基于微状态的抑郁症静息态脑电信号分析  

Analysis of resting EEG signals for depression based on microstates

作　　者：陈学莹 齐晓英 史周晰 独盟盟 CHEN Xueying;QI Xiaoying;SHI Zhouxi;DU Mengmeng(School of Mathematics and Data Science,Shaanxi University of Science and Technology,Xi’an 710021;School of Medicine,Yan'an University,Yan’an 716000)

机构地区：[1]陕西科技大学数学与数据科学学院,西安710021 [2]延安大学医学院,延安716000

出　　处：《高技术通讯》2024年第4期379-385,共7页Chinese High Technology Letters

基　　金：国家自然科学基金(12102240)资助项目。

摘　　要：抑郁症(MDD)患者存在认知功能障碍,但其瞬时神经异常活动尚未研究清楚,对此采用脑电(EEG)微状态方法对抑郁症患者的脑电数据进行研究。比较22名抑郁症患者和25名正常人的128导闭眼脑电数据微状态特征,进行差异性分析并探索与量表得分之间的相关性。结果发现,相对于健康对照组,抑郁症患者微状态C的出现次数和涵盖比更高,且与其他微状态之间的转换概率较高,而其微状态D的平均持续时间较低,且与微状态B之间的转换次数减少。此外,微状态C和微状态D与抑郁量表和焦虑量表均呈显著相关性,表明基于脑电微状态方法可以捕捉到抑郁症患者异常大脑动态特性,为抑郁症临床早期诊治提供客观参考。Patients with major depressive disorder(MDD)have cognitive dysfunction,but current studies did not clearly investigate its temporal abnormal neurological activity.In response to this problem,this paper uses the electroencephalogram(EEG)microstate method to study the EEG data of patients with major depression.This paper compares the microstate characteristics of 128-channel EEG data from 22 patients with major depressive disorder and 25 healthy controls,performs statistical analysis and explores correlations with scale scores.Results show that compared with healthy controls,the occurrence and coverage of microstateCin major depressive disorder group are higher,and the transition probabilities between other microstates andCare also higher,while the average duration of microstateDis lower and the number of transitions betweenDand microstateBsignificantly decreases.In addition,microstatesCand microstatesDare significantly correlated with the depression scale and anxiety scale.The results show that the EEG-based microstate method can capture the abnormal brain dynamic characteristics of depressed patients,and provide an objective reference for the early clinical diagnosis and treatment of depression.

关 键 词：抑郁症(MDD) 静息态脑电(EEG) 脑电信号处理 微状态 聚类 

分 类 号：R749.4[医药卫生—神经病学与精神病学] TN911.7[医药卫生—临床医学]