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+microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG

Luke Tait Orcid Logo, Jiaxiang Zhang Orcid Logo

NeuroImage, Volume: 258, Start page: 119346

Swansea University Author: Jiaxiang Zhang Orcid Logo

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DOI (Published version): 10.1016/j.neuroimage.2022.119346

Abstract

+microstate is a MATLAB toolbox for brain functional microstate analysis. It builds upon previous EEG microstate literature and toolboxes by including algorithms for source-space microstate analysis. +microstate includes codes for performing individual- and group-level brain microstate analysis in r...

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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/cronfa61201
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spelling 2022-10-06T10:58:39.3605009 v2 61201 2022-09-13 +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG 555e06e0ed9a87608f2d035b3bde3a87 0000-0002-4758-0394 Jiaxiang Zhang Jiaxiang Zhang true false 2022-09-13 MACS +microstate is a MATLAB toolbox for brain functional microstate analysis. It builds upon previous EEG microstate literature and toolboxes by including algorithms for source-space microstate analysis. +microstate includes codes for performing individual- and group-level brain microstate analysis in resting-state and task-based data including event-related potentials/fields. Functions are included to visualise and perform statistical analysis of microstate sequences, including novel advanced statistical approaches such as statistical testing for associated functional connectivity patterns, cluster-permutation topographic ANOVAs, and analysis of microstate probabilities in response to stimuli. Additionally, codes for simulating microstate sequences and their associated M/EEG data are included in the toolbox, which can be used to generate artificial data with ground truth microstates and to validate the methodology. +microstate integrates with widely used toolboxes for M/EEG processing including Fieldtrip, SPM, LORETA/sLORETA, EEGLAB, and Brainstorm to aid with accessibility, and includes wrappers for pre-existing toolboxes for brain-state estimation such as Hidden Markov modelling (HMM-MAR) and independent component analysis (FastICA) to aid with direct comparison with these techniques. In this paper, we first introduce +microstate before subsequently performing example analyses using open access datasets to demonstrate and validate the methodology. MATLAB live scripts for each of these analyses are included in +microstate, to act as a tutorial and to aid with reproduction of the results presented in this manuscript. Journal Article NeuroImage 258 119346 Elsevier BV 1053-8119 Microstate Analysis; Electroencephalography; Magnetoencephalography; Functional Connectivity Dynamics; Toolbox 1 9 2022 2022-09-01 10.1016/j.neuroimage.2022.119346 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University This study was supported by European Research Council [grant number 716321]. 2022-10-06T10:58:39.3605009 2022-09-13T13:51:35.8286456 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Luke Tait 0000-0002-2351-5328 1 Jiaxiang Zhang 0000-0002-4758-0394 2 61201__25314__d10be5ca133a4ddd9158dfeb9aed077b.pdf 61201_VoR.pdf 2022-10-06T10:57:02.8874315 Output 3265709 application/pdf Version of Record true © 2022 The Authors. This is an open access article under the CC BY license true eng http://creativecommons.org/licenses/by/4.0/
title +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
spellingShingle +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
Jiaxiang Zhang
title_short +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
title_full +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
title_fullStr +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
title_full_unstemmed +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
title_sort +microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
author_id_str_mv 555e06e0ed9a87608f2d035b3bde3a87
author_id_fullname_str_mv 555e06e0ed9a87608f2d035b3bde3a87_***_Jiaxiang Zhang
author Jiaxiang Zhang
author2 Luke Tait
Jiaxiang Zhang
format Journal article
container_title NeuroImage
container_volume 258
container_start_page 119346
publishDate 2022
institution Swansea University
issn 1053-8119
doi_str_mv 10.1016/j.neuroimage.2022.119346
publisher Elsevier BV
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
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description +microstate is a MATLAB toolbox for brain functional microstate analysis. It builds upon previous EEG microstate literature and toolboxes by including algorithms for source-space microstate analysis. +microstate includes codes for performing individual- and group-level brain microstate analysis in resting-state and task-based data including event-related potentials/fields. Functions are included to visualise and perform statistical analysis of microstate sequences, including novel advanced statistical approaches such as statistical testing for associated functional connectivity patterns, cluster-permutation topographic ANOVAs, and analysis of microstate probabilities in response to stimuli. Additionally, codes for simulating microstate sequences and their associated M/EEG data are included in the toolbox, which can be used to generate artificial data with ground truth microstates and to validate the methodology. +microstate integrates with widely used toolboxes for M/EEG processing including Fieldtrip, SPM, LORETA/sLORETA, EEGLAB, and Brainstorm to aid with accessibility, and includes wrappers for pre-existing toolboxes for brain-state estimation such as Hidden Markov modelling (HMM-MAR) and independent component analysis (FastICA) to aid with direct comparison with these techniques. In this paper, we first introduce +microstate before subsequently performing example analyses using open access datasets to demonstrate and validate the methodology. MATLAB live scripts for each of these analyses are included in +microstate, to act as a tutorial and to aid with reproduction of the results presented in this manuscript.
published_date 2022-09-01T02:32:06Z
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