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Why do humans have unique auditory event-related fields?: Evidence from computational modeling and MEG experiments

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Why do humans have unique auditory event-related fields? Evidence from computational modeling and MEG experiments. / Hajizadeh, Aida; Matysiak, Artur; Brechmann, André; König, Reinhard; May, Patrick J C.

In: Psychophysiology, 21.01.2021.

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Hajizadeh, Aida ; Matysiak, Artur ; Brechmann, André ; König, Reinhard ; May, Patrick J C. / Why do humans have unique auditory event-related fields? Evidence from computational modeling and MEG experiments. In: Psychophysiology. 2021.

Bibtex

@article{a5ec0565d7f249efa6b70234e013bb6e,
title = "Why do humans have unique auditory event-related fields?: Evidence from computational modeling and MEG experiments",
abstract = "Auditory event-related fields (ERFs) measured with magnetoencephalography (MEG) are useful for studying the neuronal underpinnings of auditory cognition in human cortex. They have a highly subject-specific morphology, albeit certain characteristic deflections (e.g., P1m, N1m, and P2m) can be identified in most subjects. Here, we explore the reason for this subject-specificity through a combination of MEG measurements and computational modeling of auditory cortex. We test whether ERF subject-specificity can predominantly be explained in terms of each subject having an individual cortical gross anatomy, which modulates the MEG signal, or whether individual cortical dynamics is also at play. To our knowledge, this is the first time that tools to address this question are being presented. The effects of anatomical and dynamical variation on the MEG signal is simulated in a model describing the core-belt-parabelt structure of the auditory cortex, and with the dynamics based on the leaky-integrator neuron model. The experimental and simulated ERFs are characterized in terms of the N1m amplitude, latency, and width. Also, we examine the waveform grand-averaged across subjects, and the standard deviation of this grand average. The results show that the intersubject variability of the ERF arises out of both the anatomy and the dynamics of auditory cortex being specific to each subject. Moreover, our results suggest that the latency variation of the N1m is largely related to subject-specific dynamics. The findings are discussed in terms of how learning, plasticity, and sound detection are reflected in the auditory ERFs. The notion of the grand-averaged ERF is critically evaluated.",
keywords = "anatomy, auditory cortex, computational modeling, dynamics, event‐related field, ERF, latency, magnetoencephalography, MEG, N1m",
author = "Aida Hajizadeh and Artur Matysiak and Andr{\'e} Brechmann and Reinhard K{\"o}nig and May, {Patrick J C}",
note = "{\textcopyright} 2021 The Authors. Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research.",
year = "2021",
month = jan,
day = "21",
doi = "10.1111/psyp.13769",
language = "English",
journal = "Psychophysiology",
issn = "0048-5772",
publisher = "John Wiley & Sons, Ltd (10.1111)",

}

RIS

TY - JOUR

T1 - Why do humans have unique auditory event-related fields?

T2 - Evidence from computational modeling and MEG experiments

AU - Hajizadeh, Aida

AU - Matysiak, Artur

AU - Brechmann, André

AU - König, Reinhard

AU - May, Patrick J C

N1 - © 2021 The Authors. Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research.

PY - 2021/1/21

Y1 - 2021/1/21

N2 - Auditory event-related fields (ERFs) measured with magnetoencephalography (MEG) are useful for studying the neuronal underpinnings of auditory cognition in human cortex. They have a highly subject-specific morphology, albeit certain characteristic deflections (e.g., P1m, N1m, and P2m) can be identified in most subjects. Here, we explore the reason for this subject-specificity through a combination of MEG measurements and computational modeling of auditory cortex. We test whether ERF subject-specificity can predominantly be explained in terms of each subject having an individual cortical gross anatomy, which modulates the MEG signal, or whether individual cortical dynamics is also at play. To our knowledge, this is the first time that tools to address this question are being presented. The effects of anatomical and dynamical variation on the MEG signal is simulated in a model describing the core-belt-parabelt structure of the auditory cortex, and with the dynamics based on the leaky-integrator neuron model. The experimental and simulated ERFs are characterized in terms of the N1m amplitude, latency, and width. Also, we examine the waveform grand-averaged across subjects, and the standard deviation of this grand average. The results show that the intersubject variability of the ERF arises out of both the anatomy and the dynamics of auditory cortex being specific to each subject. Moreover, our results suggest that the latency variation of the N1m is largely related to subject-specific dynamics. The findings are discussed in terms of how learning, plasticity, and sound detection are reflected in the auditory ERFs. The notion of the grand-averaged ERF is critically evaluated.

AB - Auditory event-related fields (ERFs) measured with magnetoencephalography (MEG) are useful for studying the neuronal underpinnings of auditory cognition in human cortex. They have a highly subject-specific morphology, albeit certain characteristic deflections (e.g., P1m, N1m, and P2m) can be identified in most subjects. Here, we explore the reason for this subject-specificity through a combination of MEG measurements and computational modeling of auditory cortex. We test whether ERF subject-specificity can predominantly be explained in terms of each subject having an individual cortical gross anatomy, which modulates the MEG signal, or whether individual cortical dynamics is also at play. To our knowledge, this is the first time that tools to address this question are being presented. The effects of anatomical and dynamical variation on the MEG signal is simulated in a model describing the core-belt-parabelt structure of the auditory cortex, and with the dynamics based on the leaky-integrator neuron model. The experimental and simulated ERFs are characterized in terms of the N1m amplitude, latency, and width. Also, we examine the waveform grand-averaged across subjects, and the standard deviation of this grand average. The results show that the intersubject variability of the ERF arises out of both the anatomy and the dynamics of auditory cortex being specific to each subject. Moreover, our results suggest that the latency variation of the N1m is largely related to subject-specific dynamics. The findings are discussed in terms of how learning, plasticity, and sound detection are reflected in the auditory ERFs. The notion of the grand-averaged ERF is critically evaluated.

KW - anatomy

KW - auditory cortex

KW - computational modeling

KW - dynamics

KW - event‐related field

KW - ERF

KW - latency

KW - magnetoencephalography

KW - MEG

KW - N1m

U2 - 10.1111/psyp.13769

DO - 10.1111/psyp.13769

M3 - Journal article

C2 - 33475173

JO - Psychophysiology

JF - Psychophysiology

SN - 0048-5772

M1 - e13769

ER -