Downstream Behavioral and Electrophysiological Consequences of Word Prediction on Recognition Memory

How predictability and individual alpha frequency shape memory: Insights from an event-related potential investigation

Prediction and memory are strongly intertwined, with predictions relying on memory retrieval, whilst also influencing memory encoding. However, it is unclear how predictability influences explicit memory performance, and how individual neural factors may modulate this relationship. The current study sought to investigate the effect of predictability on memory processing with an analysis of the N400 event-related potential in a context extending beyond language. Participants (N = 48, females = 33) completed a study-test paradigm where they first viewed predictable and unpredictable four-item 'ABCD' sequences of outdoor scene images, whilst their brain activity was recorded using electroencephalography. Subsequently, their memory for the images was tested, and N400 patterns during learning were compared with memory outcomes. Behavioural results revealed better memory for images in predictable sequences in contrast to unpredictable sequences. Memory was also strongest for predictable images in the 'B' position, suggesting that when processing longer sequences, the brain may prioritise the data deemed most informative. Strikingly, greater N400 amplitudes during learning were associated with enhanced memory at test for individuals with low versus high individual alpha frequencies. In light of the relationship between the N400 and stimulus predictability, this finding may imply that predictive processing differs between individuals to influence the extent of memory encoding. Finally, exploratory analyses provided evidence for a later positivity that was predictive of subsequent memory performance. Ultimately, the results highlight the complex and interconnected relationship between predictive processing and memory, whilst shedding light on the accumulation of predictions across longer sequences.

The effects of prediction representations on implicit learning: Evidence from sentence reading and perceptual identification

Predicting errors can facilitate implicit learning, but the long-term consequences of prediction errors are not yet fully understood. Especially when predictions are disconfirmed, it remains unclear whether initially correct prediction representations persist or are suppressed. In this study, participants first engaged in a sentence reading task and then performed a perceptual identification task after completing an N-back task or after a 24-h delay. The perceptual identification task presented previously expected and unexpected words and previously predicted but not presented words to measure implicit memory for the critical items. This study aims to investigate the mechanisms underlying the persistence of prediction representations and the long-term effects of prediction errors on implicit learning. Our results indicate that prediction errors can promote implicit learning and can persist for more than 24 h. Furthermore, originally correct but not seen in reality prediction representations persist to facilitate performance on the implicit memory task after 24 h. This may reflect long-term changes in the internal representation probabilities of prediction representations.

Prediction in reading: A review of predictability effects, their theoretical implications, and beyond

Historically, prediction during reading has been considered an inefficient and cognitively expensive processing mechanism given the inherently generative nature of language, which allows upcoming text to unfold in an infinite number of possible ways. This article provides an accessible and comprehensive review of the psycholinguistic research that, over the past 40 or so years, has investigated whether readers are capable of generating predictions during reading, typically via experiments on the effects of predictability (i.e., how well a word can be predicted from its prior context). Five theoretically important issues are addressed: What is the best measure of predictability? What is the functional relationship between predictability and processing difficulty? What stage(s) of processing does predictability affect? Are predictability effects ubiquitous? What processes do predictability effects actually reflect? Insights from computational models of reading about how predictability manifests itself to facilitate the reading of text are also discussed. This review concludes by arguing that effects of predictability can, to a certain extent, be taken as demonstrating evidence that prediction is an important but flexible component of real-time language comprehension, in line with broader predictive accounts of cognitive functioning. However, converging evidence, especially from concurrent eye-tracking and brain-imaging methods, is necessary to refine theories of prediction.

Looking for immediate and downstream evidence of lexical prediction in eye movements during reading

Previous investigations of whether readers make predictions about the full identity of upcoming words have focused on the extent to which there are processing consequences when readers encounter linguistic input that is incompatible with their expectations. To date, eye-movement studies have revealed inconsistent evidence of the processing costs that would be expected to accompany lexical prediction. This study investigated whether readers' lexical predictions were observable during or downstream from their initial point of activation. Three experiments assessed readers' eye movements to predictable and unpredictable words, and then to subsequent downstream words, which probed the lingering activation of previously expected words. The results showed novel evidence of processing costs for unexpected input but only when supported by a plausible linguistic environment, suggesting that readers could strategically modulate their predictive processing. However, there was limited evidence that their lexical predictions affected downstream processing. The implications of these findings for understanding the role of prediction in language processing are discussed.

Temporary ambiguity and memory for the context of spoken language in adults with moderate-severe traumatic brain injury

Language is processed incrementally, with addressees considering multiple candidate interpretations as speech unfolds, supporting the retention of these candidate interpretations in memory. For example, after interpreting the utterance, "Click on the striped bag", listeners exhibit better memory for non-mentioned items in the context that were temporarily consistent with what was said (e.g., dotted bag), vs. not consistent (e.g., dotted tie), reflecting the encoding of linguistic context in memory. Here, we examine the impact of moderate-severe traumatic brain injury (TBI) on memory for the contexts of language use. Participants with moderate-severe TBI (N=71) and non-injured comparison participants (NC, N=85) interpreted temporarily ambiguous utterances in rich contexts. A subsequent memory test demonstrated that participants with TBI exhibited impaired memory for context items and an attenuated memory advantage for mentioned items compared to NC participants. Nonetheless, participants with TBI showed similar, although attenuated, patterns in memory for temporarily-activated items as NC participants.

The late positive event-related potential component is time locked to the decision in recognition memory tasks

Two event-related potential (ERP) components are commonly observed in recognition memory tasks: the Frontal Negativity (FN400) and the Late Positive Component (LPC). These components are widely interpreted as neural correlates of familiarity and recollection, respectively. However, the interpretation of LPC effects is complicated by inconsistent results regarding the timing of ERP amplitude differences. There are also mixed findings regarding how LPC amplitudes covary with decision confidence. Critically, LPC effects have almost always been measured using fixed time windows relative to memory probe stimulus onset, yet it has not been determined whether LPC effects are time locked to the stimulus or the recognition memory decision. To investigate this, we analysed a large (n = 132) existing dataset recorded during recognition memory tasks with old/new decisions followed by post-decisional confidence ratings. We used ERP deconvolution to disentangle contributions to LPC effects (defined as differences between hits and correct rejections) that were time locked to either the stimulus or the vocal old/new response. We identified a left-lateralised parietal LPC effect that was time locked to the vocal response rather than probe stimulus onset. We also isolated a response-locked, midline parietal ERP correlate of confidence that influenced measures of LPC amplitudes at left parietal electrodes. Our findings demonstrate that, contrary to widespread assumptions, the LPC effect is time locked to the recognition memory decision and is best measured using response-locked ERPs. By extension, differences in response time distributions across conditions of interest may lead to substantial measurement biases when analysing stimulus-locked ERPs. Our findings highlight important confounding factors that further complicate the interpretation of existing stimulus-locked LPC effects as neural correlates of recollection. We recommend that future studies adopt our analytic approach to better isolate LPC effects and their sensitivity to manipulations in recognition memory tasks.

On the Mathematical Relationship Between Contextual Probability and N400 Amplitude

Accounts of human language comprehension propose different mathematical relationships between the contextual probability of a word and how difficult it is to process, including linear, logarithmic, and super-logarithmic ones. However, the empirical evidence favoring any of these over the others is mixed, appearing to vary depending on the index of processing difficulty used and the approach taken to calculate contextual probability. To help disentangle these results, we focus on the mathematical relationship between corpus-derived contextual probability and the N400, a neural index of processing difficulty. Specifically, we use 37 contemporary transformer language models to calculate the contextual probability of stimuli from 6 experimental studies of the N400, and test whether N400 amplitude is best predicted by a linear, logarithmic, super-logarithmic, or sub-logarithmic transformation of the probabilities calculated using these language models, as well as combinations of these transformed metrics. We replicate the finding that on some datasets, a combination of linearly and logarithmically-transformed probability can predict N400 amplitude better than either metric alone. In addition, we find that overall, the best single predictor of N400 amplitude is sub-logarithmically-transformed probability, which for almost all language models and datasets explains all the variance in N400 amplitude otherwise explained by the linear and logarithmic transformations. This is a novel finding that is not predicted by any current theoretical accounts, and thus one that we argue is likely to play an important role in increasing our understanding of how the statistical regularities of language impact language comprehension.

Error-based Implicit Learning in Language: The Effect of Sentence Context and Constraint in a Repetition Paradigm

Prediction errors drive implicit learning in language, but the specific mechanisms underlying these effects remain debated. This issue was addressed in an EEG study manipulating the context of a repeated unpredictable word (repetition of the complete sentence or repetition of the word in a new sentence context) and sentence constraint. For the manipulation of sentence constraint, unexpected words were presented either in high-constraint (eliciting a precise prediction) or low-constraint sentences (not eliciting any specific prediction). Repetition-induced reduction of N400 amplitudes and of power in the alpha/beta frequency band was larger for words repeated with their sentence context as compared with words repeated in a new low-constraint context, suggesting that implicit learning happens not only at the level of individual items but additionally improves sentence-based predictions. These processing benefits for repeated sentences did not differ between constraint conditions, suggesting that sentence-based prediction update might be proportional to the amount of unpredicted semantic information, rather than to the precision of the prediction that was violated. In addition, the consequences of high-constraint prediction violations, as reflected in a frontal positivity and increased theta band power, were reduced with repetition. Overall, our findings suggest a powerful and specific adaptation mechanism that allows the language system to quickly adapt its predictions when unexpected semantic information is processed, irrespective of sentence constraint, and to reduce potential costs of strong predictions that were violated.

It takes a village: A multi-brain approach to studying multigenerational family communication

Grandparents play a critical role in child rearing across the globe. Yet, there is a shortage of neurobiological research examining the relationship between grandparents and their grandchildren. We employ multi-brain neurocomputational models to simulate how changes in neurophysiological processes in both development and healthy aging affect multigenerational inter-brain coupling - a neural marker that has been linked to a range of socio-emotional and cognitive outcomes. The simulations suggest that grandparent-child interactions may be paired with higher inter-brain coupling than parent-child interactions, raising the possibility that the former may be more advantageous under certain conditions. Critically, this enhancement of inter-brain coupling for grandparent-child interactions is more pronounced in tri-generational interactions that also include a parent, which may speak to findings that grandparent involvement in childrearing is most beneficial if the parent is also an active household member. Together, these findings underscore that a better understanding of the neurobiological basis of cross-generational interactions is vital, and that such knowledge can be helpful in guiding interventions that consider the whole family. We advocate for a community neuroscience approach in developmental social neuroscience to capture the diversity of child-caregiver relationships in real-world settings.

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.

The Impact of Linguistic Prediction Violations on Downstream Recognition Memory and Sentence Recall

Predicting upcoming words during language comprehension not only affects processing in the moment but also has consequences for memory, although the source of these memory effects (e.g., whether driven by lingering pre-activations, re-analysis following prediction violations, or other mechanisms) remains underspecified. Here, we investigated downstream impacts of prediction on memory in two experiments. First, we recorded EEG as participants read strongly and weakly constraining sentences with expected, unexpected but plausible, or semantically anomalous endings ("He made a holster for his gun / father / train") and were tested on their recognition memory for the sentence endings. Participants showed similar rates of false alarms for predicted but never presented sentence endings whether the prediction violation was plausible or anomalous, suggesting that these arise from pre-activation of the expected words during reading. During sentence reading, especially in strongly constraining sentences, plausible prediction violations elicited an anterior positivity; anomalous endings instead elicited a posterior positivity, whose amplitude was predictive of later memory for those anomalous words. ERP patterns at the time of recognition differentiated plausible and anomalous sentence endings: Words that had been plausible prediction violations elicited enhanced late positive complex amplitudes, suggesting greater episodic recollection, whereas anomalous sentence endings elicited greater N1 amplitudes, suggesting attentional tagging. In a follow-up behavioral study, a separate group of participants read the same sentence stimuli and were tested for sentence-level recall. We found that recall of full sentences was impaired when sentences ended with a prediction violation. Taken together, the results suggest that prediction violations draw attention and affect encoding of the violating word, in a manner that depends on plausibility, and that this, in turn, may impair future memory of the gist of the sentence.

Context-specific effects of violated expectations: ERP evidence

A complete understanding of the predictive processing effect in sentence comprehension needs to understand both the facilitation effect of successful prediction and the cost associated with disconfirmed predictions. The current study compares the predictive processing effect across two types of contexts in Mandarin Chinese: the classifier-noun vs. verb-noun phrases, when controlling for the degree of contextual constraints and cloze probability of the target nouns across the two contexts. The two contexts showed similar N400 patterns for expected target nouns, indicative of an identical facilitation effect of confirmed contextual expectation. But in the post-N400 time window, the processing cost associated with the unexpected words differed between the two contexts. Additional differences between the two contexts were also revealed by the neural oscillation patterns obtained prior to the target noun. The differences between the classifier vs. verb contexts shed new light on the revision mechanism that deals with disconfirmed expectations.

Multiple predictions during language comprehension: Friends, foes, or indifferent companions?

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.

Prediction during language comprehension: what is next?

Prediction is often regarded as an integral aspect of incremental language comprehension, but little is known about the cognitive architectures and mechanisms that support it. We review studies showing that listeners and readers use all manner of contextual information to generate multifaceted predictions about upcoming input. The nature of these predictions may vary between individuals owing to differences in language experience, among other factors. We then turn to unresolved questions which may guide the search for the underlying mechanisms. (i) Is prediction essential to language processing or an optional strategy? (ii) Are predictions generated from within the language system or by domain-general processes? (iii) What is the relationship between prediction and memory? (iv) Does prediction in comprehension require simulation via the production system? We discuss promising directions for making progress in answering these questions and for developing a mechanistic understanding of prediction in language.

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.

The Development of Predictive Gender Processing Strategies During Noun Phrase Decoding: An Eye-Tracking Study With German 5- to 10-Year-Old Children

PURPOSE

Many models of language comprehension assume that listeners predict the continuation of an incoming linguistic stimulus immediately after its onset, based on only partial linguistic and contextual information. Their related developmental models try to determine which cues (e.g., semantic or morphosyntactic) trigger such prediction, and to which extent, during different periods of language acquisition. One morphosyntactic cue utilized predictively in many languages, inter alia German, is grammatical gender. However, studies of the developmental trajectories of the acquisition of predictive gender processing in German remain a few.

METHOD

This study attempts to shed light on such processing strategies used in noun phrase decoding among children acquiring German as their first language by examining their eye movements during a language-picture matching task (N = 78, 5-10 years old). Its aim was to confirm whether the eye movements indicated the presence of age-specific differences in the processing of a gender cue, provided either in isolation or in combination with a semantic cue.

RESULTS

The results revealed that German children made use of predictive gender processing strategies from the age of 5 years onward; however, the pace of online gender processing, as well as confidence in the predicted continuation, increased up to the age of 10 years.

CONCLUSION

Predictive processing of gender cues plays a role in German language comprehension even in children younger than 8 years.

Observing memory encoding while it unfolds: Functional interpretation and current debates regarding ERP subsequent memory effects

Our ability to remember the past depends on neural processes set in train in the moment an event is experienced. These processes can be studied by segregating brain activity according to whether an event is later remembered or forgotten. The present review integrates a large number of studies examining this differential brain activity, labeled subsequent memory effect (SME), with the ERP technique, into a functional organization and discusses routes for further research. Based on the reviewed literature, we suggest that memory encoding is implemented by multiple processes, typically reflected in three functionally different subcomponents of the ERP SME elicited by study stimuli, which presumably interact with preparatory SME activity preceding the to be encoded event. We argue that ERPs are a valuable method in the SME paradigm because they have a sufficiently high temporal resolution to disclose the subcomponents of encoding-related brain activity. Implications of the proposed functional organization for future studies using the SME procedure in basic and applied settings will be discussed.

Read carefully, because this is important! How value-driven strategies impact sentence memory

Little is understood about how people strategically process and remember important but complex information, such as sentences. In the current study, we asked whether people can effectively prioritize memory for sentences as a function of their relative importance (operationalized as a reward point value) and whether they do so, in part, by changing their sentence processing strategies when value information is available in advance. We adapted the value-directed remembering paradigm (Castel, Psychol Learn Motiv 48:225-270, 2007) for sentences that varied in constraint and predictability. Each sentence was associated with a high or low value for subsequent free recall (whole sentence) and recognition (sentence-final words) tests. Value information appeared after or before each sentence as a between-subject manipulation. Regardless of condition, we observed that high-value sentences were recalled more often than low-value sentences, showing that people can strategically prioritize their encoding of sentences. However, memory patterns differed depending on when value information was available. Recall for high-value sentences that ended unexpectedly (and therefore violated one's predictions) was reduced in the Before compared to the After condition. Before condition participants also showed a greater tendency to false alarm to lures (words that were the predicted - but not obtained - ending) from strongly constraining sentences. These observations suggest that when people try to prioritize sentence-level information that they know is valuable, the reading strategies they employ may paradoxically lead to worse memory.

Readers scrutinize lexical familiarity only in the absence of expectations: Evidence from lexicality effects on event-related potentials

Readers generate predictions about the meaning of upcoming words while reading constraining sentences. These predictions feed down to predictions about orthographic form. For example, orthographic neighbors of predicted words yield reduced N400 amplitudes compared to non-neighbors regardless of lexical status (Laszlo & Federmeier, 2009). We investigated whether readers are sensitive to lexicality in low constraint sentences when they must scrutinize the perceptual input more closely for word recognition. In a replication and extension of Laszlo and Federmeier (2009), we observed similar patterns as the original study in high constraint sentences, but found a lexicality effect in low constraint sentences that was not present when the sentence was highly constraining. This suggests that, in the absence of strong expectations, readers adopt a different reading strategy to scrutinize the structure of words more in depth to make sense of what they have read compared to when they encounter a supportive sentence context.

The power of "good": Can adjectives rapidly decrease as well as increase the availability of the upcoming noun?

Can a single adjective immediately influence message-building during sentence processing? We presented participants with 168 sentence contexts, such as "His skin was red from spending the day at the …" Sentences ended with either the most expected word ("beach") or a low cloze probability completion ("pool"). Nouns were preceded by adjectives that changed their relative likelihood (e.g., "neighborhood" increases the cloze probability of pool whereas "sandy" promotes beach). We asked if participants' online processing can be rapidly updated by the adjective, changing the resulting pattern of facilitation at the noun, and, if so, whether updates unfold symmetrically-not only increasing, but also decreasing, the fit of particular nouns. We measured event-related potentials (ERPs) to the adjective and the noun and modeled these with respect to (a) the overall amount of updating promoted by the adjective, (b) the preadjectival cloze probability of the noun and, (c) the amount of cloze probability change for the obtained noun after the adjective. Bayesian mixed-effects analysis of N400 amplitude at the noun revealed that adjectives rapidly influenced semantic processing of the noun, but did so asymmetrically, with positive updating (reducing N400 amplitudes) having a greater effect than negative updating (increasing N400s). At the adjective, the amount of (possible) updating was not associated with any discernible ERP modulation. Overall, these results suggest the information provided by adjectives is buffered until a head noun is encountered, at which point the access of the noun's semantics is shaped in parallel by both the adjective and the sentence-level representation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Context-based facilitation of semantic access follows both logarithmic and linear functions of stimulus probability

Stimuli are easier to process when context makes them predictable, but does context-based facilitation arise from preactivation of a limited set of relatively probable upcoming stimuli (with facilitation then linearly related to probability) or, instead, because the system maintains and updates a probability distribution across all items (with facilitation logarithmically related to probability)? We measured the N400, an index of semantic access, to words of varying probability, including unpredictable words. Word predictability was measured using both cloze probabilities and a state-of-the-art machine learning language model (GPT-2). We reanalyzed five datasets (n = 138) to demonstrate and then replicate that context-based facilitation on the N400 is graded, even among unpredictable words. Furthermore, we established that the relationship between word predictability and context-based facilitation combines linear and logarithmic functions. We argue that this composite function reveals properties of the mapping between words and semantic features and how feature- and word-related information is activated on-line.

Temporary ambiguity and memory for the context of spoken language

Spoken language is interpreted incrementally, with listeners considering multiple candidate meanings as words unfold over time. Due to incremental interpretation, when a speaker refers to something in the world, there is often temporary ambiguity regarding which of several candidate items in the referential context the speaker is referring to. Subsequent tests of recognition memory show that listeners have good memory for referenced items, but that listeners also sometimes recognize non-referenced items from the referential context that share features with items that were mentioned. Predicted or inferred (but not experienced) interpretations of what was said are also sometimes retained in memory. While these findings indicate that multiple items from the referential context may be encoded in memory, the mechanisms supporting memory for the context of language use remain poorly understood. This paper tests the hypothesis that a consequence of temporary ambiguity in spoken language is enhanced memory for the items in the referential context. Two experiments demonstrate that periods of temporary referential ambiguity boost memory for non-referenced items in the referential context. Items that temporarily matched the unfolding referring expression were better remembered than those that did not. The longer the period of ambiguity, the stronger the memory boost, particularly for items activated early in the expression. In sum, the fact that spoken language unfolds over time creates momentary ambiguity about the speaker's intention; this ambiguity, in turn, allows the listener to later remember not only what the speaker did say, but also what they could have, but did not.

Age-related Changes in the Structure and Dynamics of the Semantic Network

Normal aging has variable effects on language comprehension, perhaps because comprehension mechanisms vary in their dependence on network structure versus network dynamics. To test claims that processing dynamics are more affected by age than structure, we used EEG to measure and compare the impact of neighborhood size, a core measure of the structure of the lexico-semantic network, and repetition, a simple measure of processing dynamics, on single word processing. Older adults showed robust effects of neighborhood size on the N400, comparable to those elicited by young adults, but reduced effects of repetition. Furthermore, older adults with greater verbal fluency, print exposure, and reading comprehension showed greater repetition effects, suggesting some older adults can maintain processing dynamics that are similar to those of young adults. Thus, the organizational structure of the semantic network seems stable across normal aging, but (some) older adults may struggle to adjust activation states within that network.

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.

The N400 ERP component reflects an error-based implicit learning signal during language comprehension

The functional significance of the N400 evoked-response component is still actively debated. An increasing amount of theoretical and computational modelling work is built on the interpretation of the N400 as a prediction error. In neural network modelling work, it was proposed that the N400 component can be interpreted as the change in a probabilistic representation of meaning that drives the continuous adaptation of an internal model of the statistics of the environment. These results imply that increased N400 amplitudes should correspond to greater adaptation, which can be measured via implicit memory. To investigate this model derived hypothesis, the current study manipulated expectancy in a sentence reading task to influence N400 amplitudes and subsequently presented the previously expected vs. unexpected words in a perceptual identification task to measure implicit memory. As predicted, reaction times in the perceptual identification task were significantly faster for previously unexpected words that induced larger N400 amplitudes in the previous sentence reading task. Additionally, it could be demonstrated that this adaptation seems to specifically depend on the process underlying N400 amplitudes, as participants with larger N400 differences during sentence reading also exhibited a larger implicit memory benefit in the perceptual identification task. These findings support the interpretation of the N400 as an implicit learning signal driving adaptation in language processing.

Dividing attention influences contextual facilitation and revision during language comprehension

Although we often seem to successfully comprehend language in the face of distraction, few studies have examined the role of sustained attention in critical components of sentence processing, such as integrating information over a sentence and revising predictions when unexpected information is encountered. The current study investigated the impact of attention on sentence processing using a novel dual-task paradigm. Participants read weakly and strongly constraining sentences with expected or unexpected endings while also tracking the motion of dots in the background, and their EEG was recorded. Under full attention, the amplitude of the N400 component of the ERP, a measure of semantic access, was reduced (facilitated) in a graded fashion by contextual strength and fit. This context-based facilitation was attenuated when attention was divided, suggesting that sustained attention is important for building up message-level representations. In contrast, the post-N400 frontal positivity that has been observed to prediction violations and associated with revision processes was unaffected by dividing attention. However, under divided attention, participants also elicited posteriorly-distributed effects to these violations. Thus, predictive processes seem to be engaged even when attention is divided, but additional resources may then be required to process unexpected information.

Representational Pattern Similarity of Electrical Brain Activity Reveals Rapid and Specific Prediction during Language Comprehension

Predicting upcoming events is a critical function of the brain, and language provides a fertile testing ground for studying prediction, as comprehenders use context to predict features of upcoming words. Many aspects of the mechanisms of prediction remain elusive, partly due to a lack of methodological tools to probe prediction formation in the moment. To elucidate what features are neurally preactivated and when, we used representational similarity analysis on previously collected sentence reading data. We compared EEG activity patterns elicited by expected and unexpected sentence final words to patterns from the preceding words of the sentence, in both strongly and weakly constraining sentences. Pattern similarity with the final word was increased in an early time window following the presentation of the pre-final word, and this increase was modulated by both expectancy and constraint. This was not seen at earlier words, suggesting that predictions were precisely timed. Additionally, pre-final word activity-the predicted representation-had negative similarity with later final word activity, but only for strongly expected words. These findings shed light on the mechanisms of prediction in the brain: rapid preactivation occurs following certain cues, but the predicted features may receive reduced processing upon confirmation.

The fate of the unexpected: Consequences of misprediction assessed using ERP repetition effects

Amid increasing interest in the role of prediction in language comprehension, there remains a gap in our understanding of what happens when predictions are disconfirmed. Are unexpected words harder to process and encode because of interference from the original prediction? Or, because of their relevance for learning, do expectation violations strengthen the representations of unexpected words? In two experiments, we used event-related potentials to probe the downstream consequences of prediction violations. Critical words were unexpected but plausible completions of either strongly constraining sentences, wherein they constituted a prediction violation, or weakly constraining sentences that did not afford a clear prediction. Three sentences later the critical word was repeated at the end of a different, weakly constraining sentence. In Experiment 1, repeated words elicited a reduced N400 and an enhanced late positive complex (LPC) compared to words seen for the first time. Critically, there was no effect of initial sentence constraint on the size of the repetition effect in either time window. Thus, prediction violations did not accrue either costs or benefits for later processing. Experiment 2 used the same critical items and added strongly constraining filler sentences with expected endings to further promote prediction. Again, there was no effect of initial sentence constraint on either the N400 or the LPC to repeated critical words. When taken with prior findings, the results suggest that prediction is both powerful and flexible: It can facilitate processing of predictable information by reducing encoding effort without causing processing difficulties for unexpected inputs.

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.