Dear PyMVPA experts, I'd like to do spatial rather than temporal normalization for each classification sample to equalize the mean intensity among samples at each time point.
It's relatively straightforward to do so for self-defined, static ROI masks but less trivial for searchlight analyses. Is there a 'preproc' argument for sphere_searchlight() like postproc=mean_sample()? If not, how can I demean patterns within these dynamically running searchlights? Thanks! Konatsu
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