Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis

Wei Wang, Li Xiao, Gang Qu, Vince D. Calhoun, Yu-Ping Wang, Xiaoyan Sun

Abstract: Highlights•We introduce a multiview hyperedge-aware hypergraph convolutional network (HGCN) based functional connectivity network (FCN) embedding learning approach to integrate FCNs constructed on multiple brain atlases.•Class-consistency and site-independence modules are formulated to account for the between-subject association of intra- and inter-classes and the between-site heterogeneity in the embedding space, respectively, which can promote the learning of multiatlas-based FCN embeddings discriminative across classes and sites.•The extensive experiments on the multisite, multiatlas fMRI from the ABIDE demonstrate that the proposed class-consistency and site-independence multiview hyperedge-aware hypergraph embedding learning (CcSi-MHAHGEL) outperforms several other methods for autism spectrum disorder (ASD) identification.