Altered cortical functional network in major depressive disorder: A resting-state electroencephalogram study.

ABSTRACT:

Background

Electroencephalogram (EEG)-based brain network analysis is a useful biological correlate reflecting brain function. Sensor-level network analysis might be contaminated by volume conduction and does not explain regional brain characteristics. Source-level network analysis could be a useful alternative. We analyzed EEG-based source-level network in major depressive disorder (MDD).

Method

Resting-state EEG was recorded in 87 MDD and 58 healthy controls, and cortical source signals were estimated. Network measures were calculated: global indices (strength, clustering coefficient (CC), path length (PL), and efficiency) and nodal indices (eigenvector centrality and nodal CC) in six frequency. Correlation analyses were performed between network indices and symptom scales

SUBMITTER: Shim M 

PROVIDER: S-EPMC6039896 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature