Group information guided ICA for fMRI data analysis

• Published in: NeuroImage (Orlando, Fla.) Vol. 69; pp. 157 - 197
• Main Authors: Du, Yuhui, Fan, Yong
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.04.2013; Elsevier; Elsevier Limited
• Subjects: Algorithms; Biological and medical sciences; Brain Mapping - methods; Brain research; Data analysis; Enhanced independence; Experiments; fMRI; Fundamental and applied biological sciences. Psychology; Group information; Humans; Image Interpretation, Computer-Assisted - methods; Independent component analysis; Magnetic Resonance Imaging - methods; Methods; Multi-objective optimization; NMR; Nuclear magnetic resonance; Optimization algorithms; Principal components analysis; Studies; Subject specific ICs reconstruction; Vertebrates: nervous system and sense organs; fMRI; Multi-objective optimization; Enhanced independence; Group information; Subject specific ICs reconstruction; Independent component analysis; Human; Nuclear magnetic resonance imaging; Functional imaging

Group independent component analysis (ICA) has been widely applied to studies of multi-subject fMRI data for computing subject specific independent components with correspondence across subjects. However, the independence of subject specific independent components (ICs) derived from group ICA has no...