Hello,
I am trying to incorporate ICA-AROMA for my PPI analysis pipeline, and I just want to confirm my pipeline setup is good.
1) Run preprocessing in Feat with Motion correction, Spatial smoothing, Intensity normalization, and registration.
2) Run ICA AROMA with preprocess.feat as an input
3) Extract mean time series of PPI seed (+WM and CSF mask) from denoised_func_data
4) Run first-level Feat with Highpass filtering on but other pre stat features off, and in the stats set up a model for the PPI, and add WM and CSF regressors as nuisance variables, and do not add motion parameters
Previously I have included the output of fsl_motion_outliers as the additional confound EVs as well, but with ICA-AROMA I don’t need to add them anymore, am I correct?
Thank you!
Ami Tsuchida
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