Multi-subject fMRI analysis via combined independent component analysis and shift-invariant canonical polyadic decomposition

TCs with subject-dependent delays conform to the true situation of multi-subject fMRI data. The proposed approach is suitable for decomposing multi-subject fMRI data with large inter-subject temporal and spatial variability.