Hi All, I have trouble doing event-related searchlight analysis and would appreciate it if anyone could help! As you can see from this page (http://www.pymvpa.org/tutorial_eventrelated_searchlight.html) searchlight is applied on a dataset named evds which is generated in this way:
evds = eventrelated_dataset(ds, events=events)
“ds” is our dataset which consists of brain volumes (or samples) and “events” contains information about onsets, durations, and condition labels of our events. What the function “eventrelated_dataset” does is it segments the original time series dataset (ds) into event-related samples. As I understand, it means that it extracts (multiple) consecutive samples for each event; so eventually there will still be brain volumes (samples) in evds and not exact event information. This might be reasonable when events are synchronized with TR, but not for cases that include jitter. Is that right? If yes, is there any other function that I can use? For example, can I use the output of my “fit_event_hrf_model” function (it is perfectly fine in this function to have events that are not synchronized with the TR) for this purpose? Thank you!