Detecting and Testing Altered Brain Connectivity Networks with K-partite Network Topology.

ABSTRACT: Emerging brain connectivity network studies suggest that interactions between various distributed neuronal populations may be characterized by an organized complex topological structure. Many neuropsychiatric disorders are associated with altered topological patterns of brain connectivity. Therefore, a key inquiry of connectivity analysis is to detect group-level differentially expressed connectome patterns from the massive neuroimaging data. Recently, statistical methods have been developed to detect differentially expressed connectivity features at a subnetwork level, extending more commonly applied edge level analysis. However, the graph topological structures in these methods are limited to community/cliques which may not effectively uncover the underlying complex and dis

SUBMITTER: Chen S 

PROVIDER: S-EPMC7442212 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature