Generalized event knowledge activation during online sentence comprehension

Verb Vocabulary Supports Event Probability Use in Developmental Language Disorder

PURPOSE

Children with developmental language disorder (DLD) tend to interpret noncanonical sentences like passives using event probability (EP) information regardless of structure (e.g., by interpreting "The dog was chased by the squirrel" as "The dog chased the squirrel"). Verbs are a major source of EP information in adults and children with typical development (TD), who know that "chase" implies an unequal relationship among participants. Individuals with DLD have poor verb knowledge and verb-based sentence processing. Yet, they also appear to rely more on EP information than their peers. This paradox raises two questions: (a) How do children with DLD use verb-based EP information alongside other information in online passive sentence interpretation? (b) How does verb vocabulary knowledge support EP information use?

METHOD

We created novel EP biases by showing animations of agents with consistent action tendencies (e.g., clumsy vs. helpful actions). We then used eye tracking to examine how this EP information was used during online passive sentence processing. Participants were 4- to 5-year-old children with DLD (n = 20) and same-age peers with TD (n = 20).

RESULTS

In Experiment 1, children with DLD quickly integrated verb-based EP information with morphosyntax close to the verb but failed to do so with distant morphosyntax. In Experiment 2, the quality of children's sentence-specific verb vocabulary knowledge was positively associated with the use of EP information in both groups.

CONCLUSION

Depending on the morphosyntactic context, children with DLD and TD used EP information differently, but verb vocabulary knowledge aided its use.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25491805.

Finding structure during incremental speech comprehension

A core aspect of human speech comprehension is the ability to incrementally integrate consecutive words into a structured and coherent interpretation, aligning with the speaker's intended meaning. This rapid process is subject to multidimensional probabilistic constraints, including both linguistic knowledge and non-linguistic information within specific contexts, and it is their interpretative coherence that drives successful comprehension. To study the neural substrates of this process, we extract word-by-word measures of sentential structure from BERT, a deep language model, which effectively approximates the coherent outcomes of the dynamic interplay among various types of constraints. Using representational similarity analysis, we tested BERT parse depths and relevant corpus-based measures against the spatiotemporally resolved brain activity recorded by electro-/magnetoencephalography when participants were listening to the same sentences. Our results provide a detailed picture of the neurobiological processes involved in the incremental construction of structured interpretations. These findings show when and where coherent interpretations emerge through the evaluation and integration of multifaceted constraints in the brain, which engages bilateral brain regions extending beyond the classical fronto-temporal language system. Furthermore, this study provides empirical evidence supporting the use of artificial neural networks as computational models for revealing the neural dynamics underpinning complex cognitive processes in the brain.

Strong Prediction: Language Model Surprisal Explains Multiple N400 Effects

Theoretical accounts of the N400 are divided as to whether the amplitude of the N400 response to a stimulus reflects the extent to which the stimulus was predicted, the extent to which the stimulus is semantically similar to its preceding context, or both. We use state-of-the-art machine learning tools to investigate which of these three accounts is best supported by the evidence. GPT-3, a neural language model trained to compute the conditional probability of any word based on the words that precede it, was used to operationalize contextual predictability. In particular, we used an information-theoretic construct known as surprisal (the negative logarithm of the conditional probability). Contextual semantic similarity was operationalized by using two high-quality co-occurrence-derived vector-based meaning representations for words: GloVe and fastText. The cosine between the vector representation of the sentence frame and final word was used to derive contextual cosine similarity estimates. A series of regression models were constructed, where these variables, along with cloze probability and plausibility ratings, were used to predict single trial N400 amplitudes recorded from healthy adults as they read sentences whose final word varied in its predictability, plausibility, and semantic relationship to the likeliest sentence completion. Statistical model comparison indicated GPT-3 surprisal provided the best account of N400 amplitude and suggested that apparently disparate N400 effects of expectancy, plausibility, and contextual semantic similarity can be reduced to variation in the predictability of words. The results are argued to support predictive coding in the human language network.

Dissociable Neural Mechanisms for Human Inference Processing Predicted by Static and Contextual Language Models

Language models (LMs) continue to reveal non-trivial relations to human language performance and the underlying neurophysiology. Recent research has characterized how word embeddings from an LM can be used to generate integrated discourse representations in order to perform inference on events. The current research investigates how such event knowledge may be coded in distinct manners in different classes of LMs and how this maps onto different forms of human inference processing. To do so, we investigate inference on events using two well-documented human experimental protocols from Metusalem et al. (2012) and McKoon and Ratcliff (1986), compared with two protocols for simpler semantic processing. Interestingly, this reveals a dissociation in the relation between local semantics versus event-inference depending on the LM. In a series of experiments, we observed that for the static LMs (word2vec/GloVe), there was a clear dissociation in the relation between semantics and inference for the two inference tasks. In contrast, for the contextual LMs (BERT/RoBERTa), we observed a correlation between semantic and inference processing for both inference tasks. The experimental results suggest that inference as measured by Metusalem and McKoon rely on dissociable processes. While the static models are able to perform Metusalem inference, only the contextual models succeed in McKoon inference. Interestingly, these dissociable processes may be linked to well-characterized automatic versus strategic inference processes in the psychological literature. This allows us to make predictions about dissociable neurophysiological markers that should be found during human inference processing with these tasks.

I know how you'll say it: evidence of speaker-specific speech prediction

Most models of language comprehension assume that the linguistic system is able to pre-activate phonological information. However, the evidence for phonological prediction is mixed and controversial. In this study, we implement a paradigm that capitalizes on the fact that foreign speakers usually make phonological errors. We investigate whether speaker identity (native vs. foreign) is used to make specific phonological predictions. Fifty-two participants were recruited to read sentence frames followed by a last spoken word which was uttered by either a native or a foreign speaker. They were required to perform a lexical decision on the last spoken word, which could be either semantically predictable or not. Speaker identity (native vs. foreign) may or may not be cued by the face of the speaker. We observed that the face cue is effective in speeding up the lexical decision when the word is predictable, but it is not effective when the word is not predictable. This result shows that speech prediction takes into account the phonological variability between speakers, suggesting that it is possible to pre-activate in a detailed and specific way the phonological representation of a predictable word.

Enhancing Syntactic Knowledge in School-Age Children With Developmental Language Disorder: The Promise of Syntactic Priming

PURPOSE

We propose that implicit learning, including syntactic priming, has therapeutic promise to enhance the syntactic knowledge of children with developmental language disorder (DLD).

METHOD

We review the chunk-based learning framework of syntactic learning, the developmental evidence in support of it, and the developmental literature on syntactic priming as an instance of chunk-based statistical learning. We use this framework to help understand the nature of the syntactic learning difficulties of children with DLD. We then briefly review the available explicit treatments for syntactic deficits and end by proposing an implicit training activity that integrates syntactic priming with the principles of statistical learning.

RESULTS

Statistically induced chunk-based learning is a powerful driver of syntactic learning, and syntactic priming is a form of this learning. Repeated priming episodes during everyday language interactions lead children to create abstract and global syntactic representations in long-term memory. We offer some thoughts on an implicit language intervention approach with syntactic priming at its center.

CONCLUSIONS

Children's learning of syntactic structures is influenced by repeated syntactic priming experiences. Including a syntactic priming activity in our language intervention toolbox has the promise to enhance children's syntactic knowledge and sentence comprehension and production abilities.

Word Frequency and Predictability Dissociate in Naturalistic Reading

Many studies of human language processing have shown that readers slow down at less frequent or less predictable words, but there is debate about whether frequency and predictability effects reflect separable cognitive phenomena: are cognitive operations that retrieve words from the mental lexicon based on sensory cues distinct from those that predict upcoming words based on context? Previous evidence for a frequency-predictability dissociation is mostly based on small samples (both for estimating predictability and frequency and for testing their effects on human behavior), artificial materials (e.g., isolated constructed sentences), and implausible modeling assumptions (discrete-time dynamics, linearity, additivity, constant variance, and invariance over time), which raises the question: do frequency and predictability dissociate in ordinary language comprehension, such as story reading? This study leverages recent progress in open data and computational modeling to address this question at scale. A large collection of naturalistic reading data (six datasets, >2.2 M datapoints) is analyzed using nonlinear continuous-time regression, and frequency and predictability are estimated using statistical language models trained on more data than is currently typical in psycholinguistics. Despite the use of naturalistic data, strong predictability estimates, and flexible regression models, results converge with earlier experimental studies in supporting dissociable and additive frequency and predictability effects.

Large-scale evidence for logarithmic effects of word predictability on reading time

During real-time language comprehension, our minds rapidly decode complex meanings from sequences of words. The difficulty of doing so is known to be related to words' contextual predictability, but what cognitive processes do these predictability effects reflect? In one view, predictability effects reflect facilitation due to anticipatory processing of words that are predictable from context. This view predicts a linear effect of predictability on processing demand. In another view, predictability effects reflect the costs of probabilistic inference over sentence interpretations. This view predicts either a logarithmic or a superlogarithmic effect of predictability on processing demand, depending on whether it assumes pressures toward a uniform distribution of information over time. The empirical record is currently mixed. Here, we revisit this question at scale: We analyze six reading datasets, estimate next-word probabilities with diverse statistical language models, and model reading times using recent advances in nonlinear regression. Results support a logarithmic effect of word predictability on processing difficulty, which favors probabilistic inference as a key component of human language processing.

Nuances of knowing: Brain potentials reveal implicit effects of domain knowledge on word processing in the absence of sentence-level knowledge

In previous work investigating the relationship between domain knowledge (of the fictional world of Harry Potter) and sentence comprehension, domain knowledge had a greater impact on electrical brain potentials to words which completed sentences about fictional "facts" participants reported they did not know compared to facts they did. This suggests that individuals use domain knowledge continuously to activate relevant/related concepts as they process sentences, even with only partial knowledge. As that study relied on subjective reports, it may have resulted in response bias related to an individual's overall domain knowledge. In the present study, we therefore asked participants with varying degrees of domain knowledge to complete sentences describing fictional "facts" as an objective measure of sentence-level knowledge. We then recorded EEG as the same individuals (re-)read the same sentences, including their appropriate final words, and sorted these according to their objective knowledge scores. Replicating and extending Troyer et al., domain knowledge immediately facilitated access to meaning for unknown words; greater domain knowledge was associated with reduced N400 amplitudes for unknown words. These findings constitute novel evidence for graded preactivation of conceptual knowledge (e.g., at the level of semantic features and/or relations) in the absence of lexical prediction. Knowledge also influenced post-N400 memory/integration processes for these same unknown words; greater domain knowledge was associated with enhanced late positive components (LPCs), suggesting that deeper encoding during language processing may be engendered when knowledgeable individuals encounter an apparent gap in their knowledge.

Discourse coherence modulates use of predictive processing during sentence comprehension

Context has been shown to be vitally important for comprehension. Lexical processing is facilitated when words are highly predictable given their local sentence context, suggesting that people pre-activate likely upcoming words to aid comprehension. However, this facilitation is affected by knowledge about the global context in which comprehension takes place: people predict less when in an environment where expectations are frequently violated. The current study investigated whether discourse coherence is an additional cue that comprehenders use to modulate lexical prediction. In a series of online, self-paced reading experiments, participants read target sentences preceded by short contextual preambles. Local facilitation effects were manipulated through the cloze probability of a critical word within the target sentence and discourse coherence was manipulated by varying the degree to which the target sentence was consistent with the information presented in the preamble. In the first two experiments, target sentences were read more slowly when they occurred in less coherent discourses, but no local facilitation effects were observed. In the third experiment, we strengthened the predictability manipulation by using semantically anomalous critical words. In this experiment, predictable words were processed more quickly and anomalous words more slowly when they occurred in highly coherent discourse. Our results suggest that comprehenders are sensitive to shifts in the topic of discourse and that they downregulate predictive processing when they encounter incoherence in the discourse. This is consistent with recent theoretical accounts suggesting that comprehenders flexibly engage in predictive processing, pre-activating semantic and lexical information less when their expectations are less likely to be reliable.

Ignoring the alternatives: The N400 is sensitive to stimulus preactivation alone

The N400 component of the event-related brain potential is a neural signal of processing difficulty. In the language domain, it is widely believed to be sensitive to the degree to which a given word or its semantic features have been preactivated in the brain based on the preceding context. However, it has also been shown that the brain often preactivates many words in parallel. It is currently unknown whether the N400 is also affected by the preactivations of alternative words other than the stimulus that is actually presented. This leaves a weak link in the derivation chain-how can we use the N400 to understand the mechanisms of preactivation if we do not know what it indexes? This study directly addresses this gap. We estimate the extent to which all words in a lexicon are preactivated in a given context using the predictions of contemporary large language models. We then directly compare two competing possibilities: that the amplitude of the N400 is sensitive only to the extent to which the stimulus is preactivated, and that it is also sensitive to the preactivation states of the alternatives. We find evidence of the former. This result allows for better grounded inferences about the mechanisms underlying the N400, lexical preactivation in the brain, and language processing more generally.

Causal inference: relating language to event representations and events in the world

Events are not isolated but rather linked to one another in various dimensions. In language processing, various sources of information-including real-world knowledge, (representations of) current linguistic input and non-linguistic visual context-help establish causal connections between events. In this review, we discuss causal inference in relation to events and event knowledge as one aspect of world knowledge, and their representations in language comprehension. To evaluate the mechanism and time course of causal inference, we gather insights from studies on (1) implicit causality/consequentiality as a specific form of causal inference regarding the protagonists of cause/consequence events, and (2) the processing of causal relations. We highlight the importance of methodology in measuring causal inference, compare the results from different research methods, and emphasize the contribution of the visual-world paradigm to achieve a better understanding of causal inference. We recommend that further investigations of causal inference consider temporally sensitive measures and more detailed contexts.

Electrophysiological evidence for the enhancement of gesture-speech integration by linguistic predictability during multimodal discourse comprehension

In face-to-face discourse, listeners exploit cues in the input to generate predictions about upcoming words. Moreover, in addition to speech, speakers produce a multitude of visual signals, such as iconic gestures, which listeners readily integrate with incoming words. Previous studies have shown that processing of target words is facilitated when these are embedded in predictable compared to non-predictable discourses and when accompanied by iconic compared to meaningless gestures. In the present study, we investigated the interaction of both factors. We recorded electroencephalogram from 60 Dutch adults while they were watching videos of an actress producing short discourses. The stimuli consisted of an introductory and a target sentence; the latter contained a target noun. Depending on the preceding discourse, the target noun was either predictable or not. Each target noun was paired with an iconic gesture and a gesture that did not convey meaning. In both conditions, gesture presentation in the video was timed such that the gesture stroke slightly preceded the onset of the spoken target by 130 ms. Our ERP analyses revealed independent facilitatory effects for predictable discourses and iconic gestures. However, the interactive effect of both factors demonstrated that target processing (i.e., gesture-speech integration) was facilitated most when targets were part of predictable discourses and accompanied by an iconic gesture. Our results thus suggest a strong intertwinement of linguistic predictability and non-verbal gesture processing where listeners exploit predictive discourse cues to pre-activate verbal and non-verbal representations of upcoming target words.

Examining the extraction of parafoveal semantic information in Tibetan

This study conducted two experiments to investigate the extraction of semantic preview information from the parafovea in Tibetan reading. In Experiment 1, a single-factor (preview type: identical vs. semantically related vs. unrelated) within-subject experimental design was used to investigate whether there is a parafoveal semantic preview effect (SPE) in Tibetan reading. Experiment 2 used a 2 (contextual constraint: high vs. low) × 3 (preview type: identical vs. semantically related vs. unrelated) within-subject experimental design to investigate the influence of contextual constraint on the parafoveal semantic preview effect in Tibetan reading. Supporting the E-Z reader model, the experimental results showed that in Tibetan reading, readers could not obtain semantic preview information from the parafovea, and contextual constraint did not influence this process. However, comparing high- and low-constrained contexts, the latter might be more conducive to extracting semantic preview information from the parafovea.

Effects of world knowledge on the prediction of upcoming verbs: an eye-tracking study

Some theories of sentence processing make a distinction between two kinds of meaning: a linguistic meaning encoded at the lexicon (i.e., selectional restrictions), and an extralinguistic knowledge derived from our everyday experiences (i.e., world knowledge). According to such theories, the former meaning is privileged over the latter in terms of the time-course of its access and influence during on-line language comprehension. The present study aims to examine whether world knowledge anomalies (that do not violate selectional restrictions) are rapidly detected during online sentence processing. In an eye-tracking experiment, we used materials in which the likelihood of a specific verb (entrevistar or secuestrar, the Spanish translations for to interview and to kidnap) depended on the agent of the event (periodista or terrorista, the Spanish translations for journalist and terrorist). The results showed an effect of typicality in regression path duration and total reading times at both the verb region and the spillover region, thus providing evidence that world knowledge is rapidly accessed and used during on-line sentence comprehension.

Knowledge of the temporal structure of events in relation to autistic traits and social ability

Event knowledge, a person's understanding of patterns of activities in the world, is crucial for everyday social interactions. Social communication differences are prominent in autism, which may be related to atypical event knowledge, such as atypical knowledge of the sequences of activities that comprise the temporal structure of events. Previous research has found that autistic individuals have atypical event knowledge, but research in this area is minimal, particularly regarding autistic individuals' knowledge of the temporal structure of events. Furthermore, no studies have investigated the link between event knowledge and autistic traits in a non-clinical sample. We investigated relationships between event knowledge and autistic traits in individuals from the general population with varying degrees of autistic traits. We predicted that atypical ordering of event activities is related to autistic traits, particularly social communication abilities, but not other clinical traits. In Study 1, atypical ordering of event activities correlated with social ability, but not with most measures of repetitive behaviours and restricted interests. In Study 2, the typicality of activity ordering varied by participants' social ability and the social nature of the events. Relationships were not found between event activity ordering and other clinical traits. These findings suggest a relationship between autistic traits, specifically social abilities, and knowledge of the temporal structure of events in a general population sample.

Is the Mind Inherently Predicting? Exploring Forward and Backward Looking in Language Processing

Prediction is one characteristic of the human mind. But what does it mean to say the mind is a "prediction machine" and inherently forward looking as is frequently claimed? In natural languages, many contexts are not easily predictable in a forward fashion. In English, for example, many frequent verbs do not carry unique meaning on their own but instead, rely on another word or words that follow them to become meaningful. Upon reading take a the processor often cannot easily predict walk as the next word. But the system can "look back" and integrate walk more easily when it follows take a (e.g., as opposed to *make|get|have a walk). In the present paper, we provide further evidence for the importance of both forward and backward-looking in language processing. In two self-paced reading tasks and an eye-tracking reading task, we found evidence that adult English native speakers' sensitivity to word forward and backward conditional probability significantly predicted reading times over and above psycholinguistic predictors of reading latencies. We conclude that both forward and backward-looking (prediction and integration) appear to be important characteristics of language processing. Our results thus suggest that it makes just as much sense to call the mind an "integration machine" which is inherently backward 'looking.'

The social hierarchical restrictions of Chinese verbs rapidly guide online thematic role assignment in comprehension

The information about social hierarchical relationship has been intrinsically embedded into semantic restrictions of some Chinese verbs theoretically. For example, the Chinese verb ''(shanyang, support: provide for the needs and comfort of one's elders) only allows its Agent role to have a lower social status compared to the Patient role. However, whether this hierarchical restriction can be rapidly activated and how it impacts online thematic role assignment in reading remains to be seen. To answer this question, a 2 (Verb Type: hierarchical vs non-hierarchical verbs) × 2 (Social Hierarchy Sequence: match vs mismatch) design was constructed in the present study to investigate the interaction between the two factors. ERPs showed that hierarchical restriction violations evoked a stronger anterior negativity to the sentence-final noun (NP2). This effect was absent under two non-hierarchical conditions. To our knowledge, this study is the first to reveal that social hierarchical restrictions of Chinese hierarchical verbs can be rapidly available to guide online thematic role assignment and this process might be closely related to readers' thematic role knowledge.

The last course of coarse coding: Hemispheric similarities in associative and categorical semantic processing

To test theories that posit differences in how semantic information is represented in the cerebral hemispheres, we assessed semantic priming for associatively and categorically related prime-target pairs that were graded in relatedness strength. Visual half-field presentation was used to bias processing to the right or left hemisphere, and event-related potential (ERP) and behavioral responses were measured while participants completed a semantic relatedness judgement task. Contrary to theories positing representational differences across the cerebral hemispheres, in two experiments using (1) centralized prime presentation and lateralized targets and (2) lateralized primes and targets, we found similar priming patterns across the two hemispheres at the level of semantic access (N400), on later measures of explicit processing (late positive complex; LPC), and in behavioral response speeds and accuracy. We argue that hemispheric differences, when they arise, are more likely due to differences in task demands than in how the hemispheres fundamentally represent semantic information.

Mandarin and English Event Cognitive Alignment From Corpus-Based Semantic Fusion Model Perspective

The study explores the fusion of semantic roles and the different semantic fusion types, aiming at establishing a semantic fusion model to explain the cognitive alignment of events in Chinese and English simple sentence constructions containing two verbs. In total, 20,280 simple sentence constructions containing two verbs are collected from Chinese literary works, Peking University Chinese Corpus, and English classic literary works. The semantic fusion in the collected simple sentence constructions containing two verbs is classified into five major semantic fusion categories, which appear with different occurrence frequencies in the two languages. The semantic fusion model of event alignment is comprehensively supported by linguistic research in Chinese and English. From a cognitive linguistic perspective, it is found that the double semantic profiles of the same syntactic element N (noun) make N psychologically activated twice and enable it to enter two processes profiled by the two verbs as a participant. The two processes are combined into one event, which designates a cognitive occurrence of any degree of complexity. N's entry into the two subevents is realized by its double semantic profiles that enable it to fuse two semantic roles into one syntactic element and explain the relationship between N's double syntactic identities and double semantic roles. The semantic fusion model was used to explore event alignment in simple sentence constructions containing two verbs, and it was discovered that the fusion of two semantic roles is universal in languages and is a common psychological and cognitive behavior deeply rooted in the mental conceptualization of language users. The empirical discussion of simple sentence constructions containing two verbs proves that semantic fusion as an important psychological passage in event alignment has solid psychological reality and verifies the applicability of the semantic fusion model in the explanation of event alignment.

Predictive Processing in Sign Languages: A Systematic Review

The objective of this article was to review existing research to assess the evidence for predictive processing (PP) in sign language, the conditions under which it occurs, and the effects of language mastery (sign language as a first language, sign language as a second language, bimodal bilingualism) on the neural bases of PP. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. We searched peer-reviewed electronic databases (SCOPUS, Web of Science, PubMed, ScienceDirect, and EBSCO host) and gray literature (dissertations in ProQuest). We also searched the reference lists of records selected for the review and forward citations to identify all relevant publications. We searched for records based on five criteria (original work, peer-reviewed, published in English, research topic related to PP or neural entrainment, and human sign language processing). To reduce the risk of bias, the remaining two authors with expertise in sign language processing and a variety of research methods reviewed the results. Disagreements were resolved through extensive discussion. In the final review, 7 records were included, of which 5 were published articles and 2 were dissertations. The reviewed records provide evidence for PP in signing populations, although the underlying mechanism in the visual modality is not clear. The reviewed studies addressed the motor simulation proposals, neural basis of PP, as well as the development of PP. All studies used dynamic sign stimuli. Most of the studies focused on semantic prediction. The question of the mechanism for the interaction between one’s sign language competence (L1 vs. L2 vs. bimodal bilingual) and PP in the manual-visual modality remains unclear, primarily due to the scarcity of participants with varying degrees of language dominance. There is a paucity of evidence for PP in sign languages, especially for frequency-based, phonetic (articulatory), and syntactic prediction. However, studies published to date indicate that Deaf native/native-like L1 signers predict linguistic information during sign language processing, suggesting that PP is an amodal property of language processing.

Does the character-based dimension of stories impact narrative processing? An event-related potentials (ERPs) study

This event-related potentials (ERPs) study investigated online processes of integration of information relating to characters in narrative comprehension. The final sample included twenty-nine participants who read short third-person stories in which the plausibility of the characters' actions was manipulated. Stories were administered in three conditions: a character-based congruent condition including a target word that was consistent with the character's job; a character-based incongruent condition with a target word inconsistent with the character's job; a character-based neutral condition, narrating the action of a character presented by his/her proper name without information about his/her job. Results comparing the ERPs elicited by the experimental conditions revealed a greater negative amplitude of the N400 in the right temporal regions in response to the character-based incongruent compared to the character-based congruent narratives. This finding shows that implicit background character-based information affects the N400, with readers rapidly using this information to comprehend narratives.

Connecting and considering: Electrophysiology provides insights into comprehension

The ability to rapidly and systematically access knowledge stored in long-term memory in response to incoming sensory information-that is, to derive meaning from the world-lies at the core of human cognition. Research using methods that can precisely track brain activity over time has begun to reveal the multiple cognitive and neural mechanisms that make this possible. In this article, I delineate how a process of connecting affords an effortless, continuous infusion of meaning into human perception. In a relatively invariant time window, uncovered through studies using the N400 component of the event-related potential, incoming sensory information naturally induces a graded landscape of activation across long-term semantic memory, creating what might be called "proto-concepts". Connecting can be (but is not always) followed by a process of further considering those activations, wherein a set of more attentionally demanding "active comprehension" mechanisms mediate the selection, augmentation, and transformation of the initial semantic representations. The result is a limited set of more stable bindings that can be arranged in time or space, revised as needed, and brought to awareness. With this research, we are coming closer to understanding how the human brain is able to fluidly link sensation to experience, to appreciate language sequences and event structures, and, sometimes, to even predict what might be coming up next.

Narrative event segmentation in the cortical reservoir

Recent research has revealed that during continuous perception of movies or stories, humans display cortical activity patterns that reveal hierarchical segmentation of event structure. Thus, sensory areas like auditory cortex display high frequency segmentation related to the stimulus, while semantic areas like posterior middle cortex display a lower frequency segmentation related to transitions between events. These hierarchical levels of segmentation are associated with different time constants for processing. Likewise, when two groups of participants heard the same sentence in a narrative, preceded by different contexts, neural responses for the groups were initially different and then gradually aligned. The time constant for alignment followed the segmentation hierarchy: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. These hierarchical segmentation phenomena can be considered in the context of processing related to comprehension. In a recently described model of discourse comprehension word meanings are modeled by a language model pre-trained on a billion word corpus. During discourse comprehension, word meanings are continuously integrated in a recurrent cortical network. The model demonstrates novel discourse and inference processing, in part because of two fundamental characteristics: real-world event semantics are represented in the word embeddings, and these are integrated in a reservoir network which has an inherent gradient of functional time constants due to the recurrent connections. Here we demonstrate how this model displays hierarchical narrative event segmentation properties beyond the embeddings alone, or their linear integration. The reservoir produces activation patterns that are segmented by a hidden Markov model (HMM) in a manner that is comparable to that of humans. Context construction displays a continuum of time constants across reservoir neuron subsets, while context forgetting has a fixed time constant across these subsets. Importantly, virtual areas formed by subgroups of reservoir neurons with faster time constants segmented with shorter events, while those with longer time constants preferred longer events. This neurocomputational recurrent neural network simulates narrative event processing as revealed by the fMRI event segmentation algorithm provides a novel explanation of the asymmetry in narrative forgetting and construction. The model extends the characterization of online integration processes in discourse to more extended narrative, and demonstrates how reservoir computing provides a useful model of cortical processing of narrative structure.

Retrieval (N400) and integration (P600) in expectation-based comprehension

Expectation-based theories of language processing, such as Surprisal theory, are supported by evidence of anticipation effects in both behavioural and neurophysiological measures. Online measures of language processing, however, are known to be influenced by factors such as lexical association that are distinct from—but often confounded with—expectancy. An open question therefore is whether a specific locus of expectancy related effects can be established in neural and behavioral processing correlates. We address this question in an event-related potential experiment and a self-paced reading experiment that independently cross expectancy and lexical association in a context manipulation design. We find that event-related potentials reveal that the N400 is sensitive to both expectancy and lexical association, while the P600 is modulated only by expectancy. Reading times, in turn, reveal effects of both association and expectancy in the first spillover region, followed by effects of expectancy alone in the second spillover region. These findings are consistent with the Retrieval-Integration account of language comprehension, according to which lexical retrieval (N400) is facilitated for words that are both expected and associated, whereas integration difficulty (P600) will be greater for unexpected words alone. Further, an exploratory analysis suggests that the P600 is not merely sensitive to expectancy violations, but rather, that there is a continuous relation. Taken together, these results suggest that the P600, like reading times, may reflect a meaning-centric notion of Surprisal in language comprehension.

A Theoretical Framework for a Hybrid View of the N400

In this study, we present a novel theoretical account of the N400 event-related potential (ERP) component. Hybrid views interpret this ERP component in terms of two cognitive operations: (i) access of information, which is related to predictions (predictability component), and (ii) integration of information, which is related to plausibility (plausibility component). Though there is an empirical evidence for this view, what has been left open so far is how these two operations can be defined. In our approach, both components are related to categorization. The critical word and the argument position it is related to are associated with categories that have a graded structure. This graded structure is defined in terms of weights both on attributes and values of features belonging to a category. The weights, in turn, are defined using probability distributions. The predictability component is defined in terms of the information gain with respect to non mismatched features between the two categories. The plausibility component is defined as the difference in the degree of typicality between the two categories. Finally, the N400 amplitude is defined as a function of both components.

Semantic Predictability Facilitates Comprehension of Degraded Speech in a Graded Manner

Previous studies have shown that at moderate levels of spectral degradation, semantic predictability facilitates language comprehension. It is argued that when speech is degraded, listeners have narrowed expectations about the sentence endings; i.e., semantic prediction may be limited to only most highly predictable sentence completions. The main objectives of this study were to (i) examine whether listeners form narrowed expectations or whether they form predictions across a wide range of probable sentence endings, (ii) assess whether the facilitatory effect of semantic predictability is modulated by perceptual adaptation to degraded speech, and (iii) use and establish a sensitive metric for the measurement of language comprehension. For this, we created 360 German Subject-Verb-Object sentences that varied in semantic predictability of a sentence-final target word in a graded manner (high, medium, and low) and levels of spectral degradation (1, 4, 6, and 8 channels noise-vocoding). These sentences were presented auditorily to two groups: One group (n =48) performed a listening task in an unpredictable channel context in which the degraded speech levels were randomized, while the other group (n =50) performed the task in a predictable channel context in which the degraded speech levels were blocked. The results showed that at 4 channels noise-vocoding, response accuracy was higher in high-predictability sentences than in the medium-predictability sentences, which in turn was higher than in the low-predictability sentences. This suggests that, in contrast to the narrowed expectations view, comprehension of moderately degraded speech, ranging from low- to high- including medium-predictability sentences, is facilitated in a graded manner; listeners probabilistically preactivate upcoming words from a wide range of semantic space, not limiting only to highly probable sentence endings. Additionally, in both channel contexts, we did not observe learning effects; i.e., response accuracy did not increase over the course of experiment, and response accuracy was higher in the predictable than in the unpredictable channel context. We speculate from these observations that when there is no trial-by-trial variation of the levels of speech degradation, listeners adapt to speech quality at a long timescale; however, when there is a trial-by-trial variation of the high-level semantic feature (e.g., sentence predictability), listeners do not adapt to low-level perceptual property (e.g., speech quality) at a short timescale.

The role of language production in making predictions during comprehension

Language comprehension depends heavily upon prediction, but how predictions are generated remains poorly understood. Several recent theories propose that these predictions are in fact generated by the language production system. Here, we directly test this claim. Participants read sentence contexts that either were or were not highly predictive of a final word, and we measured how quickly participants recognised that final word (Experiment 1), named that final word (Experiment 2), or used that word to name a picture (Experiment 3). We manipulated engagement of the production system by asking participants to read the sentence contexts either aloud or silently. Across the experiments, participants responded more quickly following highly predictive contexts. Importantly, the effect of contextual predictability was greater when participants had read the sentence contexts aloud rather than silently, a finding that was significant in Experiment 3, marginally significant in Experiment 2, and again significant in combined analyses of Experiments 1-3. These results indicate that language production (as used in reading aloud) can be used to facilitate prediction. We consider whether prediction benefits from production only in particular contexts and discuss the theoretical implications of our evidence.

Thematic and other semantic relations central to abstract (and concrete) concepts

In this article, we discuss multiple types of meaningful (semantic) relations underlying abstract (as compared to concrete) concepts. We adopt the viewpoint that words act as cues to meaning (Elman in Ment Lexicon 6(1):1-34, 2011; Lupyan and Lewis in Lang Cogn Neurosci 34(10):1319-1337, 2019), which is dependent on the dynamic contents of a comprehender's mental model of the situation. This view foregrounds the importance of both linguistic and real-world context as individuals make sense of words, flexibly access relevant knowledge, and understand described events and situations. We discuss theories of, and experimental work on, abstract concepts through the lens of the importance of thematic and other semantic relations. We then tie these findings to the sentence processing literature in which such meaningful relations within sentential contexts are often experimentally manipulated. In this literature, some specific classes/types of abstract words have been studied, although not comprehensively, and with limited connection to the literature on knowledge underlying abstract concepts reviewed herein. We conclude by arguing that the ways in which humans understand relatively more abstract concepts, in particular, can be informed by the careful study of words presented not in isolation, but rather in situational and linguistic contexts, and as a function of individual differences in knowledge, goals, and beliefs.

Semantic memory: A review of methods, models, and current challenges

Adult semantic memory has been traditionally conceptualized as a relatively static memory system that consists of knowledge about the world, concepts, and symbols. Considerable work in the past few decades has challenged this static view of semantic memory, and instead proposed a more fluid and flexible system that is sensitive to context, task demands, and perceptual and sensorimotor information from the environment. This paper (1) reviews traditional and modern computational models of semantic memory, within the umbrella of network (free association-based), feature (property generation norms-based), and distributional semantic (natural language corpora-based) models, (2) discusses the contribution of these models to important debates in the literature regarding knowledge representation (localist vs. distributed representations) and learning (error-free/Hebbian learning vs. error-driven/predictive learning), and (3) evaluates how modern computational models (neural network, retrieval-based, and topic models) are revisiting the traditional "static" conceptualization of semantic memory and tackling important challenges in semantic modeling such as addressing temporal, contextual, and attentional influences, as well as incorporating grounding and compositionality into semantic representations. The review also identifies new challenges regarding the abundance and availability of data, the generalization of semantic models to other languages, and the role of social interaction and collaboration in language learning and development. The concluding section advocates the need for integrating representational accounts of semantic memory with process-based accounts of cognitive behavior, as well as the need for explicit comparisons of computational models to human baselines in semantic tasks to adequately assess their psychological plausibility as models of human semantic memory.

Rhyme as resonance in poetry comprehension: An expert-novice study

Previous research has identified alliteration as a powerful device for investigating implicit memory effects. For example, alliterative phrases can provide retrieval cues that extend to a sublexical level and reactivate previous information that shares alliterative content (Lea et al., Psychological Science, 19[7], 709-716, 2008). But it is an open question if other surface forms might provide similar effects in line with these empirical findings, and in accord with writer intuitions. The present study examined whether rhyme produces analogous memory-reactivation effects, given the ubiquity of its use and endorsement of its power in a range of materials and experiences. We also examined whether the surface benefits attributed to rhyme might support anticipatory processes such as those traditionally examined with semantic content. In Experiment 1, participants exhibited faster recognition responses to previous poetic content as a function of rhyming cues. In Experiment 2, we recruited participants identified as experts on the study and use of rhyme, replicating the probe facilitations obtained in Experiment 1, but also revealing anticipations of imminent rhymes. The results are discussed in terms of implications for theories of memory-based text processing and of nonsemantic anticipatory processes during the reading of poetry, and perhaps for discourse experiences more generally.

Effects of Dispositional Affect on the N400: Language Processing and Socially Situated Context

We examined whether the N400 Event-Related Potential (ERP) component would be modulated by dispositional affect during sentence processing. In this study, 33 participants read sentences manipulated by direct object type (congruent vs. incongruent) and object determiner type (definite vs. demonstrative). We were particularly interested in sentences of the form: (i) The connoisseur tasted the wine on the tour vs. (ii) The connoisseur tasted the # roof … We expected that processing incongruent direct objects (#roof) vs. congruent objects (wine) would elicit N400 effects. Previous ERP language experiments have shown that participants in (induced) positive and negative moods were differentially sensitive to semantic anomaly, resulting in different N400 effects. Presently, we ask whether individual dispositional affect scores (as measured by the Positive and Negative Affect Schedule; PANAS) would modulate N400 effects as shown previously. Namely, previous results showed larger N400 effects associated with happy moods and attenuated amplitudes associated with sad moods. Results revealed significant N400 effects, driven by the #roof vs. the wine, where larger amplitude differences were found for individuals showing smaller negative affect (NA) scores, thus partially replicating previous findings. We discuss our results in terms of theories of local (lexical) inhibition, such that low NA promotes stronger lexico-semantic links in sentences. Finally, our results support accounts of language processing that include social and biological characteristics of individuals during real-time sentence comprehension.

Grounding Language Processing: The Added Value of Specifying Linguistic/Compositional Representations and Processes

Abundant empirical evidence suggests that visual perception and motor responses are involved in language comprehension ('grounding'). However, when modeling the grounding of sentence comprehension on a word-by-word basis, linguistic representations and cognitive processes are rarely made fully explicit. This article reviews representational formalisms and associated (computational) models with a view to accommodating incremental and compositional grounding effects. Are different representation formats equally suitable and what mechanisms and representations do models assume to accommodate grounding effects? I argue that we must minimally specify compositional semantic representations, a set of incremental processes/mechanisms, and an explicit link from the assumed processes to measured behavior. Different representational formats can be contrasted in psycholinguistic modeling by holding the set of processes/mechanisms constant; contrasting different processes/mechanisms is possible by holding representations constant. Such psycholinguistic modeling could be applied across a wide range of experimental investigations and complement computational modeling.

Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments

We describe a novel approach to estimating the predictability of utterances given extralinguistic context in psycholinguistic research. Predictability effects on language production and comprehension are widely attested, but so far predictability has mostly been manipulated through local linguistic context, which is captured with n-gram language models. However, this method does not allow to investigate predictability effects driven by extralinguistic context. Modeling effects of extralinguistic context is particularly relevant to discourse-initial expressions, which can be predictable even if they lack linguistic context at all. We propose to use script knowledge as an approximation to extralinguistic context. Since the application of script knowledge involves the generation of prediction about upcoming events, we expect that scrips can be used to manipulate the likelihood of linguistic expressions referring to these events. Previous research has shown that script-based discourse expectations modulate the likelihood of linguistic expressions, but script knowledge has often been operationalized with stimuli which were based on researchers’ intuitions and/or expensive production and norming studies. We propose to quantify the likelihood of an utterance based on the probability of the event to which it refers. This probability is calculated with event language models trained on a script knowledge corpus and modulated with probabilistic event chains extracted from the corpus. We use the DeScript corpus of script knowledge to obtain empirically founded estimates of the likelihood of an event to occur in context without having to resort to expensive pre-tests of the stimuli. We exemplify our method at a case study on the usage of nonsentential expressions (fragments), which shows that utterances that are predictable given script-based extralinguistic context are more likely to be reduced.

Concurrent use of animacy and event-knowledge during comprehension: Evidence from event-related potentials

In two ERP experiments, we investigated whether readers prioritize animacy over real-world event-knowledge during sentence comprehension. We used the paradigm of Paczynski and Kuperberg (2012), who argued that animacy is prioritized based on the observations that the 'related anomaly effect' (reduced N400s for context-related anomalous words compared to unrelated words) does not occur for animacy violations, and that animacy violations but not relatedness violations elicit P600 effects. Participants read passive sentences with plausible agents (e.g., The prescription for the mental disorder was written by the psychiatrist) or implausible agents that varied in animacy and semantic relatedness (schizophrenic/guard/pill/fence). In Experiment 1 (with a plausibility judgment task), plausible sentences elicited smaller N400s relative to all types of implausible sentences. Crucially, animate words elicited smaller N400s than inanimate words, and related words elicited smaller N400s than unrelated words, but Bayesian analysis revealed substantial evidence against an interaction between animacy and relatedness. Moreover, at the P600 time-window, we observed more positive ERPs for animate than inanimate words and for related than unrelated words at anterior regions. In Experiment 2 (without judgment task), we observed an N400 effect with animacy violations, but no other effects. Taken together, the results of our experiments fail to support a prioritized role of animacy information over real-world event-knowledge, but they support an interactive, constraint-based view on incremental semantic processing.

A Model of Online Temporal-Spatial Integration for Immediacy and Overrule in Discourse Comprehension

During discourse comprehension, information from prior processing is integrated and appears to be immediately accessible. This was remarkably demonstrated by an N400 for "salted" and not "in love" in response to "The peanut was salted/in love." Discourse overrule was induced by prior discourse featuring the peanut as an animate agent. Immediate discourse overrule requires a model that integrates information at two timescales. One is over the lifetime and includes event knowledge and word semantics. The second is over the discourse in an event context. We propose a model where both are accounted for by temporal-to-spatial integration of experience into distributed spatial representations, providing immediate access to experience accumulated over different timescales. For lexical semantics, this is modeled by a word embedding system trained by sequential exposure to the entire Wikipedia corpus. For discourse, this is modeled by a recurrent reservoir network trained to generate a discourse vector for input sequences of words. The N400 is modeled as the difference between the instantaneous discourse vector and the target word. We predict this model can account for semantic immediacy and discourse overrule. The model simulates lexical priming and discourse overrule in the "Peanut in love" discourse, and it demonstrates that an unexpected word elicits reduced N400 if it is generally related to the event described in prior discourse, and that this effect disappears when the discourse context is removed. This neurocomputational model is the first to simulate immediacy and overrule in discourse-modulated N400, and contributes to characterization of online integration processes in discourse.

Tea With Milk? A Hierarchical Generative Framework of Sequential Event Comprehension

To make sense of the world around us, we must be able to segment a continual stream of sensory inputs into discrete events. In this review, I propose that in order to comprehend events, we engage hierarchical generative models that "reverse engineer" the intentions of other agents as they produce sequential action in real time. By generating probabilistic predictions for upcoming events, generative models ensure that we are able to keep up with the rapid pace at which perceptual inputs unfold. By tracking our certainty about other agents' goals and the magnitude of prediction errors at multiple temporal scales, generative models enable us to detect event boundaries by inferring when a goal has changed. Moreover, by adapting flexibly to the broader dynamics of the environment and our own comprehension goals, generative models allow us to optimally allocate limited resources. Finally, I argue that we use generative models not only to comprehend events but also to produce events (carry out goal-relevant sequential action) and to continually learn about new events from our surroundings. Taken together, this hierarchical generative framework provides new insights into how the human brain processes events so effortlessly while highlighting the fundamental links between event comprehension, production, and learning.

Examining the Role of General Cognitive Skills in Language Processing: A Window into Complex Cognition

Whenever we use language to communicate, sounds, signs, and/or letters are combined into words that, in turn, form sentences, which together tell a story. Both language production and language comprehension rely on representations at different levels of granularity that need to be continuously and rapidly activated, selected, and combined. The representations themselves are specific to language, but many processes that regulate their use, such as inhibition of competitors or updating of working memory with new information, are so-called domain-general abilities that apply across different kinds of tasks. Here, we provide an overview of the behavioral and neurophysiological evidence in favor of domain-general abilities underpinning language skills and describe which particular aspects of production and comprehension draw upon such cognitive resources. We discuss how this line of research not only reveals important similarities between production and comprehension but also helps to establish links between language and other cognitive domains. Finally, we argue that studying how domain-general abilities are used in language will lead to important insights into the highly dynamic and efficient communication between brain networks that is necessary to successfully go from sounds to stories.

To catch a Snitch: Brain potentials reveal variability in the functional organization of (fictional) world knowledge during reading

We harnessed the temporal sensitivity of event-related brain potentials (ERPs) alongside individual differences in Harry Potter (HP) knowledge to investigate the extent to which the availability and timing of information relevant for real-time written word processing are influenced by variation in domain knowledge. We manipulated meaningful (category, event) relationships between sentence fragments about HP stories and their sentence final words. During word-by-word reading, N400 amplitudes to (a) linguistically supported and (b) unsupported but meaningfully related, but not to (c) unsupported, unrelated sentence endings varied with HP domain knowledge. Single-trial analyses revealed that only the N400s to linguistically supported (but not to either type of unsupported) sentence-final words varied as a function of whether individuals knew (or could remember) the correct (supported) ending for each HP "fact." We conclude that the quick availability of information relevant for word understanding in sentences is a function of individuals' knowledge of both specific facts and the domain to which the facts belong. During written sentence processing, as domain knowledge increases, it is clearly evident that individuals can make use of the relevant knowledge systematically organized around themes, events, and categories in that domain, to the extent they have it.

He had it Comin': ERPs Reveal a Facilitation for the Processing of Misfortunes to Antisocial Characters

Human sociality and prosociality rely on social and moral feelings of empathy, compassion, envy, schadenfreude, as well as on the preference for prosocial over antisocial others. We examined the neural underpinnings of the processing of lexical input designed to tap into these type of social feelings. Brainwave responses from 20 participants were measured as they read sentences comprising a randomly delivered ending outcome (fortunate or unfortunate) to social agents previously profiled as prosocial or antisocial individuals. Fortunate outcomes delivered to prosocial and antisocial agents aimed to tap into empathy and envy/annoying feelings, respectively, whereas unfortunate ones into compassion for prosocial agents and schadenfreude for antisocial ones. ERP modulations in early attention-capture (100-200 ms), semantic fit (400 ms), and late reanalysis processes (600 ms) were analyzed. According to the functional interpretation of each of these event-related electrophysiological effects, we conclude that: 1) a higher capture of attention is initially obtained in response to any type of outcome delivered to a prosocial versus an antisocial agent (frontal P2); 2) a facilitated semantic processing occurs for unfortunate outcomes delivered to antisocial agents (N400); and 3) regardless of the protagonist's social profile, an increased later reevaluation for overall unfortunate versus fortunate outcomes takes place (Late Positive Potential). Thus, neural online measures capture a stepwise unfolding impact of social factors during language comprehension, which include a facilitated processing of misfortunes when they happen to occur to antisocial peers (i.e., schadenfreude).

A Tale of Two Positivities and the N400: Distinct Neural Signatures Are Evoked by Confirmed and Violated Predictions at Different Levels of Representation

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, for example, {Agent caution animate-Patient}. High constraint contexts additionally constrained for a specific event/lexical item, for example, 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.

A Tale of Two Positivities and the N400: Distinct Neural Signatures Are Evoked by Confirmed and Violated Predictions at Different Levels of Representation

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, for example, {Agent caution animate-Patient}. High constraint contexts additionally constrained for a specific event/lexical item, for example, 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.

Comprehending surprising sentences: sensitivity of post-N400 positivities to contextual congruity and semantic relatedness

Any proposal for predictive language comprehension must address receipt of less expected information. While a relationship between the N400 and sentence predictability is well established, a clear picture is still emerging of the link between post-N400 positivities (PNPs) and processing of semantically unexpected words, as well as any relation to other not-specifically-linguistic and/or syntactic late positivities. The current study employs event-related brain potentials (ERPs) to congruent and anomalous words to assess the impacts of semantic relatedness and contextual plausibility on processing unpredictable sentences. We observe PNPs with different scalp topographies to plausible unexpected words unrelated to predictable continuations (anterior PNP) and to anomalous words, regardless of, but delayed by, relatedness (posterior PNP). We offer functional explanations that reconcile inconsistencies with reported PNP findings and place added constraints on the anterior PNP's proposed link to inhibitory processing. We also suggest a testable general cognitive account for the posterior PNP.

Thematic roles: Core knowledge or linguistic construct?

The status of thematic roles such as Agent and Patient in cognitive science is highly controversial: To some they are universal components of core knowledge, to others they are scholarly fictions without psychological reality. We address this debate by posing two critical questions: to what extent do humans represent events in terms of abstract role categories, and to what extent are these categories shaped by universal cognitive biases? We review a range of literature that contributes answers to these questions: psycholinguistic and event cognition experiments with adults, children, and infants; typological studies grounded in cross-linguistic data; and studies of emerging sign languages. We pose these questions for a variety of roles and find that the answers depend on the role. For Agents and Patients, there is strong evidence for abstract role categories and a universal bias to distinguish the two roles. For Goals and Recipients, we find clear evidence for abstraction but mixed evidence as to whether there is a bias to encode Goals and Recipients as part of one or two distinct categories. Finally, we discuss the Instrumental role and do not find clear evidence for either abstraction or universal biases to structure instrumental categories.