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Prior research on the neural bases of syntactic comprehension suggests that activation in the left inferior frontal gyrus (lIFG) correlates with the processing of word order variations. However, there are inconsistencies with respect to the specific subregion within the IFG that is implicated by these findings: the pars opercularis or the pars triangularis. Here, we examined the hypothesis that the dissociation between pars opercularis and pars triangularis activation may reflect functional differences between clause-medial and clause-initial word order permutations, respectively. To this end, we directly compared clause-medial and clause-initial object-before-subject orders in German in a within-participants, event-related fMRI design. Our results showed increased activation for object-initial sentences in a bilateral network of frontal, temporal and subcortical regions. Within the lIFG, posterior and inferior subregions showed only a main effect of word order, whereas more anterior and superior subregions showed effects of word order and sentence type, with higher activation for sentences with an argument in the clause-initial position. These findings are interpreted as evidence for a functional gradation of sequence processing within the left IFG: posterior subportions correlate with argument prominence-based (local) aspects of sequencing, while anterior subportions correlate with aboutness-based aspects of sequencing, which are crucial in linking the current sentence to the wider discourse. This proposal appears compatible with more general hypotheses about information processing gradients in prefrontal cortex (Koechlin & Summerfield, 2007).Copyright © 2012 by Elsevier Inc. [ABSTRACT FROM AUTHOR]

It has often been suggested that the role of Broca's region in sentence comprehension can be explained with reference to general cognitive mechanisms (e.g. working memory, cognitive control). However, the (language-related) basis for such proposals is often restricted to findings on English. Here, we argue that an extension of the database to other languages can shed new light on the types of mechanisms that an adequate account of Broca's region should be equipped to deal with. This becomes most readily apparent in the domain of word order variations, which we examined in German verb-final sentences using event-related fMRI. Our results showed that activation in the pars opercularis - a core subregion of Broca's area - was not only modulated by the relative ordering of subject and object, but also by a further factor known to affect word order in a number of languages, namely referentiality. Notably, the finding provides the first demonstration of a word order-related activation difference within subject-initial sentences in this region. Additional parametric analyses using individual behavioral data as predictors further attest to the independence of the pars opercularis activation from: (a) sentence acceptability, and (b) difficulty in performing the experimental (judgment) task. We argue that these and related findings attest to the need for a processing mechanism that can manipulate predicate-independent, interacting and hierarchically structured relational representations during real time comprehension. These properties pose a challenge to existing accounts of pars opercularis function.Copyright © 2009 by Elsevier Inc. [ABSTRACT FROM AUTHOR]

In two visual ERP studies, we investigated whether Mandarin Chinese shows a subject-preference in spite of the controversial status of grammatical relations in this language. We compared ERP responses at the position of the verb and the second NP in object-verb-subject (OVS) and subject-verb-object (SVO) structures. While SVO is the basic word order in Chinese and OV with subject-drop is possible, OVS is strongly dispreferred. At the position of the verb, which disambiguated towards an object or a subject reading of NP1, Experiment 1 revealed an N400 for both subject-initial control conditions in comparison with the critical object-initial condition. Experiment 2 showed that this result was due to differences in lexical-semantic relatedness between NP1 and the verb. When these were controlled for, we observed an N400 for the disambiguation towards an object-initial order, i.e., evidence for a subject-preference. At the postverbal NP, the object-initial condition showed a biphasic N400-late positivity pattern in both experiments. We interpret the N400 as reflecting the processing of an unexpected argument and the late positivity as a correlate of a well-formedness mismatch. Overall, our results suggest that Mandarin Chinese shows a subject-preference for an initial argument, thus providing further converging support for the notion that the subject-preference might constitute a universal processing strategy. We argue that the functional basis for this strategy lies in cross-linguistically applicable economy principles that serve to constrain incremental interpretation. [ABSTRACT FROM AUTHOR]

This paper examines the hypothesis that grammatical function reanalyses in simple sentences should not be treated as phrase structure revisions, but rather as increased costs in 'linking' an argument from a syntactic to a semantic representation. To this end, we investigated whether subjectDSobject reanalyses in German verb-final sentences can be associated with an electrophysiological processing signature that is distinct from the response typically engendered by structure-affecting reanalyses (the P600). We hypothesized that the previously observed heterogeneous ERP component pattern for subject-object reanalyses in German might be due to task- or strategy-related interactions between the critical processing mechanisms and the experimental environment. In order to minimize specific task influences, Experiment 1 therefore embedded subject--object ambiguities into short stories (presented auditorily). Constructions with dative and accusative objects both showed a biphasic N400-late positivity pattern for disambiguation towards an object-initial structure. These results thus contrast with previous findings, in showing that there is no principled difference in the component pattern for the two types of structures. This conclusion was confirmed by the results of Experiment 2, which presented the identical accusative sentences from Experiment 1 in isolation using two different tasks (comprehension vs. acceptability) and again revealed N400-late positivity responses. From the overall data pattern, we conclude that the N400 is a robust correlate of grammatical function reanalysis that occurs independently of any lexical factors and, consequently, that grammatical function reanalysis is functionally distinct from phrase structure reanalysis. [ABSTRACT FROM AUTHOR]

Background: Mindfulness training (MT) programs have demonstrated utility as cognitive training tools, but there is little consensus on the neurophysiological processes that may underlie its benefits. It has been posited that intrinsic brain activity recorded at rest reflects the functional connectivity of large-scale brain networks and may provide insight into neuroplastic changes that support MT. In the current study, we indexed changes in several resting-state electroencephalography (EEG) parameters to investigate the neurophysiological underpinnings of MT., Methods: Resting-state EEG data were collected from active-duty U.S. military personnel ( N  = 80) at 2 testing sessions: before (time [T] 1) and after (T2) engaging in an 8-week MT or active comparison intervention (positivity training). We examined longitudinal and/or groupwise differences in several EEG parameters through parameterization of power spectra (individual alpha frequency and 1/ f activity) and microstate analysis., Results: While no significant group × time differences were observed in individual alpha frequency, significant group × time effects were observed in several EEG parameters from T1 to T2. Compared with MT, positivity training was associated with a steepening of the 1/ f slope and higher 1/ f intercepts together with decreased duration and increased global field power of microstates., Conclusions: Taken together, these results suggest that the effects of interventions may be differentiated in resting-state brain activity in a sample of military personnel. Such findings provide insight into the neural underpinnings of MT-related brain changes, but more research is required to elucidate how these may relate to task-related neural and performance changes with MT and whether results generalize to other mindfulness interventions in alternative cohorts and contexts., (© 2024 The Authors.)

The extent to which the brain predicts upcoming information during language processing remains controversial. To shed light on this debate, the present study reanalyzed Nieuwland and colleagues' (2018) [Nieuwland, M. S., Politzer-Ahles, S., Heyselaar, E., Segaert, K., Darley, E., Kazanina, N., et al. Large-scale replication study reveals a limit on probabilistic prediction in language comprehension. eLife, 7, e33468, 2018] replication of DeLong and colleagues (2015) [DeLong, K. A., Urbach, T. P., & Kutas, M. Probabilistic word pre-activation during language comprehension inferred from electrical brain activity. Nature Neuroscience, 8, 1117-1121, 2005]. Participants (n = 356) viewed sentences containing articles and nouns of varying predictability, while their EEG was recorded. We measured ERPs preceding the critical words (namely, the semantic prediction potential), in conjunction with postword N400 patterns and individual neural metrics. ERP activity was compared with two measures of word predictability: cloze probability and lexical surprisal. In contrast to prior literature, semantic prediction potential amplitudes did not increase as cloze probability increased, suggesting that the component may not reflect prediction during natural language processing. Initial N400 results at the article provided evidence against phonological prediction in language, in line with Nieuwland and colleagues' findings. Strikingly, however, when the surprisal of the prior words in the sentence was included in the analysis, increases in article surprisal were associated with increased N400 amplitudes, consistent with prediction accounts. This relationship between surprisal and N400 amplitude was not observed when the surprisal of the two prior words was low, suggesting that expectation violations at the article may be overlooked under highly predictable conditions. Individual alpha frequency also modulated the relationship between article surprisal and the N400, emphasizing the importance of individual neural factors for prediction. The present study extends upon existing neurocognitive models of language and prediction more generally, by illuminating the flexible and subject-specific nature of predictive processing., (© 2024 Massachusetts Institute of Technology.)

Human performance applications of mindfulness-based training have demonstrated its utility in enhancing cognitive functioning. Previous studies have illustrated how these interventions can improve performance on traditional cognitive tests, however, little investigation has explored the extent to which mindfulness-based training can optimise performance in more dynamic and complex contexts. Further, from a neuroscientific perspective, the underlying mechanisms responsible for performance enhancements remain largely undescribed. With this in mind, the following study aimed to investigate how a short-term mindfulness intervention (one week) augments performance on a dynamic and complex task (target motion analyst task; TMA) in young, healthy adults (n = 40, age range = 18-38). Linear mixed effect modelling revealed that increased adherence to the web-based mindfulness-based training regime (ranging from 0-21 sessions) was associated with improved performance in the second testing session of the TMA task, controlling for baseline performance. Analyses of resting-state electroencephalographic (EEG) metrics demonstrated no change across testing sessions. Investigations of additional individual factors demonstrated that enhancements associated with training adherence remained relatively consistent across varying levels of participants' resting-state EEG metrics, personality measures (i.e., trait mindfulness, neuroticism, conscientiousness), self-reported enjoyment and timing of intervention adherence. Our results thus indicate that mindfulness-based cognitive training leads to performance enhancements in distantly related tasks, irrespective of several individual differences. We also revealed nuances in the magnitude of cognitive enhancements contingent on the timing of adherence, regardless of total volume of training. Overall, our findings suggest that mindfulness-based training could be used in a myriad of settings to elicit transferable performance enhancements., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Dziego et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Language models based on artificial neural networks increasingly capture key aspects of how humans process sentences. Most notably, model-based surprisals predict event-related potentials such as N400 amplitudes during parsing. Assuming that these models represent realistic estimates of human linguistic experience, their success in modeling language processing raises the possibility that the human processing system relies on no other principles than the general architecture of language models and on sufficient linguistic input. Here, we test this hypothesis on N400 effects observed during the processing of verb-final sentences in German, Basque, and Hindi. By stacking Bayesian generalised additive models, we show that, in each language, N400 amplitudes and topographies in the region of the verb are best predicted when model-based surprisals are complemented by an Agent Preference principle that transiently interprets initial role-ambiguous noun phrases as agents, leading to reanalysis when this interpretation fails. Our findings demonstrate the need for this principle independently of usage frequencies and structural differences between languages. The principle has an unequal force, however. Compared to surprisal, its effect is weakest in German, stronger in Hindi, and still stronger in Basque. This gradient is correlated with the extent to which grammars allow unmarked NPs to be patients, a structural feature that boosts reanalysis effects. We conclude that language models gain more neurobiological plausibility by incorporating an Agent Preference. Conversely, theories of human processing profit from incorporating surprisal estimates in addition to principles like the Agent Preference, which arguably have distinct evolutionary roots., Competing Interests: Competing Interests: The authors have declared that no competing interests exist., (© 2023 Massachusetts Institute of Technology.)

This article presents the results from a Spatial Augmented Reality (SAR) study which evaluated the cognitive cost of several predictive cues. Participants performed a validated procedural button pressing task, where the predictive cue annotations guided them to the upcoming task. While existing research has evaluated predictive cues based on their performance and self-rated mental effort, actual cognitive cost has yet to be investigated. To measure the user's brain activity, this study utilized electroencephalogram (EEG) recordings. Cognitive load was evaluated by measuring brain responses for a secondary auditory oddball task, with reduced brain responses to oddball tones expected when cognitive load in the primary task is highest. A simple monitor n-back task and procedural task comparing monitor versus SAR were conducted, followed by a version of the procedural task comparing the SAR predictive cues. Results from the brain responses were able to distinguish between performance enhancing cues with a high and low cognitive load. Electrical brain responses also revealed that having an arc or arrow guide towards the upcoming task required the least amount of mental effort.

Memory is critical for many cognitive functions, from remembering facts, to learning complex environmental rules. While memory encoding occurs during wake, memory consolidation is associated with sleep-related neural activity. Further, research suggests that individual differences in alpha frequency during wake (∼7 - 13 Hz) modulate memory processes, with higher individual alpha frequency (IAF) associated with greater memory performance. However, the relationship between wake-related EEG individual differences, such as IAF, and sleep-related neural correlates of memory consolidation has been largely unexplored, particularly in a complex rule-based memory context. Here, we aimed to investigate whether wake-derived IAF and sleep neurophysiology interact to influence rule learning in a sample of 35 healthy adults (16 males; mean age = 25.4, range: 18 - 40). Participants learned rules of a modified miniature language prior to either 8hrs of sleep or wake, after which they were tested on their knowledge of the rules in a grammaticality judgement task. Results indicate that sleep neurophysiology and wake-derived IAF do not interact but modulate memory for complex linguistic rules separately. Phase-amplitude coupling between slow oscillations and spindles during non-rapid eye-movement (NREM) sleep also promoted memory for rules that were analogous to the canonical English word order. As an exploratory analysis, we found that rapid eye-movement (REM) sleep theta power at posterior regions interacts with IAF to predict rule learning and proportion of time in REM sleep predicts rule learning differentially depending on grammatical rule type. Taken together, the current study provides behavioural and electrophysiological evidence for a complex role of NREM and REM sleep neurophysiology and wake-derived IAF in the consolidation of rule-based information., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

We explore Spatial Augmented Reality (SAR) precues (predictive cues) for procedural tasks within and between workspaces and for visualizing multiple upcoming steps in advance. We designed precues based on several factors: cue type, color transparency, and multi-level (number of precues). Precues were evaluated in a procedural task requiring the user to press buttons in three surrounding workspaces. Participants performed fastest in conditions where tasks were linked with line cues with different levels of color transparency. Precue performance was also affected by whether the next task was in the same workspace or a different one.

The language comprehension system preferentially assumes that agents come first during incremental processing. While this might reflect a biologically fixed bias, shared with other domains and other species, the evidence is limited to languages that place agents first, and so the bias could also be learned from usage frequency. Here, we probe the bias with electroencephalography (EEG) in Äiwoo, a language that by default places patients first, but where sentence-initial nouns are still locally ambiguous between patient or agent roles. Comprehenders transiently interpreted nonhuman nouns as patients, eliciting a negativity when disambiguation was toward the less common agent-initial order. By contrast and against frequencies, human nouns were transiently interpreted as agents, eliciting an N400-like negativity when the disambiguation was toward patient-initial order. Consistent with the notion of a fixed property, the agent bias is robust against usage frequency for human referents. However, this bias can be reversed by frequency experience for nonhuman referents., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

The endeavour to understand human cognition has largely relied upon investigation of task-related brain activity. However, resting-state brain activity can also offer insights into individual information processing and performance capabilities. Previous research has identified electroencephalographic resting-state characteristics (most prominently: the individual alpha frequency; IAF) that predict cognitive function. However, it has largely overlooked a second component of electrophysiological signals: aperiodic 1/ƒ activity. The current study examined how both oscillatory and aperiodic resting-state EEG measures, alongside traditional cognitive tests, can predict performance in a dynamic and complex, semi-naturalistic cognitive task. Participants' resting-state EEG was recorded prior to engaging in a Target Motion Analysis (TMA) task in a simulated submarine control room environment (CRUSE), which required participants to integrate dynamically changing information over time. We demonstrated that the relationship between IAF and cognitive performance extends from simple cognitive tasks (e.g., digit span) to complex, dynamic measures of information processing. Further, our results showed that individual 1/ƒ parameters (slope and intercept) differentially predicted performance across practice and testing sessions, whereby flatter slopes and higher intercepts were associated with improved performance during learning. In addition to the EEG predictors, we demonstrate a link between cognitive skills most closely related to the TMA task (i.e., spatial imagery) and subsequent performance. Overall, the current study highlights (1) how resting-state metrics - both oscillatory and aperiodic - have the potential to index higher-order cognitive capacity, while (2) emphasising the importance of examining these electrophysiological components within more dynamic settings and over time., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more individuals engaging cooperatively in real-world tasks, such as in operational training environments. In this exploratory study, we recruited forty individuals paired as twenty dyads and recorded dual-EEG at rest and during realistic training scenarios of increasing complexity using virtual simulation systems. We estimated markers of intrinsic brain activity (i.e., individual alpha frequency and aperiodic activity), as well as task-related theta and alpha oscillations. Using nonlinear modelling and a logistic regression machine learning model, we found that resting-state EEG predicts performance and can also reliably differentiate between members within a dyad. Task-related theta and alpha activity during easy training tasks predicted later performance on complex training to a greater extent than prior behaviour. These findings complement laboratory-based research on both oscillatory and aperiodic activity in higher-order cognition and provide evidence that theta and alpha activity play a critical role in complex task performance in team environments., (© 2022. The Author(s).)

Predictive coding provides a compelling, unified theory of neural information processing, including for language. However, there is insufficient understanding of how predictive models adapt to changing contextual and environmental demands and the extent to which such adaptive processes differ between individuals. Here, we used electroencephalography (EEG) to track prediction error responses during a naturalistic language processing paradigm. In Experiment 1, 45 native speakers of English listened to a series of short passages. Via a speaker manipulation, we introduced changing intra-experimental adjective order probabilities for two-adjective noun phrases embedded within the passages and investigated whether prediction error responses adapt to reflect these intra-experimental predictive contingencies. To this end, we calculated a novel measure of speaker-based, intra-experimental surprisal ("speaker-based surprisal") as defined on a trial-by-trial basis and by clustering together adjectives with a similar meaning. N400 amplitude at the position of the critical second adjective was used as an outcome measure of prediction error. Results showed that N400 responses attuned to speaker-based surprisal over the course of the experiment, thus indicating that listeners rapidly adapt their predictive models to reflect local environmental contingencies (here: the probability of one type of adjective following another when uttered by a particular speaker). Strikingly, this occurs in spite of the wealth of prior linguistic experience that participants bring to the laboratory. Model adaptation effects were strongest for participants with a steep aperiodic (1/f) slope in resting EEG and low individual alpha frequency (IAF), with idea density (ID) showing a more complex pattern. These results were replicated in a separate sample of 40 participants in Experiment 2, which employed a highly similar design to Experiment 1. Overall, our results suggest that individuals with a steep aperiodic slope adapt their predictive models most strongly to context-specific probabilistic information. Steep aperiodic slope is thought to reflect low neural noise, which in turn may be associated with higher neural gain control and better cognitive control. Individuals with a steep aperiodic slope may thus be able to more effectively and dynamically reconfigure their prediction-related neural networks to meet current task demands. We conclude that predictive mechanisms in language are highly malleable and dynamic, reflecting both the affordances of the present environment as well as intrinsic information processing capabilities of the individual., Competing Interests: Author PA was employed by Beacon Biosignals, Boston. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bornkessel-Schlesewsky, Sharrad, Howlett, Alday, Corcoran, Bellan, Wilkinson, Kliegl, Lewis, Small and Schlesewsky.)

Memory formation involves the synchronous firing of neurons in task-relevant networks, with recent models postulating that a decrease in low-frequency oscillatory activity underlies successful memory encoding and retrieval. However, to date, this relationship has been investigated primarily with face and image stimuli; considerably less is known about the oscillatory correlates of complex rule learning, as in language. Furthermore, recent work has shown that nonoscillatory (1/ƒ) activity is functionally relevant to cognition, yet its interaction with oscillatory activity during complex rule learning remains unknown. Using spectral decomposition and power-law exponent estimation of human EEG data (17 women, 18 men), we show for the first time that 1/ƒ and oscillatory activity jointly influence the learning of word order rules of a miniature artificial language system. Flexible word-order rules were associated with a steeper 1/ƒ slope, whereas fixed word-order rules were associated with a shallower slope. We also show that increased theta and alpha power predicts fixed relative to flexible word-order rule learning and behavioral performance. Together, these results suggest that 1/ƒ activity plays an important role in higher-order cognition, including language processing, and that grammar learning is modulated by different word-order permutations, which manifest in distinct oscillatory profiles., (© 2022 Massachusetts Institute of Technology.)

Languages differ in how they mark the dependencies between verbs and arguments, e.g., by case. An eye tracking and EEG picture description study examined the influence of case marking on the time course of sentence planning in Basque and Swiss German. While German assigns an unmarked (nominative) case to subjects, Basque specifically marks agent arguments through ergative case. Fixations to agents and event-related synchronization (ERS) in the theta and alpha frequency bands, as well as desynchronization (ERD) in the alpha and beta bands revealed multiple effects of case marking on the time course of early sentence planning. Speakers decided on case marking under planning early when preparing sentences with ergative-marked agents in Basque, whereas sentences with unmarked agents allowed delaying structural commitment across languages. These findings support hierarchically incremental accounts of sentence planning and highlight how cross-linguistic differences shape the neural dynamics underpinning language use., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

The capacity to regulate one's attention in accordance with fluctuating task demands and environmental contexts is an essential feature of adaptive behavior. Although the electrophysiological correlates of attentional processing have been extensively studied in the laboratory, relatively little is known about the way they unfold under more variable, ecologically-valid conditions. Accordingly, this study employed a 'real-world' EEG design to investigate how attentional processing varies under increasing cognitive, motor, and environmental demands. Forty-four participants were exposed to an auditory oddball task while (1) sitting in a quiet room inside the lab, (2) walking around a sports field, and (3) wayfinding across a university campus. In each condition, participants were instructed to either count or ignore oddball stimuli. While behavioral performance was similar across the lab and field conditions, oddball count accuracy was significantly reduced in the campus condition. Moreover, event-related potential components (mismatch negativity and P3) elicited in both 'real-world' settings differed significantly from those obtained under laboratory conditions. These findings demonstrate the impact of environmental factors on attentional processing during simultaneously-performed motor and cognitive tasks, highlighting the value of incorporating dynamic and unpredictable contexts within naturalistic designs., (© 2021. The Author(s).)

An emerging body of work has demonstrated that resting-state non-oscillatory, or aperiodic, 1/f neural activity is a functional and behaviorally relevant marker of cognitive function capacity. In the motor domain, previous work has only applied 1/f analyses to investigations of motor coordination and performance measures. The value of aperiodic resting-state neural dynamics as a marker of individual visuomotor performance capacity remains unknown. Accordingly, the aim of this work was to investigate if individual 1/f intercept and slope parameters of aperiodic resting-state neural activity predict reaction time and perceptual sensitivity in an immersive virtual reality marksmanship task. The marksmanship task required speeded selection of target stimuli and avoidance of selecting non-target stimuli. Motor and perceptual demands were incrementally increased across task blocks and participants performed the task across three training sessions spanning one week. When motor demands were high, steeper individual 1/f slope predicted shorter reaction time. This relationship did not change with practice. Increased 1/f intercept and a steeper 1/f slope were associated with higher perceptual sensitivity, measured as d'. However, this association was only observed under the highest levels of perceptual demand and only in the initial exposure to these conditions. Individuals with a lower 1/f intercept and a shallower 1/f slope demonstrated the greatest gains in perceptual sensitivity from task practice. These findings demonstrate that individual differences in motor and perceptual performance can be accounted for with resting-state aperiodic neural dynamics. The 1/f aperiodic parameters are most informative in predicting visuomotor performance under complex and demanding task conditions. In addition to predicting capacity for high visuomotor performance with a novel task, 1/f aperiodic parameters might also be useful in predicting which individuals might derive the most improvements from practice., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Artificial grammar learning (AGL) paradigms are used extensively to characterise (neuro)cognitive bases of language learning. However, despite their effectiveness in characterising the capacity to learn complex structured sequences, AGL paradigms lack ecological validity and typically do not account for cross-linguistic differences in sentence comprehension. Here, we describe a new modified miniature language paradigm - Mini Pinyin - that mimics natural language as it is based on an existing language (Mandarin Chinese) and includes both structure and meaning. Mini Pinyin contains a number of cross-linguistic elements, including varying word orders and classifier-noun rules. To evaluate the effectiveness of Mini Pinyin, 76 (mean age = 24.9; 26 female) monolingual native English speakers completed a learning phase followed by a sentence acceptability judgement task. Generalised mixed effects modelling revealed that participants attained a moderate degree of accuracy on the judgement task, with performance scores ranging from 25% to 100% accuracy depending on the word order of the sentence. Further, sentences compatible with the canonical English word order were learned more efficiently than non-canonical word orders. We controlled for inter-individual differences in statistical learning ability, which accounted for ~20% of the variance in performance on the sentence judgement task. We provide stimuli and statistical analysis scripts as open-source resources and discuss how future research can utilise this paradigm to study the neurobiological basis of language learning. Mini Pinyin affords a convenient tool for improving the future of language learning research by building on the parameters of traditional AGL or existing miniature language paradigms.

Planning to speak is a challenge for the brain, and the challenge varies between and within languages. Yet, little is known about how neural processes react to these variable challenges beyond the planning of individual words. Here, we examine how fundamental differences in syntax shape the time course of sentence planning. Most languages treat alike (i.e., align with each other) the 2 uses of a word like "gardener" in "the gardener crouched" and in "the gardener planted trees." A minority keeps these formally distinct by adding special marking in 1 case, and some languages display both aligned and nonaligned expressions. Exploiting such a contrast in Hindi, we used electroencephalography (EEG) and eye tracking to suggest that this difference is associated with distinct patterns of neural processing and gaze behavior during early planning stages, preceding phonological word form preparation. Planning sentences with aligned expressions induces larger synchronization in the theta frequency band, suggesting higher working memory engagement, and more visual attention to agents than planning nonaligned sentences, suggesting delayed commitment to the relational details of the event. Furthermore, plain, unmarked expressions are associated with larger desynchronization in the alpha band than expressions with special markers, suggesting more engagement in information processing to keep overlapping structures distinct during planning. Our findings contrast with the observation that the form of aligned expressions is simpler, and they suggest that the global preference for alignment is driven not by its neurophysiological effect on sentence planning but by other sources, possibly by aspects of production flexibility and fluency or by sentence comprehension. This challenges current theories on how production and comprehension may affect the evolution and distribution of syntactic variants in the world's languages., Competing Interests: The authors have declared that no competing interests exist.

When viewed cross-sectionally, aging seems to negatively affect speech comprehension. However, aging is a heterogeneous process, and variability among older adults is typically large. In this study, we investigated language comprehension as a function of individual differences in older adults. Specifically, we tested whether hearing thresholds, working memory, inhibition, and individual alpha frequency would predict event-related potential amplitudes in response to classic psycholinguistic manipulations at the sentence level. Twenty-nine healthy older adults (age range 61-76 years) listened to English sentences containing reduced relative clauses and object-relative clauses while their electroencephalogram was recorded. We found that hearing thresholds and working memory predicted P600 amplitudes early during reduced relative clause processing, while individual alpha frequency predicted P600 amplitudes at a later point in time. The results suggest that participants with better hearing and larger working memory capacity simultaneously activated both the preferred and the dispreferred interpretation of reduced relative clauses, while participants with worse hearing and smaller working memory capacity only activated the preferred interpretation. They also suggest that participants with a higher individual alpha frequency had a higher likelihood of successfully reanalysing the sentence toward the reduced relative clause reading than participants with a lower individual alpha frequency. By contrast, we found no relationship between object-relative clause processing and working memory or hearing thresholds. Taken together, the results support the view that older adults employ different strategies during auditory sentence processing dependent on their hearing and cognitive abilities and that there is no single ability that uniformly predicts sentence processing outcomes., (Copyright © 2020 Kurthen, Meyer, Schlesewsky and Bornkessel-Schlesewsky.)

Semantic reversal anomalies (SRAs)-sentences where an implausibility is created by reversing participant roles-have attracted much attention in the literature on the electrophysiology of language. In spite of being syntactically well formed but semantically implausible, these sentences unexpectedly elicited a monophasic P600 effect in English and Dutch rather than an N400 effect. Subsequent research revealed variability in the presence/absence of an N400 effect to SRAs depending on the language examined and the choice of verb type in English. However, most previous studies employed the same presentation modality (visual) and task (acceptability judgement). Here, we conducted two experiments and three statistical analyses to investigate the influence of stimulus modality, task demand and statistical choices on event-related potential (ERP) response patterns to SRAs in English. We reproduced a previous study's procedure and analysis (N. Bourguignon et al. (2012) Brain and Language, 122, 179-189) and further introduced between-subjects factors of task type and modality, using mixed-effects modelling to analyse the data. We observed an N400 effect to typical English SRAs (agent subject verbs, e.g. "the fries will eat the boys"), which contrasts existing literature and was not predicted by existing theories that account for SRA processing. Task demand modulated the ERPs elicited by SRAs, while auditory presentation led to increased comprehension accuracy and a more broadly distributed ERP. Finally, the statistical methods used influenced the presence/absence of ERP effects. Our results suggest a sensitivity of language-related ERP patterns to methodological parameters, and we conclude that future experiments should take this into careful consideration., (© 2020 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Previous work found that single-session focused attention meditation (FAM) enhanced motor sequence learning through increased cognitive control as a mechanistic action, although electrophysiological correlates of sequence learning performance following FAM were not investigated. We measured the persistent frontal N2 event-related potential (ERP) that is closely related to cognitive control processes and its ability to predict behavioural measures. Twenty-nine participants were randomised to one of three conditions reflecting the level of FAM experienced prior to a serial reaction time task (SRTT): 21 sessions of FAM (FAM21, N = 12), a single FAM session (FAM1, N = 9) or no preceding FAM control (Control, N = 8). Continuous 64-channel EEG were recorded during SRTT and N2 amplitudes for correct trials were extracted. Component amplitude, regions of interests, and behavioural outcomes were compared using mixed effects regression models between groups. FAM21 exhibited faster reaction time performances in majority of the learning blocks compared to FAM1 and Control. FAM21 also demonstrated a significantly more pronounced N2 over majority of anterior and central regions of interests during SRTT compared to the other groups. When N2 amplitudes were modelled against general learning performance, FAM21 showed the greatest rate of amplitude decline over anterior and central regions. The combined results suggest that FAM training provided greater cognitive control enhancement for improved general performance, and less pronounced effects for sequence-specific learning performance compared to the other groups. Importantly, FAM training facilitates dynamic modulation of cognitive control: lower levels of general learning performance was supported by greater levels of activation, whilst higher levels of general learning exhibited less activation., (Copyright © 2020 Elsevier B.V. All rights reserved.)

One of the main characteristics of human languages is that they are subject to fundamental changes over time. However, because of the long transitional periods involved, the internal dynamics of such changes are typically inaccessible. Here, we present a new approach to examining language change via its connection to language comprehension. By means of an EEG experiment on Icelandic, a prominent current example of a language in transition, we show that the neurophysiological responses of native speakers already reflect projected changes that are not yet apparent in their overt behavior. Neurocognitive measures thus offer a means of predicting, rather than only retracing, language change., (Copyright © 2020 Bornkessel-Schlesewsky, Roehm, Mailhammer and Schlesewsky.)

Language-related event-related potential (ERP) components such as the N400 have traditionally been associated with linguistic or cognitive functional interpretations. By contrast, it has been considerably more difficult to relate these components to neurobiologically grounded accounts of language. Here, we propose a theoretical framework based on a predictive coding architecture, within which negative language-related ERP components such as the N400 can be accounted for in a neurobiologically plausible manner. Specifically, we posit that the amplitude of negative language-related ERP components reflects precision-weighted prediction error signals, i.e., prediction errors weighted by the relevance of the information source leading to the error. From this perspective, precision has a direct link to cue validity in a particular language and, thereby, to relevance of individual linguistic features for internal model updating. We view components such as the N400 and LAN as members of a family with similar functional characteristics and suggest that latency and topography differences between these components reflect the locus of prediction errors and model updating within a hierarchically organized cortical predictive coding architecture. This account has the potential to unify findings from the full range of the N400 literature, including word-level, sentence-, and discourse-level results as well as cross-linguistic differences.

Previous research has demonstrated that Augmented Reality can reduce a user's task response time and mental effort when completing a procedural task. This paper investigates techniques to improve user performance and reduce mental effort by providing projector-based Spatial Augmented Reality predictive cues for future responses. The objective of the two experiments conducted in this study was to isolate the performance and mental effort differences from several different annotation cueing techniques for simple (Experiment 1) and complex (Experiment 2) button-pressing tasks. Comporting with existing cognitive neuroscience literature on prediction, attentional orienting, and interference, we hypothesized that for both simple procedural tasks and complex search-based tasks, having a visual cue guiding to the next task's location would positively impact performance relative to a baseline, no-cue condition. Additionally, we predicted that direction-based cues would provide a more significant positive impact than target-based cues. The results indicated that providing a line to the next task was the most effective technique for improving the users' task time and mental effort in both the simple and complex tasks.

Individual alpha frequency (IAF) is a promising electrophysiological marker of interindividual differences in cognitive function. IAF has been linked with trait-like differences in information processing and general intelligence, and provides an empirical basis for the definition of individualized frequency bands. Despite its widespread application, however, there is little consensus on the optimal method for estimating IAF, and many common approaches are prone to bias and inconsistency. Here, we describe an automated strategy for deriving two of the most prevalent IAF estimators in the literature: peak alpha frequency (PAF) and center of gravity (CoG). These indices are calculated from resting-state power spectra that have been smoothed using a Savitzky-Golay filter (SGF). We evaluate the performance characteristics of this analysis procedure in both empirical and simulated EEG data sets. Applying the SGF technique to resting-state data from n = 63 healthy adults furnished 61 PAF and 62 CoG estimates. The statistical properties of these estimates were consistent with previous reports. Simulation analyses revealed that the SGF routine was able to reliably extract target alpha components, even under relatively noisy spectral conditions. The routine consistently outperformed a simpler method of automated peak detection that did not involve spectral smoothing. The SGF technique is fast, open source, and available in two popular programming languages (MATLAB, Python), and thus can easily be integrated within the most popular M/EEG toolsets (EEGLAB, FieldTrip, MNE-Python). As such, it affords a convenient tool for improving the reliability and replicability of future IAF-related research., (© 2018 Society for Psychophysiological Research.)

We hypothesize a beneficial influence of sleep on the consolidation of the combinatorial mechanisms underlying incremental sentence comprehension. These predictions are grounded in recent work examining the effect of sleep on the consolidation of linguistic information, which demonstrate that sleep-dependent neurophysiological activity consolidates the meaning of novel words and simple grammatical rules. However, the sleep-dependent consolidation of sentence-level combinatorics has not been studied to date. Here, we propose that dissociable aspects of sleep neurophysiology consolidate two different types of combinatory mechanisms in human language: sequence-based (order-sensitive) and dependency-based (order-insensitive) combinatorics. The distinction between the two types of combinatorics is motivated both by cross-linguistic considerations and the neurobiological underpinnings of human language. Unifying this perspective with principles of sleep-dependent memory consolidation, we posit that a function of sleep is to optimize the consolidation of sequence-based knowledge (the when ) and the establishment of semantic schemas of unordered items (the what ) that underpin cross-linguistic variations in sentence comprehension. This hypothesis builds on the proposal that sleep is involved in the construction of predictive codes, a unified principle of brain function that supports incremental sentence comprehension. Finally, we discuss neurophysiological measures (EEG/MEG) that could be used to test these claims, such as the quantification of neuronal oscillations, which reflect basic mechanisms of information processing in the brain.

The recent trend away from ANOVA-based analyses places experimental investigations into the neurobiology of cognition in more naturalistic and ecologically valid designs within reach. Using mixed-effects models for epoch-based regression, we demonstrate the feasibility of examining event-related potentials (ERPs), and in particular the N400, to study the neural dynamics of human auditory language processing in a naturalistic setting. Despite the large variability between trials during naturalistic stimulation, we replicated previous findings from the literature: the effects of frequency, animacy, and word order and find previously unexplored interaction effects. This suggests a new perspective on ERPs, namely, as a continuous modulation reflecting continuous stimulation instead of a series of discrete and essentially sequential processes locked to discrete events.

There is an ongoing debate whether the P600 event-related potential component following syntactic anomalies reflects syntactic processes per se, or if it is an instance of the P300, a domain-general ERP component associated with attention and cognitive reorientation. A direct comparison of both components is challenging because of the huge discrepancy in experimental designs and stimulus choice between language and 'classic' P300 experiments. In the present study, we develop a new approach to mimic the interplay of sequential position as well as categorical and relational information in natural language syntax (word category and agreement) in a non-linguistic target detection paradigm using musical instruments. Participants were instructed to (covertly) detect target tones which were defined by instrument change and pitch rise between subsequent tones at the last two positions of four-tone sequences. We analysed the EEG using event-related averaging and time-frequency decomposition. Our results show striking similarities to results obtained from linguistic experiments. We found a P300 that showed sensitivity to sequential position and a late positivity sensitive to stimulus type and position. A time-frequency decomposition revealed significant effects of sequential position on the theta band and a significant influence of stimulus type on the delta band. Our results suggest that the detection of non-linguistic targets defined via complex feature conjunctions in the present study and the detection of syntactic anomalies share the same underlying processes: attentional shift and memory based matching processes that act upon multi-feature conjunctions. We discuss the results as supporting domain-general accounts of the P600 during natural language comprehension., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

While listening to continuous speech, humans process beat information to correctly identify word boundaries. The beats of language are stress patterns that are created by combining lexical (word-specific) stress patterns and the rhythm of a specific language. Sometimes, the lexical stress pattern needs to be altered to obey the rhythm of the language. This study investigated the interplay of lexical stress patterns and rhythmical well-formedness in natural speech with fMRI. Previous electrophysiological studies on cases in which a regular lexical stress pattern may be altered to obtain rhythmical well-formedness showed that even subtle rhythmic deviations are detected by the brain if attention is directed toward prosody. Here, we present a new approach to this phenomenon by having participants listen to contextually rich stories in the absence of a task targeting the manipulation. For the interaction of lexical stress and rhythmical well-formedness, we found one suprathreshold cluster localized between the cerebellum and the brain stem. For the main effect of lexical stress, we found higher BOLD responses to the retained lexical stress pattern in the bilateral SMA, bilateral postcentral gyrus, bilateral middle fontal gyrus, bilateral inferior and right superior parietal lobule, and right precuneus. These results support the view that lexical stress is processed as part of a sensorimotor network of speech comprehension. Moreover, our results connect beat processing in language to domain-independent timing perception.

Several studies have examined effects of explicit task demands on eye movements in reading. However, there is relatively little prior research investigating the influence of implicit processing demands. In the present study, processing demands were manipulated by means of a between-subject manipulation of comprehension question difficulty. Consistent with previous results from Wotschack and Kliegl (2013), the question difficulty manipulation influenced the probability of regressing from late in sentences and re-reading earlier regions; readers who expected difficult comprehension questions were more likely to re-read. However, this manipulation had no reliable influence on eye movements during first pass reading of earlier sentence regions. Moreover, for the subset of sentences that contained a plausibility manipulation, the disruption induced by implausibility was not modulated by the question manipulation. We interpret these results as suggesting that comprehension demands influence reading behavior primarily by modulating a criterion for comprehension that readers apply after completing first-pass processing.

The hierarchical organization of human cortical circuits integrates information across different timescales via temporal receptive windows, which increase in length from lower to higher levels of the cortical hierarchy (Hasson et al., 2015). A recent neurobiological model of higher-order language processing (Bornkessel-Schlesewsky et al., 2015) posits that temporal receptive windows in the dorsal auditory stream provide the basis for a hierarchically organized predictive coding architecture (Friston and Kiebel, 2009). In this stream, a nested set of internal models generates time-based ("when") predictions for upcoming input at different linguistic levels (sounds, words, sentences, discourse). Here, we used naturalistic stories to test the hypothesis that multi-sentence, discourse-level predictions are processed in the dorsal auditory stream, yielding attenuated BOLD responses for highly predicted versus less strongly predicted language input. The results were as hypothesized: discourse-related cues, such as passive voice, which effect a higher predictability of remention for a character at a later point within a story, led to attenuated BOLD responses for auditory input of high versus low predictability within the dorsal auditory stream, specifically in the inferior parietal lobule, middle frontal gyrus, and dorsal parts of the inferior frontal gyrus, among other areas. Additionally, we found effects of content-related ("what") predictions in ventral regions. These findings provide novel evidence that hierarchical predictive coding extends to discourse-level processing in natural language. Importantly, they ground language processing on a hierarchically organized predictive network, as a common underlying neurobiological basis shared with other brain functions., Significance Statement: Language is the most powerful communicative medium available to humans. Nevertheless, we lack an understanding of the neurobiological basis of language processing in natural contexts: it is not clear how the human brain processes linguistic input within the rich contextual environments of our everyday language experience. This fMRI study provides the first demonstration that, in natural stories, predictions concerning the probability of remention of a protagonist at a later point are processed in the dorsal auditory stream. Results are congruent with a hierarchical predictive coding architecture assuming temporal receptive windows of increasing length from auditory to higher-order cortices. Accordingly, language processing in rich contextual settings can be explained via domain-general, neurobiological mechanisms of information processing in the human brain., (Copyright © 2016 Kandylaki et al.)

Human language allows us to express our thoughts and ideas by combining entities, concepts and actions into multi-event episodes. Yet, the functional neuroanatomy engaged in interpretation of such high-level linguistic input remains poorly understood. Here, we used easy to detect and more subtle "borderline" anomalies to investigate the brain regions and mechanistic principles involved in the use of real-world event knowledge in language comprehension. Overall, the results showed that the processing of sentences in context engages a complex set of bilateral brain regions in the frontal, temporal and inferior parietal lobes. Easy anomalies preferentially engaged lower-order cortical areas adjacent to the primary auditory cortex. In addition, the left supramarginal gyrus and anterior temporal sulcus as well as the right posterior middle temporal gyrus contributed to the processing of easy and borderline anomalies. The observed pattern of results is explained in terms of (i) hierarchical processing along a dorsal-ventral axis and (ii) the assumption of high-order association areas serving as cortical hubs in the convergence of information in a distributed network. Finally, the observed modulation of BOLD signal in prefrontal areas provides support for their role in the implementation of executive control processes., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The specificity or generality of language-related event-related brain potentials (ERPs) has been a point of continuing debate in the cognitive neuroscience of language. The present study measured ERPs to (preferred) subject-before-object (SO) and (dispreferred) object-before-subject (OS) word orders in German while manipulating morphosyntactic and semantic cues to correct sentence interpretation. We presented sentence pairs as connected speech (context and target sentences) and examined ERPs at the position of the first argument (noun phrase) in the target sentence. At this position, word order was determinable by either (a) case marking (morphosyntactic cue); (b) animacy (semantic cue); or (c) the preceding context sentence (local ambiguity; contextual cue). Following each sentence pair, participants judged the acceptability of the second sentence in the context of the first and performed a probe word recognition task. Results showed a biphasic N400-P600 pattern at the first noun phrase in the OS conditions irrespectively of which cues (syntactic or semantic) were available to the parser for disambiguation. N400 latency varied as a function of temporal cue availability and P600 amplitude increased for unambiguous object-initial conditions even though these were rated acceptable in the judgment task. These findings support an interpretation of ERP components in terms of general cognitive mechanisms such as predictive processes (N400) and decision certainty (P600 as an instance of the P300) rather than a domain-specific view of a semantic N400 and a syntactic P600., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Hierarchical predictive coding has been identified as a possible unifying principle of brain function, and recent work in cognitive neuroscience has examined how it may be affected by age-related changes. Using language comprehension as a test case, the present study aimed to dissociate age-related changes in prediction generation versus internal model adaptation following a prediction error. Event-related brain potentials (ERPs) were measured in a group of older adults (60-81 years; n = 40) as they read sentences of the form "The opposite of black is white/yellow/nice." Replicating previous work in young adults, results showed a target-related P300 for the expected antonym ("white"; an effect assumed to reflect a prediction match), and a graded N400 effect for the two incongruous conditions (i.e. a larger N400 amplitude for the incongruous continuation not related to the expected antonym, "nice," versus the incongruous associated condition, "yellow"). These effects were followed by a late positivity, again with a larger amplitude in the incongruous non-associated versus incongruous associated condition. Analyses using linear mixed-effects models showed that the target-related P300 effect and the N400 effect for the incongruous non-associated condition were both modulated by age, thus suggesting that age-related changes affect both prediction generation and model adaptation. However, effects of age were outweighed by the interindividual variability of ERP responses, as reflected in the high proportion of variance captured by the inclusion of by-condition random slopes for participants and items. We thus argue that - at both a neurophysiological and a functional level - the notion of general differences between language processing in young and older adults may only be of limited use, and that future research should seek to better understand the causes of interindividual variability in the ERP responses of older adults and its relation to cognitive performance.

The neural correlates of theory of mind (ToM) are typically studied using paradigms which require participants to draw explicit, task-related inferences (e.g., in the false belief task). In a natural setup, such as listening to stories, false belief mentalizing occurs incidentally as part of narrative processing. In our experiment, participants listened to auditorily presented stories with false belief passages (implicit false belief processing) and immediately after each story answered comprehension questions (explicit false belief processing), while neural responses were measured with functional magnetic resonance imaging (fMRI). All stories included (among other situations) one false belief condition and one closely matched control condition. For the implicit ToM processing, we modeled the hemodynamic response during the false belief passages in the story and compared it to the hemodynamic response during the closely matched control passages. For implicit mentalizing, we found activation in typical ToM processing regions, that is the angular gyrus (AG), superior medial frontal gyrus (SmFG), precuneus (PCUN), middle temporal gyrus (MTG) as well as in the inferior frontal gyrus (IFG) billaterally. For explicit ToM, we only found AG activation. The conjunction analysis highlighted the left AG and MTG as well as the bilateral IFG as overlapping ToM processing regions for both implicit and explicit modes. Implicit ToM processing during listening to false belief passages, recruits the left SmFG and billateral PCUN in addition to the "mentalizing network" known form explicit processing tasks., (© 2015 Wiley Periodicals, Inc.)

Do principles of language processing in the brain affect the way grammar evolves over time or is language change just a matter of socio-historical contingency? While the balance of evidence has been ambiguous and controversial, we identify here a neurophysiological constraint on the processing of language that has a systematic effect on the evolution of how noun phrases are marked by case (i.e. by such contrasts as between the English base form she and the object form her). In neurophysiological experiments across diverse languages we found that during processing, participants initially interpret the first base-form noun phrase they hear (e.g. she…) as an agent (which would fit a continuation like … greeted him), even when the sentence later requires the interpretation of a patient role (as in … was greeted). We show that this processing principle is also operative in Hindi, a language where initial base-form noun phrases most commonly denote patients because many agents receive a special case marker ("ergative") and are often left out in discourse. This finding suggests that the principle is species-wide and independent of the structural affordances of specific languages. As such, the principle favors the development and maintenance of case-marking systems that equate base-form cases with agents rather than with patients. We confirm this evolutionary bias by statistical analyses of phylogenetic signals in over 600 languages worldwide, controlling for confounding effects from language contact. Our findings suggest that at least one core property of grammar systematically adapts in its evolution to the neurophysiological conditions of the brain, independently of socio-historical factors. This opens up new avenues for understanding how specific properties of grammar have developed in tight interaction with the biological evolution of our species.

Couldn׳t a humble coconut hurt a gardener? At least in the first instance, the brain seems to assume that it should not: we perceive inanimate entities such as coconuts as poor event instigators ("Actors"). Ideally, entities causing a change in another entity should be animate and this assumption not only influences event perception but also carries over to language comprehension. We present three auditory event-related brain potential (ERP) studies on the processing of inanimate and animate subjects and objects in simple transitive sentences in Tamil. ERP responses were measured at the second argument (event participant) in all three studies. Experiment 1 employed all possible animacy combinations of Actors and Undergoers (affected participants) in Actor- and Undergoer-initial verb-final orders. Experiments 2 and 3 employed a fairly novel context design that enabled us to compare ERPs evoked by identical auditory material to differing contextual expectations: Experiment 2 focussed on constructions in which an inanimate Actor acts upon an inanimate Undergoer, whereas Experiment 3 examined whether and how a preceding context modulates the prediction for an ideal Actor. Results showed an N400 effect when the prediction for an ideal (animate) Actor following an Undergoer was not met, thus further supporting the cross-linguistically robust nature of animacy preferences. In addition, though specific contextual cues that are indicative of a forthcoming non-ideal Actor may reduce this negativity in comparison to when such cues are not available, they nevertheless do not nullify it, suggesting that animacy-based predictions are stronger than contextual cues in online language comprehension., (Copyright © 2014 Elsevier B.V. All rights reserved.)