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.
ERP
The verb “pounce” describes a single, near-instantaneous event. Yet, we easily understand that, “For several minutes the cat pounced…” describes a situation in which multiple pounces occurred, although this interpretation is not overtly specified by the sentence s syntactic structure or by any of its individual words—a phenomenon known as “aspectual coercion.” Previous psycholinguistic studies have reported processing costs in association with aspectual coercion, but the neurocognitive mechanisms giving rise to these costs remain contentious. Additionally, there is some controversy about whether readers commit to a full interpretation of the event when the aspectual information becomes available, or whether they leave it temporarily underspecified until later in the sentence. Using ERPs, we addressed these questions in a design that fully crossed context type (punctive, durative, frequentative) with verb type (punctive, durative). We found a late, sustained negativity to punctive verbs in durative contexts, but not in frequentative (e.g., explicitly iterative) contexts. This effect was distinct from the N400 in both its time course and scalp distribution, suggesting that it reflected a different underlying neurocognitive mechanism. We also found that ERPs to durative verbs were unaffected by context type. Together, our results provide strong evidence that neural activity associated with aspectual coercion is driven by the engagement of a morphosyntactically unrealized semantic operator rather than by violations of real-world knowledge, more general shifts in event representation, or event iterativity itself. More generally, our results add to a growing body of evidence that a set of late-onset sustained negativities reflect elaborative semantic processing that goes beyond simply combining the meaning of individual words with syntactic structure to arrive at a final representation of meaning.
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.
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
We used event-related potentials (ERPs) to examine the interactions between task, emotion, and contextual self-relevance on processing words in social vignettes. Participants read scenarios that were in either third person (other-relevant) or second person (self-relevant) and we recorded ERPs to a neutral, pleasant, or unpleasant critical word. In a previously reported study (Fields and Kuperberg, 2012) with these stimuli, participants were tasked with producing a third sentence continuing the scenario. We observed a larger LPC to emotional words than neutral words in both the self-relevant and other-relevant scenarios, but this effect was smaller in the self-relevant scenarios because the LPC was larger on the neutral words (i.e., a larger LPC to self-relevant than other-relevant neutral words). In the present work, participants simply answered comprehension questions that did not refer to the emotional aspects of the scenario. Here we observed quite a different pattern of interaction between self-relevance and emotion: the LPC was larger to emotional vs. neutral words in the self-relevant scenarios only, and there was no effect of self-relevance on neutral words. Taken together, these findings suggest that the LPC reflects a dynamic interaction between specific task demands, the emotional properties of a stimulus, and contextual self-relevance. We conclude by discussing implications and future directions for a functional theory of the emotional LPC.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
The ability to detect and respond to linguistic errors is critical for successful reading comprehension, but these skills can vary considerably across readers. In the current study, healthy adults (age 18-35) read short discourse scenarios for comprehension while monitoring for the presence of semantic anomalies. Using a factor analytic approach, we examined if performance in nonlinguistic conflict monitoring tasks (Stroop, AX-CPT) would predict individual differences in neural and behavioral measures of linguistic error processing. Consistent with this hypothesis, domain-general conflict monitoring predicted both readers’ end-of-trial acceptability judgments and the amplitude of a late neural response (the P600) evoked by linguistic anomalies. The influence on the P600 was nonlinear, suggesting that online neural responses to linguistic errors are influenced by both the effectiveness and efficiency of domain-general conflict monitoring. These relationships were also highly specific and remained after controlling for variability in working memory capacity and verbal knowledge. Finally, we found that domain-general conflict monitoring also predicted individual variability in measures of reading comprehension, and that this relationship was partially mediated by behavioral measures of linguistic error detection. These findings inform our understanding of the role of domain-general executive functions in reading comprehension, with potential implications for the diagnosis and treatment of language impairments.
We used magnetoencephalography (MEG) and event-related potentials (ERPs) to track the time-course and localization of evoked activity produced by expected, unexpected plausible, and implausible words during incremental language comprehension. We suggest that the full pattern of results can be explained within a hierarchical predictive coding framework in which increased evoked activity reflects the activation of residual information that was not already represented at a given level of the fronto-temporal hierarchy (“error” activity). Between 300 and 500 ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), whereas implausible inputs produced a selectively enhanced response within inferior frontal cortex (prediction error at the level of the event model). Between 600 and 1,000 ms, unexpected plausible words activated left inferior frontal and middle temporal cortices (feedback activity that produced top-down error), whereas highly implausible inputs activated left inferior frontal cortex, posterior fusiform (unsuppressed orthographic prediction error/reprocessing), and medial temporal cortex (possibly supporting new learning). Therefore, predictive coding may provide a unifying theory that links language comprehension to other domains of cognition.
There is an ongoing controversy over whether readers can access the meaning of multiple words, simultaneously. To date, different experimental methods have generated seemingly contradictory evidence in support of serial or parallel processing accounts. For example, dual-task studies suggest that readers can process a maximum of one word at a time (White, Palmer & Boynton, 2018), while ERP studies have demonstrated neural priming effects that are more consistent with parallel activation (Wen, Snell & Grainger, 2019). To help reconcile these views, I measured neural responses and behavioral accuracy in a dual-task sentence comprehension paradigm. Participants saw masked sentences and two-word phrases and had to judge whether or not they were grammatical. Grammatically correct sentences (This girl is neat) produced smaller N400 responses compared to scrambled sentences (Those girl is fled): an N400 sentence superiority effect. Critically, participants’ grammaticality judgements on the same trials showed striking capacity limitations, with dual-task deficits closely matching the predictions of a serial, all-or-none processing account. Together, these findings suggest that the N400 sentence superiority effect is fully compatible with serial word recognition, and that readers are unable to process multiple sentence positions simultaneously.
To comprehend language, we continually use prior context to pre-activate expected upcoming information, resulting in facilitated processing of incoming words that confirm these predictions. But what are the consequences of disconfirming prior predictions? To address this question, most previous studies have examined unpredictable words appearing in contexts that constrain strongly for a single continuation. However, during natural language processing, it is far more common to encounter contexts that constrain for multiple potential continuations, each with some probability. Here, we ask whether and how pre-activating both higher and lower probability alternatives influences the processing of the lower probability incoming word. One possibility is that, similar to language production, there is continuous pressure to select the higher-probability pre-activated alternative through competitive inhibition. During comprehension, this would result in relative costs in processing the lower probability target. A second possibility is that if the two pre-activated alternatives share semantic features, they mutually enhance each other’s pre-activation. This would result in greater facilitation in processing the lower probability target. To distinguish between these accounts, we recorded ERPs as participants read three-sentence scenarios that constrained either for a single word or for two potential continuations – a higher probability expected candidate and a lower probability second-best candidate. We found no evidence that competitive pre-activation between the expected and second-best candidates resulted in costs in processing the second-best target, either during lexico-semantic processing (indexed by the N400) or at later stages of processing (indexed by a later frontal positivity). Instead, we found only benefits of pre-activating multiple alternatives, with evidence of enhanced graded facilitation on lower-probability targets that were semantically related to a higher-probability pre-activated alternative. These findings are consistent with a previous eye-tracking study by Luke and Christianson (2016, Cogn Psychol) using corpus-based materials. They have significant theoretical implications for models of predictive language processing, indicating that routine graded prediction in language comprehension does not operate through the same competitive mechanisms that are engaged in language production. Instead, our results align more closely with hierarchical probabilistic accounts of language comprehension, such as predictive coding.