I am analyzing an fMRI dataset, in which participants have 3 runs of scene viewing and 1 run of object viewing. I want to compare between these two types of runs to select scene-sensitive voxels for next step. However, I have not found documentation about how to perform this kind of analysis with FSL in Nipype. The closest one I found is this. This is different from what I need because I cannot perform first-level comparison between scene and object within runs directly.
I am wondering how can I use Nipype with fsl to run this within subject but across runs analysis? I have finished first level modeling for each run with film_gls (and thus I have t-stat, copes, and other output from film_gls for each run), but am unsure how to arrange these outputs from separate runs into inputs for FLAMEO, as well as how to create the design matrix in Nipype. Is there any documentation related to this issue, and I can use as a reference?
Also, if Nipype with FSL is not the best way to do it, I am open to other suggestions!
Thanks a lot in advance!