抑郁症的脑网络失调:来自图论分析的证据  

The Disconnected Brain of Major Depression Disorder: Evidence from Graph Theory Analysis

作　　者：刘威[1,2] 李海江[1,2] 邱江[1,2] 

机构地区：[1]认知与人格教育部重点实验室(西南大学) [2]西南大学心理学部,重庆400715

出　　处：《心理科学进展》2015年第1期85-92,共8页Advances in Psychological Science

基　　金：国家自然科学基金项目(NSFC31070900;NSFC31170983;NSFC31271087)

摘　　要：以脑成像数据为支撑,基于图论的复杂脑网络分析实现了在大尺度上对于大脑的整体定量分析,克服了传统抑郁症病理改变研究仅关注少数几个脑区的缺点。本文主要总结了:(1)基于图论的脑网络分析的概念;(2)基于图论的抑郁症研究现状;(3)以往传统研究的不足,抑郁症脑网络研究的当前总结和未来展望。总体来说:抑郁症病人脑网络的小世界属性依旧存在,但在节点指标上存在明显的异常,且随疾病发展呈线性变化,整个网络趋向于随机化。区域性的异常主要存在于默认网络和前额叶?边缘系统环路。未来研究中,任务状态下的脑网络构建和"最小生长树"技术的应用可能会为抑郁症病人的脑网络异常提供更多的信息。Complex network analysis, based on graph theory and neuroimaging data, allows investigators to describe the large-scale brain networks using several topological characteristics. This approach overcomes the shortcoming of traditional neuroimaging research that can only focus on a few brain regions either individually or in combination. This review concluded includes the following issues： 1） the concepts of complex brain network analysis; 2） the researches of depression depressive disorder based on graph theory ; 3） weaknesses, conclusions and future directions of brain network research. Convergent evidence shows that Major Depressive Disorder （MDD） patients show small-world architecture in brain networks, but some of their nodal characteristics evolved with the development of disease, and the whole brain network tended to be a random network. Kegional abnormality mainly existed within the default mode network （DMN） and prefrontal-limbic circuits. In future studies, construction of whole brain networks in cognitive tasks and Minimum Spanning Tree （MST） may provide more information about the disrupted brain connectome of MDD.

关 键 词：抑郁症 复杂脑网络 图论 脑连接组 

分 类 号：B845[哲学宗教—心理学]