345. Full TextAbstract

Background

People with schizophrenia process language in unusual ways, but the causes of these abnormalities are unclear. In particular, it has proven difficult to empirically disentangle explanations based on impairments in the top-down processing of higher-level information from those based on the bottom-up processing of lower-level information.

 

Methods

To distinguish these accounts, we used visual world eye-tracking, a paradigm that measures spoken language processing during real-world interactions. Participants listened to and then acted out syntactically ambiguous spoken instructions (e.g., “tickle the frog with the feather”, which could either specify how to tickle a frog, or which frog to tickle). We contrasted how 24 people with schizophrenia and 24 demographically-matched controls used two types of lower-level information (prosody and lexical representations) and two types of higher-level information (pragmatic and discourse-level representations) to resolve the ambiguous meanings of these instructions. Eye-tracking allowed us to assess how participants arrived at their interpretation in real time, while recordings of participants’ actions measured how they ultimately interpreted the instructions.

 

Results

We found a striking dissociation in participants’ eye movements: the two groups were similarly adept at using lower-level information to immediately constrain their interpretations of the instructions, but only controls showed evidence of fast top-down use of higher-level information. People with schizophrenia, nonetheless, did eventually reach the same interpretations as controls.

 

Conclusions

These data suggest that language abnormalities in schizophrenia partially result from a failure to use higher-level information in a top-down fashion, to constrain the interpretation of language as it unfolds in real time.
Supplementary Materials
Kuperberg, G. R., Delaney-Busch, N., Fanucci, K., & Blackford, T. (2018). Priming Production: Neural evidence for enhanced automatic semantic activity immediately preceding language production in schizophrenia. NeuroImage:Clinical , 18, 74-85. Full TextAbstract

Introduction: Lexico-semantic disturbances are considered central to schizophrenia. Clinically, their clearest manifestation is in language production. However, most studies probing their underlying mechanisms have used comprehension or categorization tasks. Here, we probed automatic semantic activity prior to language production in schizophrenia using event-related potentials (ERPs).

Methods: 19 people with schizophrenia and 16 demographically-matched healthy controls named target pictures that were very quickly preceded by masked prime words. To probe automatic semantic activity prior to production, we measured the N400 ERP component evoked by these targets. To determine the origin of any automatic semantic abnormalities, we manipulated the type of relationship between prime and target such that they overlapped in (a) their semantic features (semantically related, e.g. “cake” preceding a <picture of a pie>, (b) their initial phonemes (phonemically related, e.g. “stomach” preceding a <picture of a starfish>), or (c) both their semantic features and their orthographic/phonological word form (identity related, e.g. “socks” preceding a <picture of socks>). For each of these three types of relationship, the same targets were paired with unrelated prime words (counterbalanced across lists). We contrasted ERPs and naming times to each type of related target with its corresponding unrelated target. 

Results: People with schizophrenia showed abnormal N400 modulation prior to naming identity related (versus unrelated) targets: whereas healthy control participants produced a smaller amplitude N400 to identity related than unrelated targets, patients showed the opposite pattern, producing a larger N400 to identity related than unrelated targets. This abnormality was specific to the identity related targets. Just like healthy control participants, people with schizophrenia produced a smaller N400 to semantically related than to unrelated targets, and showed no difference in the N400 evoked by phonemically related and unrelated targets. There were no differences between the two groups in the pattern of naming times across conditions.

Conclusion: People with schizophrenia can show abnormal neural activity associated with automatic semantic processing prior to language production. The specificity of this abnormality to the identity related targets suggests that that, rather than arising from abnormalities of either semantic features or lexical form alone, it may stem from disruptions of mappings (connections) between the meanings of words and their form.

Supplementary Materials
Kuperberg, G. R., Ditman, T., & Choi Perrachione, A. (2018). When proactivity fails: An electrophysiological study of establishing reference in schizophrenia. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging , 3 (1), 77-87. Full TextAbstract

Background: Schizophrenia is characterized by abnormalities in referential communication, which may be linked to more general deficits in proactive cognitive control. We used event-related potentials (ERPs) to probe the timing and nature of the neural mechanisms engaged as people with schizophrenia linked pronouns to their preceding referents during word-by-word sentence comprehension.

Methods: We measured ERPs to pronouns in two-clause sentences from 16 people with schizophrenia and 20 demographically-matched control participants. Our design crossed the number of potential referents (1-referent, 2-referent) with whether the pronoun matched the gender of its preceding referent(s) (matching, mismatching). This gave rise to four conditions: (1) 1-referent matching (“…Edward took courses in accounting but he…”), (2) 2-referent matching (“…Edward and Phillip took courses but he…”), (3) 1-referent mismatching (“…Edward took courses in accounting but she…”), and (4) 2-referent mismatching (“…Edward and Phillip took courses but she…”).

Results: Consistent with previous findings, healthy controls produced a larger left anteriorly-distributed negativity between 400-600ms to 2-referent matching than to 1-referent matching pronouns (the “Nref effect”). In contrast, people with schizophrenia produced a larger centro-posterior positivity effect between 600-800ms. Both patient and control groups produced a larger positivity between 400-800ms to mismatching than to matching pronouns.

Conclusions: These findings suggest that proactive mechanisms of referential processing, reflected by the Nref effect, are impaired in schizophrenia, while reactive mechanisms, reflected by the positivity effects, are relatively spared. Indeed, patients may compensate for proactive deficits by retro-actively engaging with context to influence the processing of inputs at a later stage of analysis.

Supplementary Materials
2017
Yan, S., Kuperberg, G. R., & Jaeger, T. F. (2017). Prediction (or not) during language processing. A commentary on Nieuwland et al. (2017) and Delong et al. (2005). bioRxiv. Full textAbstract
The extent to which language processing involves prediction of upcoming inputs remains a question of ongoing debate. One important data point comes from DeLong et al. (2005) who reported that an N400-like event-related potential correlated with a probabilistic index of upcoming input. This result is often cited as evidence for gradient probabilistic prediction of form and/or semantics, prior to the bottom-up input becoming available. However, a recent multi-lab study reports a failure to find these effects (Nieuwland et al., 2017). We review the evidence from both studies, including differences in the design and analysis approach between them. Building on over a decade of research on prediction since DeLong et al. (2005)'s original study, we also begin to spell out the computational nature of predictive processes that one might expect to correlate with ERPs that are evoked by a functional element whose form is dependent on an upcoming predicted word. For paradigms with this type of design, we propose an index of anticipatory processing, Bayesian surprise, and apply it to the updating of semantic predictions. We motivate this index both theoretically and empirically. We show that, for studies of the type discussed here, Bayesian surprise can be closely approximated by another, more easily estimated information theoretic index, the surprisal (or Shannon information) of the input. We re-analyze the data from Nieuwland and colleagues using surprisal rather than raw probabilities as an index of prediction. We find that surprisal is gradiently correlated with the amplitude of the N400, even in the data shared by Nieuwland and colleagues. Taken together, our review suggests that the evidence from both studies is compatible with anticipatory semantic processing. We do, however, emphasize the need for future studies to further clarify the nature and degree of form prediction, as well as its neural signatures, during language comprehension.
2016
Delaney-Busch, N., Wilkie, G., & Kuperberg, G. R. (2016). Vivid: How valence and arousal influence word processing under different task demands. Cognitive, Affective, & Behavioral Neuroscience , 16 (3), 413-432. Full textAbstract
In this study, we used event-related potentials to examine how different dimensions of emotion—valence and arousal—influence different stages of word processing under different task demands. In two experiments, two groups of participants viewed the same single emotional and neutral words while carrying out different tasks. In both experiments, valence (pleasant, unpleasant, and neutral) was fully crossed with arousal (high and low). We found that the task made a substantial contribution to how valence and arousal modulated the late positive complex (LPC), which is thought to reflect sustained evaluative processing (particularly of emotional stimuli). When participants performed a semantic categorization task in which emotion was not directly relevant to task performance, the LPC showed a larger amplitude for high-arousal than for low-arousal words, but no effect of valence. In contrast, when participants performed an overt valence categorization task, the LPC showed a large effect of valence (with unpleasant words eliciting the largest positivity), but no effect of arousal. These data show not only that valence and arousal act independently to influence word processing, but that their relative contributions to prolonged evaluative neural processes are strongly influenced by the situational demands (and by individual differences, as revealed in a subsequent analysis of subjective judgments).
Supplementary Materials
Kuperberg, G. R. (2016). Separate streams or probabilistic inference? What the N400 can tell us about the comprehension of events. Language, Cognition and Neuroscience , 31 (5), 602-616. Full text Abstract

Since the early 2000s, several ERP studies have challenged the assumption that we always use syntactic contextual information to influence semantic processing of incoming words, as reflected by the N400 component. One approach for explaining these findings is to posit distinct semantic and syntactic processing mechanisms, each with distinct time courses. While this approach can explain specific datasets, it cannot account for the wider body of findings. I propose an alternative explanation: a dynamic generative framework in which our goal is to infer the underlying event that best explains the set of inputs encountered at any given time. Within this framework, combinations of semantic and syntactic cues with varying reliabilities are used as evidence to weight probabilistic hypotheses about this event. I further argue that the computational principles of this framework can be extended to understand how we infer situation models during discourse comprehension, and intended messages during spoken communication.

Kuperberg, G. R., & Jaeger, F. T. (2016). What do we mean by prediction in language comprehension? Language, Cognition and Neuroscience , 31 (1), 32-59. Full textAbstract

We consider several key aspects of prediction in language comprehension: its computational nature, the representational level(s) at which we predict, whether we use higher level representations to predictively pre-activate lower level representations, and whether we 'commit' in any way to our predictions, beyond pre-activation. We argue that the bulk of behavioral and neural evidence suggests that we predict probabilistically and at multiple levels and grains of representation. We also argue that we can, in principle, use higher level inferences to predictively pre-activate information at multiple lower representational levels. We also suggest that the degree and level of predictive pre-activation might be a function of the expected utility of prediction, which, in turn, may depend on comprehenders' goals and their estimates of the relative reliability of their prior knowledge and the bottom-up input. Finally, we argue that all these properties of language understanding can be naturally explained and productively explored within a multi-representational hierarchical actively generative architecture whose goal is to infer the message intended by the producer, and in which predictions play a crucial role in explaining the bottom-up input.

Weber, K., Lau, E. F., Stillerman, B., & Kuperberg, G. R. (2016). The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing. PLoS One , 11 (3), e0148637. Full textAbstract

Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the statistical structure of the wider environmental context. Together, these findings highlight close links between the networks mediating semantic prediction, executive function and learning, giving new insights into how our brains are able to flexibly adapt to our environment.

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