ORCID Profile
0000-0003-4131-8077
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Linguistics | Linguistic Structures (incl. Grammar, Phonology, Lexicon, Semantics) |
Conserving Aboriginal and Torres Strait Islander Heritage | Expanding Knowledge in Psychology and Cognitive Sciences | Expanding Knowledge in Language, Communication and Culture
Publisher: Cold Spring Harbor Laboratory
Date: 08-06-2022
DOI: 10.1101/2022.06.07.495229
Abstract: In idual differences in second language (L2) learning can offer insights into the neurobiological bases of learning aptitude. One neurophysiological marker of inter-in idual differences in cognition is the in idual 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 litude), we report data from a modified miniature language learning study. After a vocabulary learning period, participants ( N = 38, M age = 25.3, SD = 7.13) judged the grammaticality of classifier-noun pairs, with mixed-effects modelling revealing lower IAF in iduals were better than higher IAF in iduals at grammaticality judgements. N400 litude also reduced across the experiment in low relative to high IAF in iduals, indicating the relationship between IAF and language learning is more complex than initially postulated.
Publisher: Cold Spring Harbor Laboratory
Date: 07-10-2019
DOI: 10.1101/788976
Abstract: 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 (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.
Publisher: Cold Spring Harbor Laboratory
Date: 27-05-2021
DOI: 10.1101/2021.05.27.445993
Abstract: 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 c us. 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 c us 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.
Publisher: Cold Spring Harbor Laboratory
Date: 17-02-2017
DOI: 10.1101/109355
Abstract: Sanborn and Chater propose an interesting theory of cognitive and brain function based on Bayesian s ling instead of asymptotic Bayesian inference. Their proposal unifies many current observations and models and, in spite of focusing primarily on cognitive phenomena, their work provides a springboard for unifying several proposed theories of brain function. It has the potential to serve as a bridge between three influential overarching current theories of cognitive and brain function: Bayesian models, Friston's theory of cortical responses based on the free-energy principle, and attractor-basin dynamics. Specifically, their proposal suggests a high-level perspective on Friston's theory, which in turn proposes a s ling procedure including appropriate handling of autocorrelation as well as a plausible neurobiological implementation. In turn, these two theories together link into attractor-basin dynamics at the level of networks (via Friston) as well at the level of behavior (via the relationship between the modes of prior and posterior distributions, as discussed by Sanborn and Chater). We will argue here that, by linking Sanborn and Chater's approach to neurobiological models based on the free-energy principle on the one hand and attractor-basin dynamics on the other, the scope of their proposal can be broadened considerably. Moreover, a unified perspective along these lines provides an elegant solution to several of Sanborn and Chater's Outstanding Questions relating to the neural implementation of s ling.
Publisher: Informa UK Limited
Date: 20-01-2022
Publisher: Cold Spring Harbor Laboratory
Date: 11-11-2017
DOI: 10.1101/218123
Abstract: We hypothesise 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 optimise 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.
Publisher: Wiley
Date: 21-01-2017
DOI: 10.1111/PSYP.13064
Abstract: In idual alpha frequency (IAF) is a promising electrophysiological marker of interin idual 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 in idualized 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.
Publisher: Cold Spring Harbor Laboratory
Date: 06-07-2016
DOI: 10.1101/062299
Abstract: 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 auditory language processing in a naturalistic setting. Despite the large variability between trials during naturalistic stimulation, we replicated previous findings from the literature: frequency, animacy, word order. This suggests a new perspective on ERPs, namely as a continuous modulation reflecting continuous model updates (cf. Friston, 2005) instead of a series of discrete and essentially sequential processes.
Publisher: Cold Spring Harbor Laboratory
Date: 31-08-2021
DOI: 10.1101/2021.08.29.456571
Abstract: Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more in iduals engaging cooperatively in real-world tasks, such as in operational training environments. In this exploratory study, we recruited forty in iduals 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., in idual 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.
Publisher: Springer Science and Business Media LLC
Date: 16-11-2021
DOI: 10.1038/S41598-021-01772-8
Abstract: 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 c us. 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 c us 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.
Publisher: Cold Spring Harbor Laboratory
Date: 24-03-2022
DOI: 10.1101/2022.03.23.485424
Abstract: 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 in idual information processing and performance capabilities. Previous research has identified electroencephalographic resting-state characteristics (most prominently: the in idual 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 in idual 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.
Publisher: Cold Spring Harbor Laboratory
Date: 15-12-2022
DOI: 10.1101/2022.12.14.520501
Abstract: In 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 in idual 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 in idual 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 in idual’s 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.
Publisher: Cold Spring Harbor Laboratory
Date: 09-04-2031
No related organisations have been discovered for Matthias Schlesewsky.
Start Date: 04-2021
End Date: 03-2024
Amount: $321,616.00
Funder: Australian Research Council
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