Clusterwise Independent Component Analysis (C-ICA): Using fMRI resting state networks to cluster subjects and find neurofunctional subtypes

• Published in: Journal of neuroscience methods Vol. 382; p. 109718
• Main Authors: Durieux, Jeffrey, Rombouts, Serge A.R.B., de Vos, Frank, Koini, Marisa, Wilderjans, Tom F.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2022
• Subjects: Aged; Alzheimer Disease - diagnostic imaging; Brain - diagnostic imaging; Brain Mapping - methods; Cluster Analysis; Clustering; Computer Simulation; Heterogeneity; Humans; ICA; Individual differences; Magnetic Resonance Imaging - methods; Neurofunctional subtypes; Patient clusters; Resting-state fMRI; Heterogeneity; Neurofunctional subtypes; ICA; Individual differences; Resting-state fMRI; Patient clusters; Clustering

FMRI resting state networks (RSNs) are used to characterize brain disorders. They also show extensive heterogeneity across patients. Identifying systematic differences between RSNs in patients, i.e. discovering neurofunctional subtypes, may further increase our understanding of disease heterogeneity...