脑电图
相关性
聚类系数
重性抑郁障碍
刺激
心理学
神经科学
阿尔法(金融)
路径长度
BETA(编程语言)
听力学
功能连接
频带
聚类分析
模式识别(心理学)
人工智能
数学
计算机科学
医学
认知心理学
临床心理学
认知
结构效度
心理测量学
电信
程序设计语言
几何学
带宽(计算)
计算机网络
作者
Pintao Qiu,Jinxiao Dai,Ting Wang,Hangcheng Li,Cunbin Ma,Xugang Xi
出处
期刊:Brain Sciences
[MDPI AG]
日期:2022-12-07
卷期号:12 (12): 1680-1680
被引量:4
标识
DOI:10.3390/brainsci12121680
摘要
Major depressive disorder (MDD) is a common mental illness. This study used electroencephalography (EEG) to explore the effects of music therapy on brain networks in MDD patients and to elucidate changes in functional brain connectivity in subjects before and after musical stimulation. EEG signals were collected from eight MDD patients and eight healthy controls. The phase locking value was adopted to calculate the EEG correlation of different channels in different frequency bands. Correlation matrices and network topologies were studied to analyze changes in functional connectivity between brain regions. The results of the experimental analysis found that the connectivity of the delta and beta bands decreased, while the connectivity of the alpha band increased. Regarding the characteristics of the EEG functional network, the average clustering coefficient, characteristic path length and degree of each node in the delta band decreased significantly after musical stimulation, while the characteristic path length in the beta band increased significantly. Characterized by the average clustering coefficient and characteristic path length, the classification of depression and healthy controls reached 93.75% using a support vector machine.
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