This seems like a basic problem, but I haven’t seen any answers for this yet. I’ve got a dataset with 6 runs and am using nipype to preprocess the data. Previously, with datasets with fewer runs, I did the coregistration and normalization for each functional run separately. With 6 runs, however, I was wondering if there is a more efficient way to set up a preprocessing pipeline for several runs?
Perhaps with a separate workflow for coregistration and normalization?
I have not found any example pipelines using several runs either…
Thank you very much,