Dear FSL experts,

I’m trying to use ICA-AROMA on some fMRI data that were preprocessed with SPM12 and wanted to check whether the steps I’m using are correct, as I’m a relative newbie with FSL.

Each subject has 4 functional runs, two of which involve overt speech responses, which is the reason for trying ICA-AROMA as it seems to do an excellent job of reducing motion artifacts relative to some other methods.

1. In SPM for each individual subject I’ve (a) realigned the NIfTI images, (b) normalized them to MNI space, (c) smoothed the images, and (d) converted the 3D images across all four functional runs into a single 4D file (one for each subject).

2. Next, I ran ICA-AROMA on each subject’s 4D file individually with the required motion parameter files, mask image, etc.

From the Pruim et al. papers on ICA-AROMA and the manual it’s still a little unclear whether the processing should be done for each subject individually (across all runs). The task-based fMRI example they use has multiple runs per subject but it wasn’t clear to me how the data from different runs were entered into ICA-AROMA.

Some other ICA-based programs such as GIFT involve entering all the group data to compute components, so a possible alternative would be to enter all of the subjects at once (?). Or alternately, ICA-AROMA could be run on the data from each individual run, but it seems preferable to concatenate data across all of a subject's runs for ICA.

Some tips on the best workflow would be much appreciated!

Thanks,

—Stephan











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