基于复杂网络的大脑功能连接研究

摘要

应用复杂网络方法研究数学认知的一个基本过程--背诵过程中大脑功能连接的特征.利用功能磁共振成像(fMRI)得到的数据,建立了不同认知任务下的大脑功能网络.对不同网络的分析表明,不同认知任务下,大脑功能连接虽然有一定的区别,但都具有相同的特性:功能连接的度分布呈power-law分布,网络的平均最短距离与对应的随机网络相差不大,而平均集聚系数却大很多,表明此网络具有小世界特性.对网络核心节点定位分析的结果与传统心理学和认知神经科学研究的结果得到很好的吻合.%This study uses the complex network analysis to examine the brain functional network involved in the most basic numerical processing number sequence recitation. We construct the brain functional network under this cognition task from the fMRI data. Results show that, the distribution of functional connections is scale-free. Tke characteristic path length is relatively small and comparable to those calculated for equivalent random networks. The clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small world networks, reflect important functional information about brain states.