Scale-Free Brain Networks Based on the Event-Related Potential during Visual Spatial Attention  

作　　者：LI Ling JIN Zhen-Lan 李凌;金贞兰(Key Laboratory for NeuroInformation of Ministry of Education,School of Life Science and Technology,University of Electronic Science and Technology of China,Chengdu 610054)

机构地区：[1]Key Laboratory for NeuroInformation of Ministry of Education,School of Life Science and Technology,University of Electronic Science and Technology of China,Chengdu 610054

出　　处：《Chinese Physics Letters》2011年第4期238-241,共4页中国物理快报（英文版）

基　　金：Supported by the Young Scientists Fund of the National Natural Science Foundation of China under Grant No 30800242.

摘　　要：The human brain is thought of as one of the most complex dynamical systems in the universe.The network view of the dynamical system has emerged since the discovery of scale-free networks.Brain functional networks,which represent functional associations among brain regions,are extracted by measuring the temporal correlations from electroencephalogram data.We measure the topological properties of the brain functional network,including degree distribution,average degree,clustering coefficient and the shortest path length,to compare the networks of multi-channel event-related potential activity between visual spatial attention and unattention conditions.It is found that the degree distribution of the brain functional networks under both the conditions is a power law distribution,which reflects a scale-free property.Moreover,the scaling exponent of the attention condition is significantly smaller than that of the unattention condition.However,the degree distribution of equivalent random networks does not follow the power law distribution.In addition,the clustering coefficient of these random networks is smaller than those of brain networks,and the shortest path length of these random networks is large and comparable with those of brain networks.Our results,typical of scale-free networks,indicate that the scaling exponent of brain activity could reflect different cognitive processes.

关 键 词：NETWORK NETWORKS shortest 

分 类 号：TN9[电子电信—信息与通信工程]