Bjerre, Troels

Hansen, Lars Kai

Henriksen, Jonas

Madsen, Kristoffer Hougaard

Nielsen, Carsten Haagen

Rasmussen, Peter Mondrup

We present a toolbox for exploratory analysis of functional magnetic resonance imaging (fMRI) data using independent component analysis (ICA) within the widely used SPM analysis pipeline. The toolbox enables dimensional reduction using principal component analysis, ICA using several different ICA algorithms, selection of the number of components using the Bayesian information criterion (BIC), visualization of ICA components, and extraction of components for subsequent analysis using the standard general linear model. We demonstrate how the toolbox is capable of identifying activity and nuisance effects in fMRI data from a visual experiment

Unified ICA-SPM analysis of fMRI experiments:Implementation of an ICA graphical user interface for the SPM pipeline

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