FSL experts,
I realize that this is an old thread, but I'd like to see if I can get clarification on something. I am using FIX to clean rs-fMRI data, but I know that several of my subjects have relatively high motion (>3mm displacement). I am using the -m flag in FIX to regress out the motion (I believe that does the "24 motion related confounds" to which you referred). However, I am wondering whether I should also use fsl_motion_outliers (using DVARS) to identify time points with excessive motion effects and remove outliers using feat (additional confound EVs).
1) Is this a necessary/helpful step to add?
2) Should this be done before or after FIX cleaning?
3) With a TR of 1000ms should I also select the time point before and after too?
If it matters, the next steps would be to create voxel-wise measures of functional connectivity (ReHo, VMHC, etc.)
Thanks in Advance,
-Riley
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