Hello,

If all of the stim classes are being modeled using IM, and if motion and other regressors of no interest, then you should get identical betas modeling per run as with across runs. The t-stats would be different, of course. But the basic point is that if all regressors are only non-zero in a single run, then it does not matter if they are fit over one run or all. The betas would not change.

If that is the case, it might be an alternative way to save RAM, if your computer is not able to reasonably run the analysis as is.

Note that if you were NOT using IM, then indeed, we would analyze all runs at once, so that all samples in a category are present. But when using IM, it is like each event is its own category.


But either way, I do not see what you could do with these results. With 3600 regressors over 3750 time points (and that means not even censoring motion points, which will have a big effect on local betas), it suggests that not only is this IM, but the responses to events overlap heavily. So the betas for one class will be strongly affected by the betas for another. These results will probably be quite noisy.


Getting to your last question, the IM method will output one beta per event. But all of this is "per voxel", too. The results are across a volume. So at each voxel there will be one beta per event, it is one beta per event per voxel.

- rick