关键词: 拓扑数据分析, 持续同调, 复杂脑网络, 持续拓扑特征

Abstract: Aiming at the problem that there is no accepted standard determine appropriate threshold in brain network analysis，based on the topology data analysis of Persistent Homology(PH) theory，a multi-scale brain network modeling analysis method is proposed，in which Rips filtering algorithm is used to capture the dynamic persistence topological features by increasing threshold in the range of the whole scale distances，and the persistence topological features were visualized by barcodes and persistence diagrams，finally the stability of persistence topological features were analyzed through calculating the Bottleneck distances and Wasserstein distances between persistence diagrams.Experimental results show that this method can more accurately extract the topological features of brain networks and improve the accuracy of diagnosis and classification.

Key words: TDA(Topological Data Analysis), Persistent homology, Complex brain network, Persistence topological feature