A Fixed-Point Iteration Based Constrained Independent Component Analysis and Its Application in FMRI

Ze Wang¹

We presented a new constrained independent component analysis (cICA) in this work. Evaluated with synthetic data, it demonstrated better performance than the original cICA in terms of higher SNR and faster convergence time. Using synthetic fMRI data, the proposed cICA also demonstrated a superior activation detection sensitivity/specificity performance. Applied to sensorimotor fMRI data, it yielded spatially more extended activation patterns in the target functional regions than standard univariate general linear model approach.