Dear HCP Experts,
As I have been struggling with this for a few weeks now, I would appreciate some guidance on how best to handle a longitudinal dataset within the HCP pipelines.
We have multiple structural (T1w/T2w) sessions collected longitudinally, and a larger number of task fMRI sessions acquired at separate time points that do not coincide exactly with the structural sessions. I ran PreFreeSurfer, FreeSurfer, and PostFreeSurfer on each structural session, followed by the longitudinal FreeSurfer and PostFreeSurfer pipelines to generate a long.base template.
However, I cannot directly use the longitudinal version of the fMRIVolume pipeline because it expects session-specific T1wCross2Long transforms, implicitly assuming that each fMRI session is paired with one of the structural sessions used to build the longitudinal template. While I could associate each fMRI session with the structural session that is nearest in time, this felt a bit suboptimal (though I might be wrong).
Instead, I attempted to run the fMRIVolume/Surface pipelines cross-sectionally for each fMRI session, while reusing the longitudinal base template outputs so that all data are ultimately aligned to the same subject-specific template. In doing so, I encountered several issues:
- Missing eye.dat (seems to be the same across sessions, so can copy),
- Missing MNINonLinear/BiasField (this may not be a problem as I am using SEBased bias correction for fMRI),
- Missing lh.white_deformed / rh.white_deformed, which I understand to be the MNI-registered white surfaces required for ribbon masking and surface processing.
My main questions are:
- Does this general strategy (cross-sectional fMRI pipelines anchored to a longitudinal base template) make sense within the HCP framework?
- Is there a recommended way to generate the required *_deformed surfaces (e.g., from the longitudinal PostFreeSurfer outputs), or another workaround and/or any other issues I should be watching out for?
- Or is it preferable to explicitly associate each fMRI session with a specific structural session and use the standard longitudinal fMRIVolume pipeline as intended?
Any advice or best-practice suggestions would be greatly appreciated.
Many thanks in advance,
Deniz