Effect of electroconvulsive therapy on brain functional network in major depressive disorder.
10.7507/1001-5515.202201032
- Author:
Shuxiang TIAN
1
;
Guizhi XU
1
;
Xinsheng YANG
1
;
B Fitzgerald PAUL
2
;
Wang ALAN
3
Author Information
1. Key Laboratory of Bioelectromagnetic and Neural Engineering of Hebei Province, Hebei University of Technology, Tianjin 300401, P. R. China.
2. School of Medicine and Psychology, The Australian National University, Canberra, Australian Capital Territory 2601, Australia.
3. Auckland Bioengineering Institute, The University of Auckland, Auckland 1010, New Zealand.
- Publication Type:Journal Article
- Keywords:
Brain functional network;
Electroconvulsive therapy;
Major depressive disorder;
Minimum spanning tree;
Resting-state electroencephalogram
- MeSH:
Humans;
Depressive Disorder, Major/therapy*;
Electroconvulsive Therapy;
Brain;
Algorithms;
Electroencephalography
- From:
Journal of Biomedical Engineering
2023;40(3):426-433
- CountryChina
- Language:Chinese
-
Abstract:
Electroconvulsive therapy (ECT) is an interventional technique capable of highly effective neuromodulation in major depressive disorder (MDD), but its antidepressant mechanism remains unclear. By recording the resting-state electroencephalogram (RS-EEG) of 19 MDD patients before and after ECT, we analyzed the modulation effect of ECT on the resting-state brain functional network of MDD patients from multiple perspectives: estimating spontaneous EEG activity power spectral density (PSD) using Welch algorithm; constructing brain functional network based on imaginary part coherence (iCoh) and calculate functional connectivity; using minimum spanning tree theory to explore the topological characteristics of brain functional network. The results show that PSD, functional connectivity, and topology in multiple frequency bands were significantly changed after ECT in MDD patients. The results of this study reveal that ECT changes the brain activity of MDD patients, which provides an important reference in the clinical treatment and mechanism analysis of MDD.
