Disrupted intrinsic functional brain topology in patients with major depressive disorder

重性抑郁障碍 默认模式网络 神经科学 稳健性(进化) 拓扑(电路) 静息状态功能磁共振成像 心理学 功能连接 医学 生物 数学 认知 生物化学 基因 组合数学
作者
Hong Yang,Xiao Chen,Zuo-Bing Chen,Le Li,Xue-Ying Li,F. Xavier Castellanos,Tong-Jian Bai,Qi-Jing Bo,Jun Cao,Zhi-Kai Chang,Guan-Mao Chen,Ning-Xuan Chen,Wei Chen,Cheng Chang,Yu-Qi Cheng,Xi-Long Cui,Jia Duan,Yiru Fang,Qiyong Gong,Wen-Bin Guo
出处
期刊:Molecular Psychiatry [Springer Nature]
卷期号:26 (12): 7363-7371 被引量:236
标识
DOI:10.1038/s41380-021-01247-2
摘要

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
畅快盼望发布了新的文献求助10
1秒前
博雯发布了新的文献求助30
2秒前
ann完成签到,获得积分10
3秒前
坚强书文发布了新的文献求助10
3秒前
123456完成签到 ,获得积分10
4秒前
4秒前
Hey完成签到 ,获得积分10
4秒前
科目三应助cata采纳,获得10
4秒前
bkagyin应助雷豪采纳,获得10
5秒前
6秒前
6秒前
打打应助gouqi采纳,获得10
6秒前
6秒前
7秒前
8秒前
9秒前
yzy发布了新的文献求助10
9秒前
10秒前
梁队长发布了新的文献求助10
11秒前
11秒前
13秒前
所所应助傻子与白痴采纳,获得10
13秒前
15秒前
15秒前
无限达完成签到,获得积分10
15秒前
17秒前
科研通AI6.4应助畅快盼望采纳,获得10
18秒前
坚强书文完成签到,获得积分10
19秒前
ke完成签到,获得积分10
19秒前
20秒前
21秒前
22秒前
23秒前
打打应助sai采纳,获得10
23秒前
木木发布了新的文献求助10
24秒前
iris完成签到,获得积分10
25秒前
26秒前
南极以南发布了新的文献求助10
26秒前
务实寻真发布了新的文献求助10
27秒前
woshizy完成签到,获得积分10
28秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
Resiliency Scale for Adolescents--Chinese Version 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 550
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7328628
求助须知:如何正确求助?哪些是违规求助? 8943260
关于积分的说明 18969254
捐赠科研通 6984352
什么是DOI,文献DOI怎么找? 3216357
关于科研通互助平台的介绍 2383041
邀请新用户注册赠送积分活动 2195805