ON THE INDEPENDENT COMPONENTS OF FUNCTIONAL NEUROIMAGES
K.S. Petersen, L.K. Hansen, T. Kolenda
We discuss the application of ICA procedures to fMRI
(functional Magnetic Resonance Imaging) sequences.
While principal component analysis can identify acti-
vation patterns that are uncorrelated in both space and
time ICA can identify events that are independent in
either time or space. We show that the activation re-
lated components found by either spatial or temporal
independency are consistent, hence robust to choice of
spatial or temporal separation and to choice of ICA ap-
proach. We discuss these issues in the context of three
ICA algorithms applied to an fMRI visual activation
study.