计算机应用 ›› 2012, Vol. 32 ›› Issue (07): 2044-2048.DOI: 10.3724/SP.J.1087.2012.02044

• 典型应用 • 上一篇    下一篇

静息态脑功能网络的社团结构研究

王艳群,李海芳,郭浩,陈俊杰   

  1. 太原理工大学 计算机科学与技术学院,太原030024
  • 收稿日期:2011-12-29 修回日期:2012-02-12 发布日期:2012-07-05 出版日期:2012-07-01
  • 通讯作者: 李海芳
  • 作者简介:王艳群(1987-),女,山西临汾人,硕士研究生,主要研究方向:智能信息处理、脑信息学;李海芳(1963-),女,山西昔阳人,教授,博士生导师,主要研究方向:脑认知模型与脑机接口技术、视听觉信息计算;郭浩(1981-),男,山西太原人,讲师,博士研究生,主要研究方向:智能信息处理、脑信息学、脑影像学、语义网;陈俊杰(1956-),男,山西太原人,教授,博士生导师,主要研究方向:数据库与智能信息处理。
  • 基金资助:

    国家自然科学基金资助项目(61070077; 60970059);山西省自然科学基金资助项目(2010011020-2);2011年太原市大学生创新创业人才项目计划资助项目(110148005)

Research into community structure of resting-state brain functional network

WANG Yan-qun, LI Hai-fang, GUO Hao, CHEN Jun-jie   

  1. College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan Shanxi 030024, China
  • Received:2011-12-29 Revised:2012-02-12 Online:2012-07-05 Published:2012-07-01
  • Contact: LI Hai-fang

摘要: 为了探索人脑的工作机制,提出将社团划分算法应用于人脑功能网络。利用功能磁共振(fMRI)采集28名健康被试静息态脑功能数据,构建了基于时间序列的脑功能网络;根据模块度和网络全连接理论对网络中的边数划定阈值范围,利用层次聚类算法和贪心算法对脑网络进行社团划分,实验结果证明两种算法的划分结果基本一致,验证了人脑功能网络具有模块化结构;进而分析了脑网络社团结构在跨阈值范围内的差异化表现,提出了研究脑功能网络的边数有效阈值范围是180至320条边。挖掘脑网络的社团结构有助于研究脑病变机理,以辅助脑疾病的诊断治疗。

关键词: 复杂网络, 社团结构, 跨阈值, 脑功能网络, 模块度

Abstract: The community detecting algorithm was applied to human functional network to explore the mechanism of human brain. The brain functional data of 28 healthy subjects were collected by functional Magnetic Resonance Imaging (fMRI), and the brain functional network of human beings based on time series was constructed. A threshold range of vertices in the network was designated according to modularity and full connected network theory. The community structures were detected by using the hierarchical clustering algorithm and the greedy algorithm respectively, and the experimental results show that similar community structures have been obtained. Then different performances can be explored across the threshold by analyzing the modularity. An effective threshold range of vertices between 180 to 320 in brain network was proposed. Exploring the community structure is helpful to comprehend the mechanism of brain lesions, which provides a tool for diagnosis and treatment of brain diseases.

Key words: complex network, community structure, cross-threshold, brain functional network, modularity

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