In case of multi-run experiments, preprocessing is currently performed separately for each time series (including linear trend removal), the time series are separately demeaned, and finally concatenated. Instead of demeaning, it would be better to model across-runs variance with a separate predictor in the GLM. (Not relevant for ParCon experiment, because there is only one pRF run there.)
In case of multi-run experiments, preprocessing is currently performed separately for each time series (including linear trend removal), the time series are separately demeaned, and finally concatenated. Instead of demeaning, it would be better to model across-runs variance with a separate predictor in the GLM. (Not relevant for ParCon experiment, because there is only one pRF run there.)