Dear FSL experts,
It is my understanding that fsl_regfilt can also be used to regress out nuisance factors such as CSF and WM.
In this regard, when running seed connectivity analysis, I was wondering which method is preferable, or whether they have any difference at all.
1) Run fsl_glm on original data with extracted time-series (seed) and nuisance regressors (motion parameters, CSF, WM).
2) Using fsl_regfilt, remove nuisance regressors from original data, and then simply run glm on cleaned data with only the seed time-series in the design matrix.
My general approach when extracting time-series from the seed region is to regress out nuisance factors from the seed time-series first (using fsl_regfilt) and then use fslmaths to extract the time-series that is ideally unaffected by non-neural factors. With this raw signal, I was not sure which of the two methods to pursue.
Thanks,
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