Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (11): 44-49.DOI: 10.3778/j.issn.1002-8331.1512-0307

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Evaluation method of node centrality for brain network based on betweenness centrality and K-shell

WANG Xiaojun, WANG Bin, XIA Yidan, LU Lipeng, LIU Hui, XIONG Xin   

  1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
  • Online:2017-06-01 Published:2017-06-13


王小俊,王  彬,夏一丹,鹿丽鹏,刘  辉,熊  新   

  1. 昆明理工大学 信息工程与自动化学院,昆明 650500

Abstract: Identification of core nodes is of great significance for the research of whole human brain network which is reconstructed based on nuclear magnetic resonance imaging technology. A novel core node evaluation method with K-shell decomposition and betweenness centrality is presented in this paper. Firstly the important nodes in human brain network are evaluated by degree centrality, betweenness centrality and closeness centrality respectively and the relativity between the results is discussed, then the K-shell decomposition method is used to find those core nodes in the shell, and finally these two methods are integrated together to identify the most important core nodes in the human brain network taking into account the overall characteristics and local characteristics of the brain network node. Experimental results show this method provides a more comprehensive and accurate assessment for the core nodes in human brain network.

Key words: core node, human brain structure network, betweenness centrality, [K]-shell decomposition method, degree centrality, closeness centrality

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。

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