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That would be typical for ICA of fast TR data. Peace, Matt. On 11/2/15, 9:27 PM, "FSL - FMRIB's Software Library on behalf of Aaron Kucyi" <[log in to unmask] on behalf of [log in to unmask]> wrote: >I'm very much enjoying the ICA-AROMA tool. It has reliably improved my >sensitivity in several activation and connectivity analyses. I am now >trying to apply ICA-AROMA to simultaneous multi-slice (SMS) data that is >much more rich than typical fMRI datasets, with voxel sizes of 2x2x2 mm >and a TR of 1 sec (~10 min runs). With default ICA-AROMA settings, >including automatic dimensionality estimation, I am typically getting >>100 components. It is not uncommon for the algorithm to then recommend >>regressing out ~50-80 components, a considerably higher number than than >>reported by Pruim et al in developing the method. In applying ICA-AROMA >>to such rich SMS data, do you recommend keeping automatic dimensionality >>estimation as such or limiting ICA to a fewer number of components? > >Thank you