Biology subjects

Schlesewsky, M.

Publications and source records attributed to Schlesewsky, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Verb-Specific Linking Properties Modulate the N400 Effect: Evidence from Thematic Reversal Anomalies in Malayalam

The present study examined whether thematic reversal anomalies are processed similarly across subject and object experiencer constructions in Malayalam. Event-related brain potentials (ERPs) were recorded as 30 first-language speakers of Malayalam read transitive sentences with the two types of experiencer verbs, in which the thematic role assignment for the preceding arguments was either correct or reverse. The reversal anomaly became apparent only at the position of the experiencer verb. A linear mixed-models analysis confirmed a biphasic N400-P600 effect at the verb for both verb types when the argument roles were reverse. Thus, our results suggest a uniform processing strategy for TRAs irrespective of the type of experiencer verb involved. However, the N400 amplitude was larger for the object experiencer verb compared to subject experiencer verbs. We suggest that the quantitative difference observed for object experiencer verbs is due to the inverse linking of grammatical function and thematic roles associated with these verbs. In other words, verb-specific linking properties modulate the processing of TRAs involving object experiencer verbs. We argue that this modulation occurs because the parser recalibrates cue weighting when the expected form-to-meaning mappings are overridden by the inverse linking properties of object experiencer verbs.

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bioRxiv2025

The absent P3a. Performance monitoring ERPs differentiate trust in humans and autonomous systems.

To address suggestions that human brain responses to autonomous system errors may be used as brain-based measures of trust in automation, the present study asked participants to monitor the performance of either a virtual human or an autonomous system partner performing a novel, complex, real-world image classification task. We predicted visual feedback of partner errors would elicit the feedback-related negativity and P3 ERP components, and that these components would differ between the human and system groups. Behavioural results showed that while participants calibrated their trust in their partner according to our intended manipulation of error rates, no group differences were found. The ERP data, however, revealed FRN and P3 effects for both groups, modulated by accuracy and error rate. An unexpected finding was that the P3 topography differed between groups, with both a frontal P3a and posterior P3b component seen for the human condition, while for the system condition only the posterior P3b was observed and the P3a was completely absent. We suggest that this selective absence of the P3a may reflect reduced frontal attention during system monitoring in passive task conditions potentially resulting from reduced social and emotional processing for the system partner. This study demonstrates the potential for EEG-based measures of trust in automation to surpass the sensitivity of traditional measures of trust, while additionally uncovering a potential neural signature of automation complacency in the absent P3a. This identifies potential boundary conditions under which the application of human correlates of performance monitoring may not apply to the monitoring of an automated system.

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bioRxiv2024

Predictive influences on memory encoding: investigating oscillations and the N400 event-related potential component

To effectively function in an ever-changing environment, the brain is proposed to make predictions about upcoming information. However, the association between prediction and memory formation and the role of between-subject neural variability in this relationship is unclear. To shed light on the relationship between prediction and memory, the present study reanalysed data from Jano, Chatburn, and colleagues (2024). In the original experiment, participants were exposed to naturalistic images in predictable and unpredictable four-item sequences, after which their memory was tested using an old/new paradigm. In the present analysis (N = 46), N400 amplitude and oscillatory power during learning was measured to gauge processes related to prediction error and memory encoding, respectively. This activity was compared with subsequent memory outcomes and individual alpha frequency (IAF) calculated at rest. Linear mixed-effects regressions revealed an alpha power subsequent memory effect that was not related to the amplitude of the N400, suggesting that memory encoding may occur independently of the level of prediction error. Notably, IAF influenced the relationship between theta power, N400 amplitude and subsequent memory, implying that the electrophysiological conditions for successful memory formation differ between individuals. Consequently, the degree to which prediction errors (presumably gauged via the N400) drive memory encoding could depend on inter-individual variability in intrinsic neural activity. These findings emphasise the flexible nature of memory, whilst having potential implications for prediction error-driven accounts of learning.

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bioRxiv2024

Augmenting complex and dynamic performance through mindfulness-based cognitive training: an investigation of on-task EEG dynamics.

Mindfulness-based cognitive training exhibits great propensity for improving cognitive performance across a range of contexts. However, the neurophysiological basis of these cognitive enhancements has remained relatively unclear. Previous studies have widely examined EEG during mindfulness practice - or made comparisons with long-term meditators and controls - but have failed to capture how EEG dynamics in subsequent cognitive testing scenarios might be altered as a function of mindfulness-based interventions. The current study therefore aimed to assess a variety of EEG dynamics (oscillatory, aperiodic, and event-related) during engagement in a dynamic and complex cognitive task, following a mindfulness-based cognitive training regime. Participants (n = 40, age range = 18 - 38) attended the lab on two separate occasions (pre- and post-a web-based one-week mindfulness intervention), where EEG was recorded during engagement in the Target Motion Analyst (TMA) task. Previous analysis of the same participants demonstrated that greater adherence to the mindfulness-based cognitive training was associated with improved performance on the TMA task (Dziego, Bornkessel-Schlesewsky, Schlesewsky et al., 2024). Here, we capitalise on these previous findings to assess whether adherence is paralleled by measurable differences in on-task EEG dynamics. Linear mixed-effects modelling demonstrated that, while main effects were observed across session, adherence to cognitive training was not directly associated with alpha power, theta power or 1/f parameters. Challenges also arose when computing event-related potentials (ERPs), illustrating the difficulties of using this technique in more complex testing environments. While these results are challenging to place within the context of previous EEG studies on meditation and cognitive performance, our findings highlight the complexities in understanding the cognitive benefits of mindfulness-based training interventions through EEG dynamics observed during subsequent cognitive testing.

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bioRxiv2023

Individual alpha frequency modulates prediction error-driven memory encoding

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

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bioRxiv2023

Augmenting complex and dynamic performance through mindfulness-based cognitive training: an evaluation of training adherence, trait mindfulness, personality and resting-state EEG.

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 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. Further analyses of resting-state electroencephalographic (EEG) metrics and additional individual factors demonstrated 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.

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bioRxiv2023

Expecting the unexpected: A reanalysis of a multi-laboratory study provides evidence for prediction in language

The extent to which the brain predicts upcoming information during language processing remains controversial. To shed light on this debate, the present study reanalysed Nieuwland and colleagues (2018) replication of DeLong et al. (2005). Participants (N = 356) viewed sentences containing articles and nouns of varying predictability, while their electroencephalogram was recorded. We measured event-related potentials (ERPs) preceding the critical words (namely the semantic prediction potential; SPP), in conjunction with post-word 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, SPP 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 (IAF) also modulated the relationship between article surprisal and the N400, emphasising 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.

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bioRxiv2022

Effects of neural noise on predictive model updating across the adult lifespan

AbstractIn the perceptual and sensorimotor domains, ageing is accompanied by a stronger reliance on top-down predictive model information and reduced sensory learning, thus promoting simpler, more efficient internal models in older adults. Here, we demonstrate analogous effects in higher-order language processing. One-hundred and twenty adults ranging in age from 18 to 83 years listened to short auditory passages containing manipulations of adjective order, with order probabilities varying between two speakers. As a measure of model adaptation, we examined attunement of the N400 event-related potential, a measure of precision-weighted prediction errors in language, to a trial-by-trial measure of speaker-based adjective order expectedness ("speaker-based surprisal") across the course of the experiment. Adaptation was strongest for young adults, weaker for middle-aged adults, and absent for older adults. Over and above age-related differences, we observed individual differences in model adaptation, with aperiodic (1/f) slope and intercept metrics derived from resting-state EEG showing the most pronounced modulations. We suggest that age-related changes in aperiodic slope, which have been linked to neural noise, may be associated with individual differences in the magnitude of stimulus-related prediction error signals. By contrast, changes in aperiodic intercept, which reflects aggregate population spiking, may relate to an individuals updating of inferences regarding stimulus precision. These two mechanisms jointly contribute to age-related changes in the precision-weighting of prediction errors and the degree of sensory learning.

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bioRxiv2022

Electrophysiological indices of individual differences in adult language learning

Individual differences in second language (L2) learning can offer insights into the neurobiological bases of learning aptitude. One neurophysiological marker of inter-individual differences in cognition is the individual alpha frequency (IAF), a trait-like measure correlated with cognition. Further, the N400 is an electrophysiological marker indexing stimulus irregularity and has been used to study L2 learning; however, its relationship with IAF and L2 learning remains unknown. To examine the relation between IAF and L2 learning (indexed by N400 amplitude), we report data from a modified miniature language learning study. After a vocabulary learning period, participants (N = 38, Mage = 25.3, SD = 7.13) judged the grammaticality of classifier-noun pairs, with mixed-effects modelling revealing lower IAF individuals were better than higher IAF individuals at grammaticality judgements. N400 amplitude also reduced across the experiment in low relative to high IAF individuals, indicating the relationship between IAF and language learning is more complex than initially postulated.

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bioRxiv2022

Neural and cognitive correlates of performance in dynamic multi-modal settings

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.

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bioRxiv2021

Neural signatures of teamwork: Evidence from real-world military training

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.

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bioRxiv2021

Additive Effects of Cognitive Load, Motor Demand, and Environmental Complexity on Attention: A Real-World EEG-study

The capacity to regulate ones 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.

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bioRxiv2021

Resting-state aperiodic neural dynamics predict individual differences in visuomotor performance and learning

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 description of action coordination and performance. 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 non-target stimuli selection. 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.

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bioRxiv2020

Individual Differences in Peripheral Hearing and Cognition Reveal Sentence Processing Differences in Healthy Older Adults

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 towards 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.

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bioRxiv2020

Oscillatory and aperiodic neural activity jointly predict grammar learning

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. Further, recent work has shown that non-oscillatory (1/f) 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 females, 18 males), we show for the first time that 1/f 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/f slope, while 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 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.

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bioRxiv2020

Slow wave-spindle coupling during sleep predicts language learning and associated oscillatory activity

Sentence comprehension involves the rapid decoding of both semantic and grammatical information, a process fundamental to communication. As with other complex cognitive processes, language comprehension relies, in part, on long-term memory. However, the electrophysiological mechanisms underpinning the initial encoding and generalisation of higher-order linguistic knowledge remain elusive, particularly from a sleep-based consolidation perspective. One candidate mechanism that may support the consolidation of higher-order language is the temporal coordination of slow oscillations (SO) and sleep spindles during non-rapid eye movement sleep (NREM). To examine this hypothesis, we analysed electroencephalographic (EEG) data recorded from 35 participants (Mage = 25.4, SD = 7.10; 16 males) during an artificial language learning task, contrasting performance between individuals who were given an 8hr nocturnal sleep period or an equivalent period of wake. We found that sleep relative to wake was associated with superior performance for rules that followed a sequence-based word order. Post-sleep sequence-based word order processing was further associated with less task-related theta desynchronisation, an electrophysiological signature of successful memory consolidation, as well as cognitive control and working memory. Frontal NREM SO-spindle coupling was also positively associated with behavioural sensitivity to sequence-based word order rules, as well as with task-related theta power. As such, theta activity during retrieval of previously learned information correlates with SO-spindle coupling, thus linking neural activity in the sleeping and waking brain. Taken together, this study presents converging behavioral and neurophysiological evidence for a role of NREM SO-spindle coupling and task-related theta activity as signatures of successful memory consolidation and retrieval in the context of higher-order language learning. SIGNIFICANCE STATEMENTThe endogenous temporal coordination of neural oscillations supports information processing during both wake and sleep states. Here we demonstrate that slow oscillation-spindle 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 theta power predict enhanced sensitivity to grammatical violations after a period of sleep and strong slow oscillation-spindle 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.

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bioRxiv2019

Semantic Reversal Anomalies under the Microscope: Task and Modality Influences on Language-Related ERP components

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 studys procedure and analysis (Bourguignon et al., 2012), 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.

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bioRxiv2019

Looking forward does not mean forgetting about the past: ERP evidence for the interplay of predictive coding and interference during language processing

Interference and prediction have independently been identified as crucial influencing factors during language processing. However, their interaction remains severely underinvestigated. Furthermore, the neurobiological basis of cue-based retrieval and retrieval interference during language processing remains insufficiently understood. Here, we present an ERP experiment that systematically examined the interaction of interference and prediction during language processing. We used the neurobiologically well-established predictive coding framework and insights regarding the neuronal mechanisms of memory for the theoretical framing of our study. German sentence pairs were presented word-by-word, with an article in the second sentence constituting the critical word. We analyzed mean single trial EEG activity in the N400 time window and found an interaction between interference and prediction (measured by cloze probability). Under high predictability, no interference effects were observable. Under the predictive coding account, highly predictable input is totally explained by top-down activity. Therefore the input induces no retrieval operations which could be influenced by interference. In contrast, under low predictability, conditions with high interference or with a close, low-interference distractor showed a broadly distributed negativity compared to conditions with a distant, low-interference distractor. We interpret this result as showing that when unpredicted input induces model updating, this may elicit memory retrieval including the evaluation of distractor items, thus leading to interference effects. We conclude that interference should be included in predictive coding-based accounts of language because prediction errors can trigger retrieval operations and, therefore, induce interference.

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