Hi,
we examined a patient in a single session with 5 runs and 5 different
cognitive tasks (A,B,C,D,E)each run using a block design. Tasks were
repeated twice a run, task sequence was altered each run.
Run01: E, A, B, C, D, E, D, C, B, A
Run02: B, E, A, D, C, C, D, E, B, A
Run03: ...
Run04: ...
Run05: ...
Now I'd like to look at the mean effect of each task, for example A.
I started a First-Level analysis for each run and got good activations (for
example Run01A.feat, Run02A.feat, Run03A.feat ...)
Doing a Higher-level analysis with this lower-level feat directories to see
the effect of a task over the session (in the example A) I got no
activation at all. The matrix I used consisted of 1 group with 5 inputs,
EV1=1 and Contrast EV1 = 1 (as described in the FSL handbook for single
group average).
The question is: is there a better or any other way to design the higher
level analysis?
Hope you can help me
and many thanks
Thomas Meindl
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