I’m trying to run some analyses with Cosmo using some preprocessed fmri from FMRIPREP but am running into issues with the masks that were output per run. In order to combine datasets Cosmo requires that the input matrices for each be of equal dimension. But after filtering the preprocessed functional run files with their associated masks each run has a data matrix with a different number of voxels chosen by the mask. These can differ in size by several hundred voxels or so in cases, and this is between runs within the same participant.
Cosmo has a function for dealing with this sort of discrepancy in size (which can be seen here) but using that I seem to be losing around a third of the voxels in the process of aligning the two datasets, which seems excessive especially for data recorded from the same participant on back-to-back runs.
Is there something in my fmriprep pipeline that might’ve caused the masks (or the BOLD images) to come out so seemingly lacking in alignment between runs? I’ve included the shell code I used to run FMRIPREP in case that might be informative:
docker run -m=“11.5g” --memory-swap=“40g” -ti --rm -v /Users/Blake/Documents/angular/Nifti:/data:ro -v /Users/Blake/Documents/angular:/out -v /Users/Blake/licenses/freesurfer/license.txt:/opt/freesurfer/license.txt -v /Users/Blake/plugin.yml:/plugin poldrack/fmriprep:latest fmriprep:latest --use-plugin /plugin /data /out/out participant --ignore fieldmaps
Thanks in advance for any help that can be offered.