Use of Independent Component Analysis to Define Regions of Interest for fMRI Studies

Jolinda Carol Smith¹, Scott H. Frey^1,2

Regions of interest (ROIs) are frequently used in fMRI. When defining functional ROIs, investigators face a number of arbitrary choices concerning the statistical threshold to employ and the method for delineating ROI boundaries. We propose a method for defining ROIs using independent component analysis (ICA). This method avoids many of the shortcomings of general linear model based ROI definition, and is robust and easy to implement. As a demonstration, we apply this method to define ROIs in the cortex and cerebellum that respond selectively to aurally paced movements of the lips, hands, and feet.