What does fMRIPrep do with T1w with --longitudinal?

Hi all,

I was wondering what fMRIPrep is doing exactly with multiple T1’s for multiple sessions per subject. We have a study design with multiple measures over a longer period. We expect that T1’s will change over time substantially. From the explanation of fMRIPrep’s website, I understand that if there are more than 2 sessions (which we do have), it constructs an ‘unbiased’ T1 template (if you use the flag --longitudinal). What does this mean exactly? That the BOLD fmri’s are registered to the session-specific T1’s? (without averaging them over sessions)
What we want to avoid is averaging out differences in the T1s over the sessions.
Do you have any recommendations about how to proceed, whether or not to use the --longitudinal flag?

Best,
Julia

The --longitudinal flag tells fMRIPrep to try to find a template T1w image that is equidistant from all time points, rather than aligning to the first time point. This takes significantly longer, as it’s an iterative process, but I don’t have a sense of how it scales with number of time points.

The idea of the flag was to generally adjust processing to be more appropriate for longitudinal use cases, but that was the only change ever made, so it’s not very useful and is probably more confusing than helpful.

Our current contributors have done little (if any) longitudinal work, which is why support is so minimal. We would be happy to talk about what changes are needed to address the challenges of longitudinal use cases.

An alternative would be to use --bids-filter-file to specify to only use files from a certain session (which in your case may correspond to a longitudinal timepoint). Just note that you would not be able to reliably compare timepoints within subjects in subject space if you do this, since the T1s as you already pointed out will be appreciably different.

Steven

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