CCPD under sparsity and low-rank constraints: multi-frequency dynamic functional network connectivity analysis in schizophrenia
Weijun Liang
This study aims to jointly extract group-shared connectivity patterns and group-specific temporal and frequency information from multi-frequency dynamic functional network connectivity (dFNC) tensors of healthy controls (HCs) and schizophrenia patients (SZs) using a coupled canonical polyadic decomposition (CCPD) approach. Based on 145 subjects (71 SZs and 74 HCs) from the COBRE dataset, multi-frequency dFNC tensors were constructed via group independent component analysis and a filter-banked co