Aberrant network topological structure of sensorimotor superficial white-matter system in major depressive disorder

被引:0
|
作者
Wang, Peng [1 ,2 ,3 ]
Bai, Yanling [4 ]
Xiao, Yang [5 ]
Zheng, Yuhong [1 ,2 ,3 ]
Sun, Li [1 ,2 ,3 ]
Wang, Jinhui [6 ]
Xue, Shaowei [1 ,2 ,3 ]
机构
[1] Hangzhou Normal Univ, Ctr Cognit & Brain Disorders, Dept Neurol, Affiliated Hosp, Hangzhou 311121, Peoples R China
[2] Hangzhou Normal Univ, Inst Psychol Sci, Hangzhou 311121, Peoples R China
[3] Zhejiang Key Lab Res Assessment Cognit Impairments, Hangzhou 311121, Peoples R China
[4] Hangzhou Normal Univ, Jing Hengyi Sch Educ, Hangzhou 311121, Peoples R China
[5] Peking Univ, Inst Mental Hlth, Hosp 6, Beijing 100191, Peoples R China
[6] South China Normal Univ, Inst Brain Res & Rehabil, Guangzhou 510631, Peoples R China
来源
关键词
Major depressive disorder (MDD); Magnetic resonance imaging (MRI); White matter; Brain network; BRAIN NETWORKS; CONNECTIVITY; ORGANIZATION; ACCURACY; MOTION;
D O I
10.1631/jzus.B2300880
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
White-matter tracts play a pivotal role in transmitting sensory and motor information, facilitating interhemispheric communication and integrating different brain regions. Meanwhile, sensorimotor disturbance is a common symptom in patients with major depressive disorder (MDD). However, the role of aberrant sensorimotor white-matter system in MDD remains largely unknown. Herein, we investigated the topological structure alterations of white-matter morphological brain networks in 233 MDD patients versus 257 matched healthy controls (HCs) from the DIRECT consortium. White-matter networks were derived from magnetic resonance imaging (MRI) data by combining voxel-based morphometry (VBM) and three-dimensional discrete wavelet transform (3D-DWT) approaches. Support vector machine (SVM) analysis was performed to discriminate MDD patients from HCs. The results indicated that the network topological changes in node degree, node efficiency, and node betweenness were mainly located in the sensorimotor superficial white-matter system in MDD. Using network nodal topological properties as classification features, the SVM model could effectively distinguish MDD patients from HCs. These findings provide new evidence to highlight the importance of the sensorimotor system in brain mechanisms underlying MDD from a new perspective of white-matter morphological network.
引用
收藏
页码:39 / 51
页数:13
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