物理学报Issue(20)：1-6,6.DOI:10.7498/aps.63.208705
基于Kendall改进的同步算法癫痫脑网络分析
An improved synchronous algorithm based on Kendall for analyzing epileptic brain network
摘要
Abstract
In this study, we propose a kendall rank correlation based synchronous algorithm inverse rank correlation (IRC). The kendall rank correlation is a generalized algorithm of nonlinear dynamics analysis which can effectively measure nonlinear correlations between variables. The study of complex networks has gradually penetrated into various fields of the social sciences. We use our algorithm to construct functional brain networks based on the data from electroencephalogram (EEG). The average node degree of complex brain networks is analyzed to investigate whether epileptic functional brain networks are distinctly different from normal brain networks. Results show that our method can distinguish between epileptic and normal functional brain networks and needs to record a very small number of EEG data. Experimental data show that our method suited to distinguish between epilepsy and normal brain node degree, which may contribute to further deepening the study of the brain neural dynamic behaviors, and provide an effective tool for clinical diagnosis.关键词
electroencephalogram/癫痫/Kendall等级相关/复杂网络Key words
electroencephalogram/epileptic/Kendall rank correlation/complex network引用本文复制引用
董泽芹,侯凤贞,戴加飞,刘新峰,李锦,王俊..基于Kendall改进的同步算法癫痫脑网络分析[J].物理学报,2014,(20):1-6,6.基金项目
国家自然科学基金(批准号:61271082,61201029,61102094)、江苏省自然科学基金(批准号：BK2011759, BK2011565)、南京军区南京总医院基金(批准号:2014019)和中央高校基本科研业务费(批准号：FY2014LX0039)资助的课题.* Project supported by the National Natural Science Foundation of China (Grant Nos.61271082,61201029,61102094), the Natural Science Foundation of Jiangsu Province, China (Grant Nos. BK2011759, BK2011565), the Foundation of Nanjing General Hospital of Nanjing Military Command, China (Grant No.2014019), and the Fundamental Research Fund for the Central Universities, China (Grant No. FY2014LX0039) （批准号:61271082,61201029,61102094）
