Hi all, I have a dataset with TR=2 where I want to delete the first 10 TRs (first 20 seconds) before running fit_event_hrf_model.
Deleting the first TRs is easy: ds = ds[10:] However I am unsure what to do with time coordinates. I understand that if I adjust the onsets in the event list then I will also need to adjust the time_attr in the dataset, like: TR=2 for e in event_list: e['onset'] = e['onset']-10*TR ds = ds.sa.time_coords - 10 * TR result= fit_event_hrf_model(ds, event_list, time_attr='time_coords', condition_attr=('targets', 'chunks')) My intuition is that it shouldn't matter whether you adjust event onset and ds time coordinates as long as you adjust both or neither - so that they stay correctly aligned. But when I run this and test, then I do get slightly different estimates depending solely on whether I adjust the both time coordinates and event onsets, or neither (keeping constant the removal of 10 trs). Mainly I am wanting to know whether or not I should adjust the time coordinates, but I would be interested to hear from anyone who knows why estimates actually differ. Ben
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