1. I get a significant activation at the group level A > B.
2. I create a mask with this contrast intersecting in my ROI's using fslmaths and -bin to binarise it.
3. I take this mask for each ROI separately and apply it to A > fixation, A < fixation, B > fixation, B < fixation.
4. I then pull all the beta weights featquery calculates.
5. It doesn't matter which values I use (minz, mean, tstat, etc.....) I got bar graphs where the beta's for A & B have overlapping error bars and look very similar.
6. I pulled this at the group level featquery with ROI<Fixation for labeled regions.
http://picasaweb.google.com/lh/photo/gsIBSEwmXjXLNIgR4jS3PA?feat=directlink
I am attempting to find out the magnitude of deactivation or activation. It doesn't make sense that if I get a significant group level contrast of A > B that I would then get non-significant BETAs.
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