Simple question but I’m hoping I can get an fmriprep expert answer (@ChrisGorgolewski?). I have longitudinal data but some of my participants only completed baseline. If I want to process all of my subjects’ resting state data do not only cross-sectional (baseline) comparisons but also longitudinal comparisons (for those with both time points), should I leave the --longitudinal flag for everyone or only those with both time points?
--longitudinal flag only affects the anatomical processing that will end up generating the anatomical references and support mappings between MNI - T1w - BOLD runs.
Therefore, and similarly to the discussion we had recently (Multiple scan sessions some bad anatomicals), I think the
--longitudinal flag has little usefulness for fMRIPrep per se. You may want to use it if you are planning some longitudinal analysis of brain morphology and thus, you want FreeSurfer to run on that mode.
If that is not the case (longitudinal analysis of the anatomy), then there are two options. If the anatomy between sessions is not expected to change dramatically, then I would suggest running fMRIPrep without the
--longitudinal flag, letting it average the T1w images. If the anatomy changes a lot, then I’d say it is best treating sessions far apart as if they were different subjects.
Thanks @oesteban for the input. I have been inclined to run this as a longitudinal pipeline because I don’t expect the anatomy to change substantially (6 week interval between scans), but wasn’t sure how fmriprep would function if there weren’t scans at every timepoint (due to QC removal).
Let me clarify though:
If the anatomy between sessions is not expected to change dramatically, then I would suggest running fMRIPrep without the
--longitudinal flag, letting it average the T1w images.
Do you mean “with the --longitudinal flag” so that it averages? My understanding was that it averages only if the flag is included.
Actually the opposite since averaging will block any further longitudinal analysis
Got it. Thanks for your help @oesteban.