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Functional connectivity of major depression disorder using ongoing EEG during music perception
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论文类型: 期刊论文
发表时间: 2020-10-01
发表刊物: CLINICAL NEUROPHYSIOLOGY
收录刊物: SCIE
卷号: 131
期号: 10
页面范围: 2413-2422
ISSN号: 1388-2457
关键字: Functional connectivity; Ongoing EEG; Major depression disorder; Music perception; Naturalistic stimuli
摘要: Objective: The functional connectivity (FC) of major depression disorder (MDD) has not been well studied under naturalistic and continuous stimuli conditions. In this study, we investigated the frequency-specific FC of MDD patients exposed to conditions of music perception using ongoing electroencephalogram (EEG).
   Methods: First, we applied the phase lag index (PLI) method to calculate the connectivity matrices and graph theory-based methods to measure the topology of brain networks across different frequency bands. Then, classification methods were adopted to identify the most discriminate frequency band for the diagnosis of MDD.
   Results: During music perception, MDD patients exhibited a decreased connectivity pattern in the delta band but an increased connectivity pattern in the beta band. Healthy people showed a left hemisphere-dominant phenomenon, but MDD patients did not show such a lateralized effect. Support vector machine (SVM) achieved the best classification performance in the beta frequency band with an accuracy of 89.7%, sensitivity of 89.4% and specificity of 89.9%.
   Conclusions: MDD patients exhibited an altered FC in delta and beta bands, and the beta band showed a superiority in the diagnosis of MDD.
   Significance: Our study provided a promising reference for the diagnosis of MDD, and revealed a new perspective for understanding the topology of MDD brain networks during music perception. (C) 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

张驰

副教授   硕士生导师

性别: 男

毕业院校:东北大学

学位: 博士

所在单位:生物医学工程学院

学科:生物医学工程. 信号与信息处理

电子邮箱:chizhang@dlut.edu.cn

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