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