Papers

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.

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.

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).

Although there is broad agreement that top-down expectations can facilitate lexical-semantic processing, the mechanisms driving these effects are still unclear. In particular, while previous electroencephalography (EEG) research has demonstrated a reduction in the N400 response to words in a supportive context, it is often challenging to dissociate facilitation due to bottom-up spreading activation from facilitation due to top-down expectations. The goal of the current study was to specifically determine the cortical areas associated with facilitation due to top-down prediction, using magnetoencephalography (MEG) recordings supplemented by EEG and functional magnetic resonance imaging (fMRI) in a semantic priming paradigm. In order to modulate expectation processes while holding context constant, we manipulated the proportion of related pairs across 2 blocks (10 and 50% related). Event-related potential results demonstrated a larger N400 reduction when a related word was predicted, and MEG source localization of activity in this time-window (350-450 ms) localized the differential responses to left anterior temporal cortex. fMRI data from the same participants support the MEG localization, showing contextual facilitation in left anterior superior temporal gyrus for the high expectation block only. Together, these results provide strong evidence that facilitatory effects of lexical-semantic prediction on the electrophysiological response 350-450 ms postonset reflect modulation of activity in left anterior temporal cortex.

Language and thought dysfunction are central to the schizophrenia syndrome. They are evident in the major symptoms of psychosis itself, particularly as disorganized language output (positive thought disorder) and auditory verbal hallucinations (AVHs), and they also manifest as abnormalities in both high-level semantic and contextual processing and low-level perception. However, the literatures characterizing these abnormalities have largely been separate and have sometimes provided mutually exclusive accounts of aberrant language in schizophrenia. In this review, we propose that recent generative probabilistic frameworks of language processing can provide crucial insights that link these four lines of research. We first outline neural and cognitive evidence that real-time language comprehension and production normally involve internal generative circuits that propagate probabilistic predictions to perceptual cortices - predictions that are incrementally updated based on prediction error signals as new inputs are encountered. We then explain how disruptions to these circuits may compromise communicative abilities in schizophrenia by reducing the efficiency and robustness of both high-level language processing and low-level speech perception. We also argue that such disruptions may contribute to the phenomenology of thought-disordered speech and false perceptual inferences in the language system (i.e., AVHs). This perspective suggests a number of productive avenues for future research that may elucidate not only the mechanisms of language abnormalities in schizophrenia, but also promising directions for cognitive rehabilitation.

A large body of social psychological research suggests that we think quite positively of ourselves, often unrealistically so. Research on this ’self-positivity bias’ has relied mainly on self-report and behavioral measures, but these can suffer from a number of problems including confounds that arise from the desire to present oneself well. What has not been clearly assessed is whether the self-positivity bias influences the processing of incoming information as it unfolds in real time. In this study, we used event-related potentials to address this question. Participants read two-sentence social vignettes that were either self- or other-relevant. Pleasant words in self-relevant contexts evoked a smaller negativity between 300 and 500 ms (the N400 time window) than the same words in other-relevant contexts, suggesting that comprehenders were more likely to expect positive information when a scenario referred to themselves. This finding indicates that the self-positivity bias is available online, acting as a general schema that directly influences real-time comprehension.

In two event-related potential experiments, we asked whether comprehenders used the concessive connective, even so, to predict upcoming events. Participants read coherent and incoherent scenarios, with and without even so, e.g. ‘Elizabeth had a history exam on Monday. She took the test and aced/failed it. (Even so), she went home and celebrated wildly’, as they rated coherence (Experiment 1) or simply answered intermittent comprehension questions (Experiment 2). The semantic function of even so was used to reverse real-world knowledge predictions, leading to an attenuated N400 to coherent versus incoherent target words (‘celebrated’). Moreover, its pragmatic communicative function enhanced predictive processing, leading to more N400 attenuation to coherent targets in scenarios with than without even so. This benefit however, did not come for free: the detection of failed event predictions triggered a later posterior positivity and/or an anterior negativity effect, and

Constituent structure has long been established as a central feature of human language. Analogous to how syntax organizes words in sentences, a narrative grammar organizes sequential images into hierarchic constituents. Here we show that the brain draws upon this constituent structure to comprehend wordless visual narratives. We recorded neural responses as participants viewed sequences of visual images (comics strips) in which blank images either disrupted individual narrative constituents or fell at natural constituent boundaries. A disruption of either the first or the second narrative constituent produced a left-lateralized anterior negativity effect between 500 and 700ms. Disruption of the second constituent also elicited a posteriorly-distributed positivity (P600) effect. These neural responses are similar to those associated with structural violations in language and music. These findings provide evidence that comprehenders use a narrative structure to comprehend visual sequences and that the brain engages similar neurocognitive mechanisms to build structure across multiple domains.

We used event-related potentials (ERPs) to investigate the neurocognitive mechanisms associated with processing light verb constructions such as “give a kiss”. These constructions consist of a semantically underspecified light verb (“give”) and an event nominal that contributes most of the meaning and also activates an argument structure of its own (“kiss”). This creates a mismatch between the syntactic constituents and the semantic roles of a sentence. Native speakers read German verb-final sentences that contained light verb constructions (e.g., “Julius gave Anne a kiss”), non-light constructions (e.g., “Julius gave Anne a rose”), and semantically anomalous constructions (e.g., *“Julius gave Anne a conversation”). ERPs were measured at the critical verb, which appeared after all its arguments. Compared to non-light constructions, the light verb constructions evoked a widely distributed, frontally focused, sustained negative-going effect between 500 and 900 ms after verb onset. We interpret this effect as reflecting working memory costs associated with complex semantic processes that establish a shared argument structure in the light verb constructions.