On the Reliability of the EEG Microstate Approach.

Kleinert, Tobias; Koenig, Thomas; Nash, Kyle; Wascher, Edmund (2024). On the Reliability of the EEG Microstate Approach. Brain topography, 37(2), pp. 271-286. Springer 10.1007/s10548-023-00982-9

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EEG microstates represent functional brain networks observable in resting EEG recordings that remain stable for 40-120ms before rapidly switching into another network. It is assumed that microstate characteristics (i.e., durations, occurrences, percentage coverage, and transitions) may serve as neural markers of mental and neurological disorders and psychosocial traits. However, robust data on their retest-reliability are needed to provide the basis for this assumption. Furthermore, researchers currently use different methodological approaches that need to be compared regarding their consistency and suitability to produce reliable results. Based on an extensive dataset largely representative of western societies (2 days with two resting EEG measures each; day one: n = 583; day two: n = 542) we found good to excellent short-term retest-reliability of microstate durations, occurrences, and coverages (average ICCs = 0.874-0.920). There was good overall long-term retest-reliability of these microstate characteristics (average ICCs = 0.671-0.852), even when the interval between measures was longer than half a year, supporting the longstanding notion that microstate durations, occurrences, and coverages represent stable neural traits. Findings were robust across different EEG systems (64 vs. 30 electrodes), recording lengths (3 vs. 2 min), and cognitive states (before vs. after experiment). However, we found poor retest-reliability of transitions. There was good to excellent consistency of microstate characteristics across clustering procedures (except for transitions), and both procedures produced reliable results. Grand-mean fitting yielded more reliable results compared to individual fitting. Overall, these findings provide robust evidence for the reliability of the microstate approach.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > University Psychiatric Services > University Hospital of Psychiatry and Psychotherapy > Translational Research Center

UniBE Contributor:

König, Thomas

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1573-6792

Publisher:

Springer

Language:

English

Submitter:

Pubmed Import

Date Deposited:

10 Jul 2023 10:10

Last Modified:

23 Feb 2024 00:12

Publisher DOI:

10.1007/s10548-023-00982-9

PubMed ID:

37410275

Uncontrolled Keywords:

Clustering EEG microstates Fitting Retest reliability Stability

BORIS DOI:

10.48350/184561

URI:

https://boris.unibe.ch/id/eprint/184561

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