Hey all -- 

Has anyone used data preprocessed by FSL's FEAT? I am working with a large dataset (>200 functionals) and have already done my preprocessing and QA in FEAT. They key issue I'm hitting is that of registration: I would like my files to be in subject space, and have a corresponding func2anat registration matrix. However, if I resample my functional using this matrix, the size of my files goes up to ~4GB each. Is there a way for CONN to apply a co-registration step, or is this file size something I will just have to deal with?

Thanks!
Stephen

Hey all -- If anyone else runs into this, it looks like the best thing to do is to apply the FEAT-generated registrations to the "filtered_func_data" files. I misjudged the amount of extra hard disk space it took up in MNI_2mm space... it was 400 MB per file, no 4GB. Still a lot, but doable.