Hi Bertrand,
thanks for your answer. Your suggestion sounds reasonable but I wonder if it would be possible to just concatenate the design matrices? Meaning to model each run/session separately and then create a large design matrix where all bold regressors “span” over all runs and regressors that are run-specific (e.g. drift-correction, confounds, motion outliers etc.) are set to 0 for all runs except those they were modeled for?
I’m a little bit unsure what this would mean in statistical terms. It feels like this would add a little bit of power because the model has more data to be fitted on, but there is probably a caveat to this approach I’m not seeing here.
Thanks,
Marc