Functional connectivity analysis on electroencephalography signals reveals potential biomarkers for treatment response in major depression

Shiau Shian Huang, Yu Hsiang Yu, His Han Chen, Chia Chun Hung, Yao Ting Wang, Chieh Hsin Chang, Syu Jyun Peng, Po Hsiu Kuo

研究成果: 雜誌貢獻文章同行評審

1 引文 斯高帕斯(Scopus)

摘要

Background: The treatment efficacy varies across individual patients with major depressive disorder (MDD). It lacks robust electroencephalography (EEG) markers for an antidepressant-responsive phenotype. Method: This is an observational study enrolling 28 patients with MDD and 33 healthy controls (mean age of 40.7 years, and 71.4% were women). Patients underwent EEG exams at baseline (week0) and week1, while controls’ EEG recordings were acquired only at week0. A resting eye-closing EEG segment was analyzed for functional connectivity (FC). Four parameters were used in FC analysis: (1) node strength (NS), (2) global efficiency (GE), (3) clustering coefficient (CC), and (4) betweenness centrality (BC). Results: We found that controls had higher values in delta wave in the indices of NS, GE, BC, and CC than MDD patients at baseline. After treatment with antidepressants, patients’ FC indices improved significantly, including GE, mean CC, and mean NS in the delta wave. The FC in the alpha and beta bands of the responders were higher than those of the non-responders. Conclusions: The FC of the MDD patients at baseline without treatment was worse than that of controls. After treatment, the FC improved and was close to the values of controls. Responders showed better FC in the high-frequency bands than non-responders, and this feature exists in both pre-treatment and post-treatment EEG.
原文英語
文章編號554
期刊BMC Psychiatry
23
發行號1
DOIs
出版狀態已發佈 - 12月 2023

ASJC Scopus subject areas

  • 精神病學和心理健康

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