EEG-based major depressive disorder recognition by neural oscillation and asymmetry.

ABSTRACT:

Background

Major Depressive Disorder (MDD) is a pervasive mental health issue with significant diagnostic challenges. Electroencephalography (EEG) offers a non-invasive window into the neural dynamics associated with MDD, yet the diagnostic efficacy is contingent upon the appropriate selection of EEG features and brain regions.

Methods

In this study, resting-state EEG signals from both eyes-closed and eyes-open conditions were analyzed. We examined band power across various brain regions, assessed the asymmetry of band power between the hemispheres, and integrated these features with clinical characteristics of MDD into a diagnostic regression model.

Results

Regression analysis found significant predictors of MDD to be beta2 (16-24 Hz) power in the Prefrontal Cortex (

SUBMITTER: Liu X 

PROVIDER: S-EPMC10899403 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature