Dear Alfonso/colleagues,

Hope you're well.

I suspect I'm right in thinking that ROI-to-ROI (resting-state functional connectivity) analyses that are conducted using anatomical seed and target ROIs in native space would still require denoising just like the typical seed-to-voxel connectivity analyses in MNI space - i.e., using the au4D.nii files as input, one would still need to regress the potential confounding effects characterized by CSF timeseries and WM timeseries (using the CSF and WM segmentations in NATIVE SPACE) , plus motion regressors and their first order derivatives, etc... 

If this is so, then I suspect it's difficult to do this within the same project as that for seed (native-space ROIs)-to-voxel (whole-brain, MNI space) analyses, and one would need to set up a separate project in CONN altogether ? Otherwise, if both analyses are in the same project, I can't seem to find a way to regress out CSF and WM timeseries in MNI space for the seed (native space ROI)-to-voxel (whole-brain MNI space) separately from the CSF and WM timeseries in native space for the (native spsace) ROI-to-ROI analyses?

many thanks for your help

Georgios