Hi pt,

The .annot parcellation was actually sent to us by another group, and is based on the fs_average template, which is why I executed a series of commands to transpose the parcellation onto each individual's surface and then convert to nifti. Am I understanding correctly that your suggestion re @SUMA_Make_Spec_FS should replace mri_aparc2aseg in our pipeline? (to clarify, I never previously used @SUMA_Make_Spec_FS, so I'm trying to figure out what it adds and where it would fit in)

3dAllineate was used to correct for eddy distortions. However, it sounds like it shouldn't be used for that and I should remove it entirely.

Also, new, relevant information: I got in touch with the people involved in data acquisition. They confirmed that there were obliquity issues for all subjects who were scanned on the Siemens scanners, which are the same set of subjects I had trouble with (where 3dInfo showed mismatched grid). They mentioned: "we have now preprocessed derivatives for both T1w and diffusion that we are happier with" and fixed it "by re-orienting the image and rotating the bvecs using the align.py script from pnlNipype (https://github.com/pnlbwh/pnlNipype/blob/master/scripts/align.py). This was done at the beginning before any further pre-processing"
-- This is not something I am familiar with. Does it sound like this should solve my issue of within-subject data being on different grids?

Thank you and have a nice weekend.