基于脑电的复杂网络性别差异性研究

人脑的生理结构和功能因性别不同存在很大差异,为了考察不同性别在脑网络研究中的差异性表现,本文利用复杂网络理论对20例健康被试者静息状态下的脑电数据在连续阈值区间内进行了脑网络构建和分析。结果发现:在所选阈值区间内女性组聚类系数、特征路径长度、网络平均度、效率都普遍高于男性组,与之前研究者所得结论具有一致性,而且不同阈值间脑网络拓扑属性差异极显著(P0.01)。结果提示:性别差异在脑网络分析中是一个不容忽视的因素。在利用复杂网络手段诊断各类疾病时,将性别因素考虑在内,很可能可以提高基于脑网络分析手段对各类疾病诊断的准确率。

The Study of Gender Difference in Using Complex Network Theory Based on EEG Data

There is a big difference in physiological structure and function of the human brain of different gender. In order to understand the differences in performance of the brain network of different gender, the EEG data of 20 healthy subjects in the resting state were studied by using the complex network theory and were analyzed in successive threshold range in this study. Results showed that clustering coefficient, the average path length, the average degree and efficiency of the brain functional network of female group were generally higher than the male group, which was consistent with the results concluded by previous researchers. We also found that topology attributes of brain network in different thresholds showed significant difference （P 〈0.01）. The results suggested that gender difference was a factor which could not be ignored and when we used complex network theory to diagnose diseases, taking gender difference into account might help improve the accuracy.