Hi Yarick et al. In a typical FSL preprocessing pipeline, the timeseries images are globally scaled such that the median of all four dimensions (within the brain mask) is the same number across scans (usually 10000). To minimize duplicated data, it would be nice to take the output of my preprocessing and use it for both univariate and multivariate analyses, but I'm wondering if this scaling step will introduce any bias. Is this a valid concern? And does the answer change if I'm using a leave-one-run-out cross validation approach?
Best, Michael
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