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中华脑科疾病与康复杂志(电子版) ›› 2025, Vol. 15 ›› Issue (04) : 232 -237. doi: 10.3877/cma.j.issn.2095-123X.2025.04.007

短篇论著

基于静息态脑电图的慢性意识障碍微状态分析
赵光锐1, 吴玉璋2, 尹绍雅2, 陈光贵1,()   
  1. 1237000 安徽六安,安徽医科大学附属六安医院(六安市人民医院)神经外科
    2300350 天津,天津大学环湖医院神经外科
  • 收稿日期:2024-11-12 出版日期:2025-08-15
  • 通信作者: 陈光贵

Microstate analysis of prolonged disorders of consciousness based on resting-state electroencephalogram

Guangrui Zhao1, Yuzhang Wu2, Shaoya Yin2, Guanggui Chen1,()   

  1. 1Department of Neurosurgery, Lu'an People's Hospital Affiliated to Anhui Medical University (Lu'an People's Hospital), Lu'an 237000, China
    2Department of Neurosurgery, Tianjin University Huanhu Hospital, Tianjin 300350, China
  • Received:2024-11-12 Published:2025-08-15
  • Corresponding author: Guanggui Chen
  • Supported by:
    Tianjin Natural Science Foundation Project(20JCYBJC00930)
引用本文:

赵光锐, 吴玉璋, 尹绍雅, 陈光贵. 基于静息态脑电图的慢性意识障碍微状态分析[J/OL]. 中华脑科疾病与康复杂志(电子版), 2025, 15(04): 232-237.

Guangrui Zhao, Yuzhang Wu, Shaoya Yin, Guanggui Chen. Microstate analysis of prolonged disorders of consciousness based on resting-state electroencephalogram[J/OL]. Chinese Journal of Brain Diseases and Rehabilitation(Electronic Edition), 2025, 15(04): 232-237.

目的

通过分析慢性意识障碍(pDOC)患者静息态脑电图微状态特征,探寻pDOC患者特征性电生理标志物。

方法

选取安徽医科大学附属六安医院神经外科自2021年1月至2024年3月收治的23例pDOC患者作为pDOC组,同期纳入于本院体检的17名健康受试者为健康组。收集受试者的静息态视频脑电图资料。通过基于Matlab数学计算平台的EEGLAB工具包进行微状态聚类,分析微状态指标(平均持续时间、出现频率、时间覆盖率)。

结果

2组受试者的微状态A、C和D地形图形态相似,微状态B的地形图形态差别较大。pDOC组微状态B的时间覆盖率(0.37±0.14)高于健康组(0.29±0.10),微状态D的出现频率(2.96±0.75)和时间覆盖率[0.27(0.23,0.42)]均低于健康组[3.36±0.42,0.35(0.30,0.39)],差异有统计学意义(P<0.05)。

结论

pDOC患者的微状态B地形图呈左右分布,这可能成为判断pDOC及意识障碍程度的电生理标志物。

Objective

To explore the characteristic electrophysiological markers of patients with prolonged disorders of consciousness (pDOC) by analyzing the resting-state electroencephalogram (EEG) microstate features of patients with pDOC.

Methods

Twenty three patients with pDOC admitted to the Neurosurgery Department of Lu'an People's Hospital Affiliated to Anhui Medical University from January 2021 to March 2024 were selected as the pDOC group, and 17 healthy subjects who underwent physical examination in our hospital were collected as the healthy group at the same time. Video EEG data of resting-state were collected. Microstate clustering was performed using the EEGLAB toolkit based on the Matlab mathematical calculation platform, and statistical analysis was conducted on micro-state indicators (average duration, occurrence frequency, time coverage) between two groups.

Results

The microstate topographic maps A, C and D of the two groups were similar, while the topographic maps of microstate B were significantly different. The time coverage rate of microstate B in the pDOC group (0.37±0.14) was higher than that in the healthy group (0.29±0.10), and the frequency of microstate D (2.96±0.75) and time coverage rate [0.27 (0.23, 0.42)] were lower than those in the healthy group [3.36±0.42, 0.35 (0.30, 0.39)], with statistically significant differences (P<0.05).

Conclusions

The microstate B of pDOC patients has a marked left-right distribution, which may serve as an electrophysiological marker for future assessment of pDOC and degree of consciousness impairment.

表1 23例pDOC患者的临床特征
Tab.1 Clinical characteristics of 23 patients of pDOC
图1 2组受试者的微状态地形图对比A:微状态A地形图组间相似度高并呈前后分布;B:微状态B地形图存在明显差异,pDOC组呈左右分布,健康组呈前后分布;C:微状态C地形图组间存在相似性,呈左额颞-右顶枕分布,D:微状态D地形图组间存在相似性,呈右额颞-左顶枕方向分布
Fig.1 Comparison of microstate topographic maps of two groups
表2 2组受试者的4种微状态指标比较
Tab.2 Comparison of 4 micro-state indicators between the two groups
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