Analysis of resting EEG signals for depression based on microstates
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 electroen-cephalogram(EEG)microstate method to study the EEG data of patients with major depression.This paper com-pares 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 com-pared with healthy controls,the occurrence and coverage of microstate C in major depressive disorder group are higher,and the transition probabilities between other microstates and C are also higher,while the average duration of microstate D is lower and the number of transitions between D and microstate B significantly decreases.In addi-tion,microstates C and microstates D are 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 de-pressed patients,and provide an objective reference for the early clinical diagnosis and treatment of depression.
major depressive disorder(MDD)resting-state electroencephalogram(EEG)EEG signal pro-cessingmicrostateclustering
国家科技期刊平台
NSTL
万方数据
维普
