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Exploratory fMRI analysis by autocorrelation maximization
Ola Friman1, Magnus Borga, Peter Lundberg
1Department of Biomedical Engineering, Linköping University, University Hospital, Linköping, Sweden.
Neuroimage
|May 29, 2002
Abstract:
A novel and computationally efficient method for exploratory analysis of functional MRI data is presented. The basic idea is to reveal underlying components in the fMRI data that have maximum autocorrelation. The tool for accomplishing this task is Canonical Correlation Analysis. The relation to Principal Component Analysis and Independent Component Analysis is discussed and the performance of the methods is compared using both simulated and real data.