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Hi FSL experts, I am attempting to run MELODIC on functional data from a working memory task (in parallel to traditional processing using FEAT). There are two scans for each session, in which different levels of the n-back task (n=3, n=1, n=0) are presented in a mirrored block-design, as follows: Run A: 3 1 0 0 1 3 Run B: 0 1 3 3 1 0 I would like to do a session-level analysis to identify components associated with task, fixation, etc. Is this appropriate given that the temporal order of the two scans is different? If so, which of the two options (tensor vs. temporal concatenation) should I use and how large should I set the high-pass filter cutoff? Thanks. Cheers, Pete Fried Department of Anatomy & Neurobiology Boston University School of Medicine