基于介中心性及K-shell的脑网络核心节点评价方法

发布时间：2018-02-14 15:24

本文关键词： 核心节点人脑结构网络点介中心性 K-shell分解法度中心性邻近中心性　出处：《计算机工程与应用》2017年11期 　论文类型：期刊论文

【摘要】：在对基于核磁共振成像技术重构得到的人脑结构网络的研究中,核心节点的识别是对全脑网络特性展开研究的基础,具有重要意义。给出了一种基于K-shell和介中心性的核心节点评价方法,首先使用以节点局部重要性为标准的度中心性、邻近中心性和介中心性三个中心性评价方法分别对人脑结构网络中的节点重要性展开评估和分析;接着利用以节点全局地位为标准的K-shell分解法对人脑结构网络的核心节点展开分析。实验结果显示,由于同时兼顾了脑网络节点的整体特性和局部特性,该方法能够更全面和准确地识别核心脑区节点。
[Abstract]:The recognition of core nodes is the basis of the research on the characteristics of the whole brain network in the research of the human brain structure network reconstructed by the nuclear magnetic resonance imaging technology. A core node evaluation method based on K-shell and mesocentricity is presented. Firstly, the degree centrality based on the local importance of nodes is used. The importance of nodes in the human brain network is evaluated and analyzed by the three evaluation methods of proximity centrality and mesocentricity respectively. Then the K-shell decomposition method based on the global status of the nodes is used to analyze the core nodes of the human brain network. The experimental results show that both the global and local characteristics of the nodes in the brain network are taken into account at the same time. This method can identify the nodes of the core brain more comprehensively and accurately.
【作者单位】：昆明理工大学信息工程与自动化学院;
【基金】：国家自然科学基金(No.61263017) 昆明理工大学人才培养基金(No.KKSY201303120)
【分类号】：O157.5;R338

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