Hello,
I wondered if anybody could help me with some masking issues. I have run a
within-participants experiment with 4 tasks (1,2,3,4: each a separate scan),
with three conditions in each task: 1A,1B,1C, 2A, 2B, 2C…. Initially I ran a
first-level analysis for each participant computing the contrasts that I was
interested in (e.g. 1A+1B-1C etc). I then ran a higher-level mixed analysis
computing the grand average of these contrasts. I am therefore able to see
areas of activation within each task. What I’d like to do now is look at the
areas of unique and common activation between pairs of tasks, in particular
looking at the contrast A+B-C. What’s the best way of doing this?
I have attempted the inclusive masking. I’ve generated binary masks of
activations for A+B-C in task 1 and 2 and then used the fslmaths command –
mul to look at common activation. Is this correct? Using this method I am able
to see the areas of activation using fslview, however I wondered if there is
any way of getting a list of the clusters and some z-coordinates?
Finally, with regard to the exclusive masking I’m not sure of the best way to
go about doing this, both theoretically and practically. So detailed advice on
this would be much appreciated!
Thanks very much.
|