Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder
Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder作者机构:Department of Psychiatry Affiliated Nanjing Brain Hospital Nanjing Medical University Nanjing Jiangsu 210029 China Research Center of Learning Science Southeast University Nanjing Jiangsu 210096 China Research Institute of Suzhou Southeast University Suzhou Jiangsu 215123 China
出 版 物:《Chinese Medical Journal》 (中华医学杂志(英文版))
年 卷 期:2016年第129卷第6期
页 面:679-689页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0805[工学-材料科学与工程(可授工学、理学学位)] 080502[工学-材料学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:The work was supported by the grants from:The National High-tech Research and Development Program of China the National Natural Science Foundation of China the Clinical Medicine Technology Foundation of Jiangsu Province the Natural Science Foundation of Jiangsu Province State Key Clinical Specialty Provincial Medical Key Discipline
主 题:Diffusion Tensor Imaging Graph Theory Analysis Major Depressive Disorder Topological Organization
摘 要:Background: Most previous neuroimaging studies have focused on the structural and functional abnormalities of local brain regions in major depressive disorder (MDD). Moreover, the exactly topological organization of networks underlying MDD remains unclear. This study examined the aberrant global and regional topological patterns of the brain white matter networks in MDD patients. Methods: The diffusion tensor imaging data were obtained from 27 patients with MDD and 40 healthy controls. The brain fractional anisotropy-weighted structural networks were constructed, and the global network and regional nodal metrics of the networks were explored by the complex network theory. Results: Compared with the healthy controls, the brain structural network of MDD patients showed an intact small-world topology, but significantly abnormal global network topological organization and regional nodal characteristic of the network in MDD were found. Our findings also indicated that the brain structural networks in MDD patients become a less strongly integrated network with a reduced central role of some key brain regions. Conclusions: All these resulted in a less optimal topological organization of networks underlying MDD patients, including an impaired capability of local information processing, reduced centrality of some brain regions and limited capacity to integrate information across different regions. Thus, these global network and regional node-level aberrations might contribute to understanding the pathogenesis of MDD from the view of the brain network.