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MEG cortical microstates: Spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses

Luke Tait, Jiaxiang Zhang Orcid Logo

NeuroImage, Volume: 251, Start page: 119006

Swansea University Author: Jiaxiang Zhang Orcid Logo

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DOI (Published version): 10.1016/j.neuroimage.2022.119006

Abstract

EEG microstate analysis is an approach to study brain states and their fast transitions in healthy cognition and disease. A key limitation of conventional microstate analysis is that it must be performed at the sensor level, and therefore gives limited anatomical insight. Here, we generalise the mic...

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Published in: NeuroImage
ISSN: 1053-8119
Published: Elsevier BV 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa61345
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Abstract: EEG microstate analysis is an approach to study brain states and their fast transitions in healthy cognition and disease. A key limitation of conventional microstate analysis is that it must be performed at the sensor level, and therefore gives limited anatomical insight. Here, we generalise the microstate methodology to be applicable to source-reconstructed electrophysiological data. Using simulations of a neural-mass network model, we first established the validity and robustness of the proposed method. Using MEG resting-state data, we uncovered ten microstates with distinct spatial distributions of cortical activation. Multivariate pattern analysis demonstrated that source-level microstates were associated with distinct functional connectivity patterns. We further demonstrated that the occurrence probability of MEG microstates were altered by auditory stimuli, exhibiting a hyperactivity of the microstate including the auditory cortex. Our results support the use of source-level microstates as a method for investigating brain dynamic activity and connectivity at the millisecond scale.
College: Faculty of Science and Engineering
Funders: This study was supported by European Research Council [grant number 716321].
Start Page: 119006

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