University Of Tasmania
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Reliability of EEG microstate analysis at different electrode densities during propofol-induced transitions of brain states

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journal contribution
posted on 2023-09-12, 03:27 authored by K Zhang, W Shi, C Wang, Y Li, Z Liu, T Liu, J Li, X Yan, Q Wang, Z Cao, G Wang

Electroencephalogram (EEG) microstate analysis is a promising and effective spatio-temporal method that can segment signals into several quasi-stable classes, providing a great opportunity to invertigate short-range and long-range neural dynamics. However, there are still many controversies in terms of reproducibility and reliability when selecting different parameters or datatypes.

In this study, five types of electrode configurations (including 91, 64, 32, 19, and 8 channels) , were configured to measure the reliability of microstate analysis at different five electrode densities during the propofol-induced sedation.

First, the microstate topography and parameters at different five electrode densities were compared between the baseline (BS) condition and the moderate sedation (MD) condition, respectively. The intraclass correlation coefficient (ICC) and coefficient of variation (CV) were introduced to quantify the consistency of the microstate parameters. Second, the statistical analysis and classification between BS and MD were performed to determine whether the microstate differences between different conditions can remain stable at different electrode densities, and ICC is also calculated between different condition to measure the consistency of the results in a single condition.

The results showed that either in BS condition or the MD condition, there were few significant differences of microstate parameters among the configurations of 91, 64, and 32 channels, and the majority differences existed between the configurations of 19 and 8 channels and other channels. The ICC and CV also showed that the consistency among the configurations of 91, 64, and 32 channels was better than that among all 5 types of electrode configurations after involving 19 and 8 channels. Furthermore, the significant differences between the conditions in 91 channels remained stable those in 64 and 32 channels, but it disappeared for the conditions in 19 and 8 channels. In addition, the results of classification and ICC showed that the microstate analysis becomes unreliable with less than 20 electrodes.

The findings in this study supports our hypothesis that the microstate analysis of different brain states is more reliable with high electrode densities and it is not recommended to use with a small number of channels for EEG microstate analysis.


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Information and Communication Technology


Academic Press Inc Elsevier Science

Publication status

  • Published

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525 B St, Ste 1900, San Diego, USA, Ca, 92101-4495

Rights statement

© 2021 The Author(s). Published by Elsevier Inc.

Socio-economic Objectives

220402 Applied computing