Does anyone know what the correct recon-all usage is for longitudinal data that has both a hi-res T1w and a hi-res T2w image? I know I can use the T2 for pial refinement and the cross-sectional is easy to specify.
Being that the cross-sectional version creates both T2.mgz and T2.norm.mgz (and some T2 related images in transforms), is it sufficient after base creation to simply pass --T2pial or do I need to respecify the path to the original T2 image?
I found a very old conversation (2016) about this on the Freesurfer ListServ but nothing since then that seems to clearly answer the question.
@bpinsard,
With your updates to fMRIPrep’s longitudinal processing, any thoughts or insights?
@Adam_Raikes
I did such preprocessing recently, and relying on the freesurfer BIDS-app allowed me to abstract these. I don’t remember what is does from the top of my head ( I can check the logs later if needed), but maybe checking the logic for longitudinal options here freesurfer/run.py at master · bids-apps/freesurfer · GitHub will give you clues about what options are passed to recon-all for these stages of the longitudinal preprocessing.
@bpinsard,
I looked into the BIDS freesurfer app and found that it actually doesn’t do anything for the longitudinal data. T2s/FLAIRs are used in the first step (cross-sectional) but are not propagated downstream at all to the longitudinal step.