Hi, Maya-

You would create the transformation from subject anatomical (what you input to FreeSurfer, or the *SurfVol*.nii* dset in the output SUMA/ directory after running recon-all and @SUMA_Make_Spec_FS) to your template dataset, and then you can apply that transform to the aparc+aseg or any other dataset that in the subject anatomical space. For nonlinear warping of human T1w anatomical volumes to a template, we would generally recommend using @SSwarper for both skullstripping (SS) and nonlinear warp estimation---there is a specific version of hte MNI 2009c template that is a reference base for @SSwarper: MNI152_2009_template_SSW.nii.gz.

If you are using afni_proc.py, this is even easier, because you can include any of hte recon-all output atlases as "follower ROI" dsets, and those will end up in your final space, either on the same grid with your final anatomical dset or with your final EPI dset. This is demo'ed in this afni_proc.py example:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/programs/afni_proc.py_sphx.html#example-11-resting-state-analysis-now-even-more-modern
... with these options specifically, where the first one puts the aparc*nii file on the final "anat" grid, and the second puts the same dset on the final "epi" grid:

-anat_follower_ROI aaseg anat aparc.a2009s+aseg.nii       \
-anat_follower_ROI aeseg epi aparc.a2009s+aseg.nii        \

That example also shows how to include FS output volumes (ventricles and WM) that might be of interest for, say, ANATICOR, even with erosion of them (so they are muuuuch less likely to overlap GM, which would be bad)

-anat_follower_ROI FSvent epi fs_ap_latvent.nii.gz        \
        -anat_follower_ROI FSWe epi fs_ap_wm.nii.gz               \
        -anat_follower_erode FSvent FSWe                          \

We also have FreeSurfer output from running on the MNI template itself, so the ROIs are all there in MNI space, and would just have to be regridded to your final "applied" dataset, if that is your goal:

https://afni.nimh.nih.gov/pub/dist/tgz/suma_MNI152_2009.tgz

... though I notice this is a wee bit old from @SUMA_Make_Spec_FS output, and some of the extra-convenient files from @SUMA_Make_Spec_FS might not be present (like the specifically ROI-like GM and the FS* tissue maps), though most of the nicer "REN* versions of the aparc* and aseg* files are there.

--pt



Edited 1 time(s). Last edit at 08/09/2022 09:25AM by ptaylor.