针对局灶性癫痫患者的脑电微状态分析

张克旭 1; 杜昌旺 2; 赵浩淇 1; 李扩 2; 张益榕 1; 王畅 1; 刘晓芳 2; 闫相国 1; 王刚 1

doi:10.7652/xjtuxb202009018

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针对局灶性癫痫患者的脑电微状态分析

更新时间：2025-07-09

- 针对局灶性癫痫患者的脑电微状态分析
- Analysis of Brain Microstates in Patients with Focal Epilepsy
- 西安交通大学学报 2020年54卷第9期页码：157-163
- 作者机构：
  
  西安交通大学生物医学信息工程教育部重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2020-01-11。作者简介: 张克旭(1998—),男,本科生;王刚(通信作者),男,副教授。基金项目: 国家自然科学基金资助项目(315710000);陕西省自然科学基础研究计划资助项目(2020JM-037)
- DOI：10.7652/xjtuxb202009018
  中图分类号： R318.04
- 网络首发：2020-09-10，
  
  纸质出版：2020
- 稿件说明：
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张克旭 1, 杜昌旺 2, 赵浩淇 1, 等. 针对局灶性癫痫患者的脑电微状态分析[J]. 西安交通大学学报, 2020,54(9):157-163.

Analysis of Brain Microstates in Patients with Focal Epilepsy[J]. 2020, 54(9): 157-163.
张克旭 1, 杜昌旺 2, 赵浩淇 1, 等. 针对局灶性癫痫患者的脑电微状态分析[J]. 西安交通大学学报, 2020,54(9):157-163. DOI： 10.7652/xjtuxb202009018.

Analysis of Brain Microstates in Patients with Focal Epilepsy[J]. 2020, 54(9): 157-163. DOI： 10.7652/xjtuxb202009018.

摘要

针对脑电的癫痫神经机制研究仅限于致痫灶相关的局部脑区

提出利用脑电微状态从全局角度揭示癫痫发病的神经机制。使用修正K均值聚类算法提取了癫痫患者发作间期的特征微状态

并与连续脑电信号配对得到微状态序列; 计算每种微状态的平均持续时间、总占比、每秒出现次数

对比癫痫患者和正常人的参数相对趋势差异; 利用小波变换的方法分析癫痫患者微状态序列的分形特性。研究发现:癫痫患者的微状态D的平均持续时间为(101.42±22.91)ms、在整个时间序列上的总占比为(30.86±9.79)%、出现频率为(3.10±0.94)次1 s

数值结果显著大于微状态A、B

和微状态C相近

和正常人趋势不同; 在32 ms～16 s的时间尺度上

分形分析的结果显示癫痫脑电微状态序列的赫斯特指数为0.643 5±0.010 2

具有分形特性。微状态D的参数异常解释了癫痫患者易出现注意力缺失的现象; 癫痫微状态参数相对趋势变化对癫痫疾病诊断有参考意义; 癫痫微状态序列的分形性质表明了序列在很大的时间范围内具有自相似、无标度的特性

使微状态序列具有研究癫痫发病机制和预测癫痫发作的潜力。

Abstract

Current study of the neural mechanism of epilepsy based on electroencephalography(EEG)is limited to the epilepsy-related local brain regions. This study uses microstate to reveal the cerebral neural mechanism of epilepsy from a global perspective. The modified K-means algorithm is used to cluster typical microstates of epileptic patients

and the sequence of the microstates is obtained by fitting the microstates with the continuous EEG signals. The duration

coverage and occurrence are calculated to compare the relative trend difference of parameters between patients and healthy people. Then wavelet transform is employed to test the fractal characteristics of EEG microstates sequence. Results show that the mean duration of epileptic patients- microstate D is(101.42-22.91)ms

the proportion of microstate D in the entire time series is(30.86-9.79)%

and the occurrence of microstate D is(3.10-0.94)times per second. The values of the parameters of microstate D are significantly larger

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references

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