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作者:

Li Huai-Zhou (Li Huai-Zhou.) | Zhou Hai-Yan (Zhou Hai-Yan.) | Yang Yang (Yang Yang.) | Yang Xiao-Jing (Yang Xiao-Jing.) | Wang Hai-Yuan (Wang Hai-Yuan.) | Zhong Ning (Zhong Ning.)

收录:

Scopus SCIE PKU CSCD

摘要:

This study focused on the changes of network topological efficiency under the condition of maximizing the intrinsic functional connectivity, and explored the relationships between altered topological efficiency and depressive psychopathology. For this purpose, we collected the resting-state functional MRI data from 20 major depressive disorder (MDD) patients and 20 healthy control (HC) individuals with matching of age, gender and education level. Graph theory analysis showed that the patients with MDD exhibited significantly reduced nodal efficiency in the left parahippocampal gyms, right amygdala, left heschl and left temporal pole (middle temporal gyrus) compared with the HC group. The reduced nodal efficiency indicated that the function of transmitting information to other regions was weakened in MDD patients. The local efficiency of the left medial superior frontal gyrus, left orbital superior frontal gyrus, right rectus, left amygdala, right superior parietal gyrus, left thalamus, and left temporal pole (middle temporal gyrus) were also significantly reduced. And the local efficiency of the left medial superior frontal gyrus, left amygdala, left thalamus had negative correlation with PHQ-9. The reduced local efficiency implied that the ability of information transmission at the local level was damaged in the depressed brain network. These results suggested that the prefrontal-thalamo-limbic system involving affective processing was damaged in MDD patients. Our findings might provide a potential biomarker for the clinical diagnosis of depressed patients.

关键词:

graph theory network efficiency resting state functional magnetic resonance imaging major depressive disorder

作者机构:

  • [ 1 ] [Li Huai-Zhou]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 2 ] [Zhou Hai-Yan]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 3 ] [Yang Xiao-Jing]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 4 ] [Wang Hai-Yuan]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 5 ] [Zhong Ning]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 6 ] [Li Huai-Zhou]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing 100124, Peoples R China
  • [ 7 ] [Yang Yang]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing 100124, Peoples R China
  • [ 8 ] [Yang Xiao-Jing]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing 100124, Peoples R China
  • [ 9 ] [Wang Hai-Yuan]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing 100124, Peoples R China
  • [ 10 ] [Zhong Ning]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing 100124, Peoples R China
  • [ 11 ] [Li Huai-Zhou]Beijing Int Collaborat Base Brain Informat & Wisd, Beijing 100124, Peoples R China
  • [ 12 ] [Zhou Hai-Yan]Beijing Int Collaborat Base Brain Informat & Wisd, Beijing 100124, Peoples R China
  • [ 13 ] [Yang Yang]Beijing Int Collaborat Base Brain Informat & Wisd, Beijing 100124, Peoples R China
  • [ 14 ] [Yang Xiao-Jing]Beijing Int Collaborat Base Brain Informat & Wisd, Beijing 100124, Peoples R China
  • [ 15 ] [Wang Hai-Yuan]Beijing Int Collaborat Base Brain Informat & Wisd, Beijing 100124, Peoples R China
  • [ 16 ] [Zhong Ning]Beijing Int Collaborat Base Brain Informat & Wisd, Beijing 100124, Peoples R China
  • [ 17 ] [Li Huai-Zhou]Beijing Key Lab MRI & Brain Informat, Beijing 100124, Peoples R China
  • [ 18 ] [Zhou Hai-Yan]Beijing Key Lab MRI & Brain Informat, Beijing 100124, Peoples R China
  • [ 19 ] [Yang Yang]Beijing Key Lab MRI & Brain Informat, Beijing 100124, Peoples R China
  • [ 20 ] [Yang Xiao-Jing]Beijing Key Lab MRI & Brain Informat, Beijing 100124, Peoples R China
  • [ 21 ] [Wang Hai-Yuan]Beijing Key Lab MRI & Brain Informat, Beijing 100124, Peoples R China
  • [ 22 ] [Zhong Ning]Beijing Key Lab MRI & Brain Informat, Beijing 100124, Peoples R China
  • [ 23 ] [Yang Yang]Maebashi Inst Technol, Dept Life Sci & Informat, Maebashi, Gunma 3710816, Japan
  • [ 24 ] [Zhong Ning]Maebashi Inst Technol, Dept Life Sci & Informat, Maebashi, Gunma 3710816, Japan

通讯作者信息:

  • 钟宁

    [Zhong Ning]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China;;[Zhong Ning]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Beijing 100124, Peoples R China;;[Zhong Ning]Beijing Int Collaborat Base Brain Informat & Wisd, Beijing 100124, Peoples R China;;[Zhong Ning]Beijing Key Lab MRI & Brain Informat, Beijing 100124, Peoples R China;;[Zhong Ning]Maebashi Inst Technol, Dept Life Sci & Informat, Maebashi, Gunma 3710816, Japan

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来源 :

PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS

ISSN: 1000-3282

年份: 2018

期: 1

卷: 45

页码: 43-50

0 . 3 0 0

JCR@2022

ESI学科: BIOLOGY & BIOCHEMISTRY;

ESI高被引阀值:193

JCR分区:4

被引次数:

WoS核心集被引频次: 1

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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