Group Independent Component Analysis of Multi-subject fMRI Data: Connections and Distinctions between Two Methods

• Published in: 2008 International Conference on BioMedical Engineering and Informatics Vol. 2; pp. 748 - 752
• Main Author: Ying Guo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2008
• Subjects: Biomedical engineering; Biomedical informatics; Brain modeling; fMRI; GIFT; Group comparison; Independent component analysis; Matrix decomposition; Multisubject analysis; Neuroimaging; Principal component analysis; Public healthcare; Signal processing; Tensile stress; tensor PICA

Independent component analysis (ICA) has been successfully applied for single-subject functional Magnetic Resonance Imaging (fMRI) analysis. The extension of ICA for group inferences remains an active research topic. We consider two popular group ICA methods for multi-subject fMRI data: GIFT [1] and...