Aberrant Static and Dynamic Functional Brain Network in Depression Based on EEG Source Localization.

Objective: Depression is accompanied by abnormalities in large-scale functional brain networks. This paper combined static and dynamic methods to analyze the abnormal topology and changes of functional connectivity network (FCN) of depression.

Methods: We collected resting-state EEG recordings from 27 depressed subjects and 28 normal subjects, then obtained 68 regions of interests (ROIs) by source localization.

EEG based depression recognition using improved graph convolutional neural network.

Depression is a global psychological disease that does serious harm to people. Traditional diagnostic method of the doctor-patient communication, is not objective and accurate enough. Thus, a more accurate and objective method for depression detection is urgently needed.