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A comprehensive theory of human language requires a data set that is representative of the typological diversity present in the world’s 7,000+ languages (Evans & Levinson, 2009). However, the treatment of linguistic diversity in cognitive science has been historically uneven. While many subfields of linguistics explicitly aim to describe and explain variation (e.g., linguistic typology, phonology), adjacent fields like psycholinguistics have suffered from an overreliance on English (Blasi et al., 2022; Christiansen et al., 2022a; Kidd & Garcia, 2022), mimicking cognitive science in general (Henrich et al., 2010). This large data skew prevents the field from fully explaining how humans acquire, represent, and process language, one of the core defining features of our species.

The study is a reanalysis of existing data from Nieuwland et al. (2018). We aim to determine whether pre-stimulus neural activity is indicative of predictive processing, and to examine whether individual neural markers (i.e. Individual alpha frequency; IAF, and the 1/f aperiodic component) are associated with differences in predictive processing. Pre-stimulus event-related activity and alpha oscillatory activity time locked to the definite article and noun words will be analysed, in order to investigate whether pre-stimulus neural activity changes as cloze probability (an index of word predictability) increases. It is hoped that this will further illuminate the nature of prediction in the brain whilst better capturing sources of item and inter-subject variability.

PhD Experiments 1 and 2 - Louise Kyriaki, University of South Australia

Mini Pinyin was run by Zachariah Cross in 2016 - 2020 as part of his Doctoral research conducted at the Centre for Cognitive and Systems Neuroscience at the University of South Australia, Adelaide, headed by Professor Bornkessel-Schlesewsky. The data set evaluates the validity of a new modified miniature language model – termed Mini Pinyin – to study language learning at the sentence level. Using state-of-the-art statistical analysis techniques, we demonstrate that Mini Pinyin accurately characterises various aspects of grammar learning, including cross-linguistic differences in incremental sentence processing. Upon publication, we will make this repository public, thus providing the material (stimuli, experimental tasks, raw data) open to the scientific community, with the aim of building upon and complementing existing paradigms used to study higher-order language learning.

Data and analysis code to accompany the paper "Two sides of the same coin? The interaction of predictive processing and similarity-based retrieval interference: An ERP study" by Pia Schoknecht, Dietmar Roehm, Matthias Schlesewsky and Ina Bornkessel-Schlesewsky.

Cognition and Hearing Acuity in Older Adults' Sentence Processing

PhD experiment of Louise Kyriaki at the Centre for Cognitive and Systems Neuroscience, University of South Australia. Combined rTMS-EEG methodology to examine ERP and behavioural responses during auditory processing of semantic reversal anomaly sentences. Procedure and materials reproduced from Bourguignon et al., 2012.

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. This work was funded by Swiss National Science Foundation Grant Nr. 100015_160011 (B.B. and M.M.), the NCCR Evolving Language, Swiss National Science Foundation Agreement Nr. #51NF40_180888 (B.B. and M. M.), and the PhD Program in Linguistics and the Graduate Research Campus of the University of Zurich (A.E.). DEB is supported by a grant from the Harvard Data Science Initiative and the Branco Weiss Foundation. I.B.-S. is supported by an Australian Research Council Future Fellowship (FT160100437). I.L. is supported by grants from the Spanish Ministry of Economy and Competitiveness (Grant No. FFI2015-64183-P) and the Basque Government (IT1169-19). The authors thank Anne-Lise Giraud for the suggestion to include beta-band analyses, Vitória Piai for advice on EEG data processing, Giuachin Kreiliger for statistical consultation, Andrina Balsofiore and Edurne Petrirena for help recording the lead-in fragments, Nathalie Rieser and Debora Beuret for help with data collection and processing, and the Phonogram Archives of the University of Zurich for technical support. The authors also thank two anonymous reviewers for their helpful comments on an earlier version of the manuscript.

Language processing requires memory retrieval to integrate current input with previous context and making predictions about upcoming input. We propose that prediction and retrieval are two sides of the same coin, i.e. functionally the same, as they both activate memory representations. Under this assumption, memory retrieval and prediction should interact: Retrieval interference can only occur at a word that triggers retrieval and a fully predicted word would not do that. The present study investigated the proposed interaction with event-related potentials (ERPs) during the processing of sentence pairs in German. Predictability was measured via cloze probability. Memory retrieval was manipulated via the position of a distractor inducing proactive or retroactive similarity-based interference. Linear mixed model analyses provided evidence for the hypothesised interaction in a broadly distributed negativity, which we discuss in relation to the interference ERP literature. Our finding supports the proposal that memory retrieval and prediction are functionally the same. Pia Schoknecht, Dietmar Roehm, Matthias Schlesewsky, Ina Bornkessel- Schlesewsky

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., Little is known about the neural processes involved in planning to speak. This study uses eye-tracking and EEG to show that speakers prepare sentence structures in different ways and rely on alpha and theta oscillations differently when planning sentences with and without agent case marking, challenging theories on how production and comprehension affect language evolution.

Language is one of the most defining human capabilities, involving the coordination of brain networks that generalise the meaning of linguistic units of varying complexity. On a neural level, neocortical slow waves and thalamic spindles during sleep facilitate the reactivation of newly encoded memory traces, manifesting in distinct oscillatory activity during retrieval. However, it is currently unknown if the effect of sleep on memory extends to the generalisation of the mechanisms that subserve sentence comprehension. We address this question by analysing electroencephalogram data recorded from 36 participants during an artificial language learning task and an 8hr nocturnal sleep period. We found that a period of sleep was associated with increased alpha/beta synchronisation and improved behavioural performance. Cross-frequency coupling analyses also revealed that spindle-slow wave coupling predicted the consolidation of varying word order permutations, which was associated with distinct patterns of task-related oscillatory activity during sentence processing. Taken together, this study presents converging behavioural and neurophysiological evidence for a role of sleep in the consolidation of higher order language learning and associated oscillatory neuronal activity. SIGNIFICANCE STATEMENT The endogenous temporal coordination of neural oscillations supports information processing during both wake and sleep states. Here we demonstrate that spindle-slow wave coupling during non-rapid eye movement sleep predicts the consolidation of complex grammatical rules and modulates task-related oscillatory dynamics previously implicated in sentence processing. We show that increases in alpha/beta synchronisation predict enhanced sensitivity to grammatical violations after a period of sleep and strong spindle-slow wave coupling modulates subsequent task-related theta activity to influence behaviour. Our findings reveal a complex interaction between both wake- and sleep-related oscillatory dynamics during the early stages of language learning beyond the single word level.

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. (VLID)4735978

Semantic reversal anomalies (SRAs) – sentences where an implausibility is created by reversing participant roles – have attracted a great deal of attention in the literature on the electrophysiology of language. In spite of being syntactically well-formed but semantically implausible, these structures 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 modelling on ERP response patterns to SRAs in English. We reproduced a previous study’s procedure and analysis (Bourguignon et al., 2012), aiming to replicate their findings. We further introduced between-subjects factors of task type and modality and conducted linear mixed effects modelling to analyse the data. We observed an N400 effect to typical English SRAs, in contrast to the existing literature and not predicted by existing theories that accounts for SRA processing. Task demand quantitively and qualitatively 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 the sensitivity of language-related ERP patterns to methodological parameters and we conclude that future experiments should take this into careful consideration.

Gisbert Fanselow’s work has been invaluable and inspiring to many ­researchers working on syntax, morphology, and information ­structure, both from a ­theoretical and from an experimental perspective. This ­volume comprises a collection of articles dedicated to Gisbert on the occasion of his 60th birthday, covering a range of topics from these areas and beyond. The contributions have in ­common that in a broad sense they have to do with language structures (and thus trees), and that in a more specific sense they have to do with birds. They thus cover two of Gisbert’s major interests in- and outside of the linguistic world (and ­perhaps even at the interface).

Gisbert Fanselow’s work has been invaluable and inspiring to many ­researchers working on syntax, morphology, and information ­structure, both from a ­theoretical and from an experimental perspective. This ­volume comprises a collection of articles dedicated to Gisbert on the occasion of his 60th birthday, covering a range of topics from these areas and beyond. The contributions have in ­common that in a broad sense they have to do with language structures (and thus trees), and that in a more specific sense they have to do with birds. They thus cover two of Gisbert’s major interests in- and outside of the linguistic world (and ­perhaps even at the interface).

Recent theoretical models outline that motor sequence learning involves cognitive control processes that affects stimulus- or plan-based control, although clear contributions from the have not been delineated. Previously, we found that single-session focused attention meditation (FAM) enhanced stimulus-based control through increased top-down activation. In the present experiment, we aimed to understand if single-session FAM effects could be enhanced with short-term FAM training in behavioural reaction time, and neurophysiological indices in the form event-related potentials (ERP). We investigated the N200 component that is closely related to top-down activation, and the error-related negatively (ERN) component that is closely related to error processing for plan development. 29 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 whereby N200 amplitudes for correct trials, and ERN using mean difference in amplitudes for correct and error trials, were extracted. Component amplitudes, topography and behavioural outcomes were compared using linear mixed effects regression models between groups. Firstly, FAM21 exhibited faster reaction time performances in majority of the learning blocks compared to FAM1 and Control. FAM21 also demonstrated a significantly more pronounced N200 component over all anterior and the central regions during SRTT compared to FAM1 and Control. When N200 amplitudes were modelled against general learning performance, FAM21 also showed the greatest rate of decline over all anterior and the central regions during SRTT compared to FAM1 and Control. No robust differences in the ERN component were found that supported our predictions. The N200 is associated with top-down cognitive control processes, and hence may index stimulus-based learning effects; whilst the ERN is associated with error and updating of an internalised plan that may index plan-based learning effects. Firstly, our results show that after FAM training, top-down activation is increased for better block-on-block RT performances compared to the other groups. More importantly, FAM training facilitates more efficient and dynamic modulation of top-down activation such that at high levels of general learning performance, less top-down control is needed to maintain the performance.

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.

Muralikrishnan & Bornkessel-Schlesewsky (2017). Poster presented at the 30th CUNY Conference on Human Sentence Processing at Massachussets Institute of Technology, Boston, USA.

During reading the eyes do not smoothly slide trough the sentence, they rather show an alternating pattern of stable phases (so called fixations) and jumps (so called saccades). Whereas most of the saccades are in the direction of reading (i.e., from left to right in most Western European writing systems), some of the saccades go in the opposite direction, moving the eyes back to sentence material that has been fixated earlier. These so called regressive saccades occur frequently in the context of difficulties in language processing but their exact functional role in reading is largely unclear. Especially, it is still an open question in which cases the eyes just show increased fixation durations and in which cases the eyes actually regress. The present thesis focuses on the functional role of regressive eye movements during reading. In the first part, the limitations of the existing literature in the field of regressive eye movements are discussed. After that, a new account is presented which is called the Information Gathering Framework. This framework postulates at its core that each regressive eye movement has a function, namely to gather additional information about a word that has been processed earlier. Based on this hypothesis a detailed architecture of the model is outlined and it is shown how the model may account for empirical findings from reading research that have been reported in the literature. Also further predictions of the model are discussed. In the second part of the thesis, 2 experiments are presented that were developed to explicitly test the predictions of the Information Gathering Model. The first experiment focuses on the influence of different tasks on regression behavior using eyetracking. The second experiment (consisting of two sub experiments) focuses on the neural correlates of regressive eye movements using combined fMRI / eyetracking measurements. The results of both experiments provide clear empirical evidence in favor of the assumptions of the presented model. In particular, they clearly suggest that increased fixation durations and a higher probability to regress have to be viewed as functional different strategies in reading. In sum, the Information Gathering Framework is the first model of regressive eye movements during reading that may explain the interplay between increased fixation durations and regressive eye movements and that may account for human reading behavior as well., Wenn wir lesen, gleiten unsere Augen nicht durch den Satz, sondern sie springen. Während aber die meisten dieser Sprünge, auch Sakkaden genannt, in der Leserichtung erfolgen, bewegen sich bei ca. 15% der Sakkaden die Augen in die entgegengesetzte Richtung. Obwohl diese so genannten Regressionen der Leseforschung seit Jahrzehnten wohlbekannt sind, bilden ihre genauen Ursachen und Funktionen nach wie vor ein Forschungsdesiderat, was auch darin begründet liegt, dass eine Erklärung sowohl okulomotorische als auch linguistische Aspekte berücksichtigen muss. Die vorliegende Arbeit versucht, sich diesem Problem zu nähern. Dazu wird im ersten Teil nach einer kritischen Analyse der aktuellen Forschungslage ein eigenes Blickbewegungsmodell entworfen, das so genannte Information Gathering Framework, welches das komplexe Zusammenspiel von Fixationszeiten und Regressionsraten während des Lesens zu erklären versucht. Das Modell basiert auf der einfachen Annahme, dass eine Regression immer dann ausgelöst wird, wenn zusätzliche Information über vorherigen Input benötigt wird, genauer gesagt, Information über die Identität eines vorangegangen Wortes. Im zweiten Teil der Arbeit werden zwei empirische Studien vorgestellt, die wichtige Annahmen des entwickelten Modells testen und weitere Erkenntnisse über die Rolle von regressiven Blickbewegungen für die Satzinterpretation liefern. In der ersten Studie, einer Blickbewegungsstudie, wurde der Einfluss von unterschiedlichen Verständnisfragen auf das Regressionsmuster beim Lesen von normalen und anormalen englischen Sätzen untersucht. In der zweiten Studie lag der Fokus neben einer sprach-vergleichenden Untersuchung mit deutschen Sätzen auf den neurobiologischen Unterschieden zwischen progressiven und regressiven Sakkaden. Dazu wurden Blickbewegungsmessungen in ein Verfahren mit funktionalen Bildgebung (fMRT) integriert und die neuronale Antwort des Gehirns auf die beiden Sakkadentypen analysiert. Die Ergebnisse beider Studien bestätigen wichtige Annahmen des Information Gathering Frameworks. So konnte im Besonderen eine klare funktionale Dissoziation zwischen verlängerten Fixationszeiten und Regressionsraten, die beide als Indiz für linguistische Verarbeitungsschwierigkeiten gelten, nachgewiesen werden. Darüber hinaus wurde auch die Annahme des Modells, dass neben der gemeinsamen Grundfunktion zwei unterschiedliche Typen von Regression existieren, anhand der Blickbewegungsmuster bestätigt. Die neuronalen Ergebnisse liefern ferner weitere Evidenz für die funktionale Dissoziation zwischen progressiven und regressiven Sakkaden. Zusammengefasst präsentiert die vorliegende Arbeit das erste umfassende kognitive Blickbewegungsmodell zu regressiven Sakkaden während des Lesens, das den hierarchischen linguistischen Verarbeitungsprozess berücksichtigt und gleichzeitig die wichtigsten Befunde des menschlichen Leseverhaltens erklären kann.

Poster presented at the 2015 meeting of the Society for Neuroscience

of presentation for ALS2016

Talk presented at annual meeting of the Society for the Neurobiology of Language 2011

Poster presented at the Annual Meeting of die Society for the Neurobiology of Language 2016

Presented at the 2015 meeting of the Australasian Cognitive Neuroscience Society

Presented at the annual meeting of the Society for the Neurobiology of Language 2016

Poster presented at the 2016 meeting of the Cognitive Neuroscience Society

Talk presented at Experimental Approaches to Arabic and other understudied Languages (EXAL+) 2016 , Abu Dhabi

Poster presented at 2015 meeting of the Society for the Neurobiology of Language

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.

Muralikrishnan & Bornkessel-Schlesewsky (2011). Poster presented at the 10th International Symposium of Psycholinguistics, BCBL, Donostia San Sebastian, Spain.

Muralikrishnan, Schlesewsky and Bornkessel-Schlesewsky (2008). Poster presented at the 21st CUNY Conference on Sentence Processing, University of North Carolina, Chapel Hill, NC, USA.

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/f 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/f parameters (slope and intercept) differentially predicted performance across practice and testing sessions, whereby flatter slopes were associated with improved performance during learning, while higher intercepts were linked to better performance during testing. 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.

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. Refereed/Peer-reviewed

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. To date, this relationship has predominantly been investigated using objects (e.g., faces, natural scenes); however, considerably less is known about the oscillatory correlates of complex rule learning (e.g., language acquisition). Further, recent work has shown that aperiodic (non-oscillatory) 1/ f activity is functionally and behaviourally relevant, yet its interaction with oscillatory activity during complex rule learning remains virtually unknown. Using spectral decomposition and power-law exponent estimation of human EEG data, we show for the first time that 1/ f and oscillatory activity jointly influence the learning of different word order rules of a miniature language system. Fixed word order rules were associated with an increased power-law exponent (i.e. steeper 1/ f slope) compared to flexible word order rules. We also show that stronger anterior beta synchronisation predicts fixed word order rule learning and subsequent behavioural performance, while stronger theta/alpha synchronisation is associated with the learning of flexible word order rules. These results also revealed nonlinear differences between word order rules as a function of time and sensor space. Moreover, we demonstrated that inter-individual variations in spectral power across the learning task interacted with aperiodic activity to influence subsequent behavioural performance. Together, these results suggest that 1/ f 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.

Refereed/Peer-reviewed This paper 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 vs 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.

Refereed/Peer-reviewed Language processing requires memory retrieval to integrate current input with previous context and making predictions about upcoming input. We propose that prediction and retrieval are two sides of the same coin, i.e. functionally the same, as they both activate memory representations. Under this assumption, memory retrieval and prediction should interact: Retrieval interference can only occur at a word that triggers retrieval and a fully predicted word would not do that. The present study investigated the proposed interaction with event-related potentials (ERPs) during the processing of sentence pairs in German. Predictability was measured via cloze probability. Memory retrieval was manipulated via the position of a distractor inducing proactive or retroactive similarity-based interference. Linear mixed model analyses provided evidence for the hypothesised interaction in a broadly distributed negativity, which we discuss in relation to the interference ERP literature. Our finding supports the proposal that memory retrieval and prediction are functionally the same.

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.