 |
 |
Dear SPM Experts, Let's say you have a study that you've scanned in three functional runs. When are you EVER justified in modeling this as a single session? For example, in past inquiries on this I've seen folks who have done this because of a priori interest in session effects; others have done this because the frequency of specific types of events is confounded with sessions (e.g., condition A has 1 instance in Session #1, but 8 instances in Session #2; this typically comes up a lot when conditions are defined by subject response). But despite the fact that I know that it HAS been done, I'm not sure if it SHOULD be done, so I'm writing to see if anyone has thought about this and has a relatively straightforward answer. If there are cases where this is an acceptable analytical option, the second question is how to do this appropriately. I've attached a picture of two models of the same single-subject data, one modeled as two sessions and the other as one. In order to model as a single session, I added in a regressor for each of the sessions (last two columns of the single-session model). Is this an acceptable method for accounting for session differences in a single-session model? If not, what is? Any advice would be much appreciated...thanks in advance for any help you can offer! Sincerely, Bob Spunt