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中文摘要：
社团结构是复杂网络普遍具有的一个拓扑特性,被认为是一个复杂网络的主要组织原则。基于静息态fMRI（functional magnetic resonance imaging）数据构建功能脑网络,并对其进行模块划分,研究人类脑功能网络的社团结构,并首次从脑网络社区结构的角度分析抑郁症患者和正常人的差异。另外,在研究过程中,通过引入＂小核团＂的概念,提出一种分析脑网络社区结构间差异的新方法。通过研究抑郁症病患者在脑网络社团结构的改变,为疾病诊断方面提供了一些重要的研究和临床应用价值。
英文摘要：
Community structure, being a universal topology characteristic of the complex networks, is deemed as the main organising principles of the complex networks. In this paper, based on fMRI data in resting state, we build the functional brain network and partition it into modules. Then we study the community structure of functional human brain network and analyse for the first time the differences between the patients with depression and the normal people in terms of modular organisation of brain network. Besides, by introducing the concept of ＂ small-nuclei＂ , we propose a new method of analysing the difference between the community structures of brain networks in the process of our study. By researching the changes of depression patients in their community structure of brain network, we provide some important research and clinical values for disease diagnosis.
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Machine learning classifier using abnormal brain network topological metrics in major depressive dis
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