Capturing inter-subject variability with group independent component analysis of fMRI data: A simulation study

• Published in: NeuroImage (Orlando, Fla.) Vol. 59; no. 4; pp. 4141 - 4159
• Main Authors: Allen, Elena A., Erhardt, Erik B., Wei, Yonghua, Eichele, Tom, Calhoun, Vince D.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.02.2012; Elsevier Limited
• Subjects: Brain - physiology; Brain research; Datasets; Experiments; fMRI; Group ICA; Humans; Inter-subject variability; Magnetic Resonance Imaging - methods; Model order; Multi-subject; Principal Component Analysis; Quality; Simulations; Standard deviation; Studies; fMRI; Simulations; Group ICA; Multi-subject; Inter-subject variability; Model order

A key challenge in functional neuroimaging is the meaningful combination of results across subjects. Even in a sample of healthy participants, brain morphology and functional organization exhibit considerable variability, such that no two individuals have the same neural activation at the same locat...