脑电微状态分析方法及其在认知障碍患者中的应用

doi:10.3969/j.issn.0258-8021.2026.01.009

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Abstract Electroencephalogram (EEG) microstates can characterize the spatiotemporal dynamic network reorganization in the brain by capturing transient stable patterns of global potential distribution. The core value lies in resolving the discontinuous transitions and non-stationary conversion characteristics of functional brain states. However, conventional analysis methods for the microstates face challenges in standardization due to technical heterogeneity in workflows and classification uncertainty, limiting the comparability of cross-study results. This review systematically elaborated the fundamental principles and extraction procedures of microstate analysis, covering key technical steps including signal preprocessing, frequency band optimization, and clustering method selection. Rresearch advancements in traditional feature parameters and dynamic syntactic characteristics were summarized. Focusing on cognitive impairment research, this article discussed current applications of the microstate analysis in patients with Alzheimer′s disease (AD) and mild cognitive impairment (MCI), including feature characterization, disease diagnosis, and cognitive assessment. Finally, potential challenges and future research directions were discussed, with the aim of providing valuable references for researchers in this field.

Key words： electroencephalogram microstate Alzheimer′s disease mild cognitive impairment

Received: 28 May 2025

PACS:

R318

Corresponding Authors: ^*E-mail: yinliyong81@163.com

About author:: ^#Member,Chinese Society of Biomedical Engineering

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	Li Zipeng
	Li Xin
	Qu Zhongjie
	Su Rui
	Yin Bowen
	Yin Liyong

Cite this article:

Li Zipeng,Li Xin,Qu Zhongjie, et al. Analytical Methods of EEG Microstates and Applications in Cognitive Impairment Patient[J]. Chinese Journal of Biomedical Engineering, 2026, 45(1): 87-99.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2026.01.009 OR http://cjbme.csbme.org/EN/Y2026/V45/I1/87

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