Summary of what happened:
I am working with a bids fmri dataset (preprocessed in fmriprep). The data was acquired through a sparse scanning paradigm (basically through Perrachione and Ghosh you have the participant do a task when not acquiring a scan, then scan right after to reduce effects of scanner-related sounds on the data (valuable for speech and auditory tasks). See fig 2 of that paper to see what this looks like in concept
Basically I am curious if there is a way to set up my design matrix with after resampling my data based on when the scans occur (e.g. going from panel C to D) natively in nilearn, or whether I will need to do this more manually.
I am going to try to leverage this nipype class as a part of my code to help here fwiw