Simple question from an SPM neophyte: We ran six sessions on the same subject;
each session had a total of 60 scans in a boxcar alternating between baseline
and a task (a total of 30 scans in the baseline, 30 scans in the task). The
task in session 1 and 4 can be considered A+B; in 2 and 5, A+C; in sessions 3
and 6, A+D.
The design matrix is set up with one column per session, each session
identical, each session modelled as a boxcar, in the order mentioned above.
1) If I use the contrast [1 1 1 1 1 1] and a cluster shows up, is that finding
voxels which were significant in *all* sessions, or voxels which were
significant in *any* session? Is that the best way to see the effects of A
which are consistent across all tasks?
2) If I want the effects of B without A: should I use [1 0 0 1 0 0] and mask
it with [ 1 1 1 1 1 1 ], or mask it with [0 1 1 0 1 1]? or something else
entirely? I thought about [1 -1/2 -1/2 1 -1/2 -1/2], but I didn't think giving
the non-B sessions negative weights was the right thing to do because I want
areas which just increase with B, regardless of whether they decrease for C
and D. Or is there a better approach to pulling out the effects of B? (and
eventually C and D)
3) Tangential question: If we want to do an analysis only in one hemisphere or
region of interest, can that be done in SPM99?
Many thanks in advance--
Jessica Turner
Long Beach VA Medical Center
--Jess
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