Dear Stan, Darren, Geraint,
I agree, Stan's problem here is:
> 2. Generating some group statistic for activation in such a 'localiser'
> defined area, where the 'localised' area may be spatially variable across
> subjects.
I wouldn't claim to be any kind on an expert either, but I would have thought
the technique has two advantages; the first is as Geraint has said, avoiding
some of the problems of variability across subjects. The second is using an
optimal shape for averaging in the area that you are interested in - rather
than relying on the smoothing kernel being the right shape. Personally I find
the approach very attractive - it's good to see bags of formal apriori
specification every now and then...
You could get the data from a region pretty easily; I recently posted a little
function to do this once you have specified to the region with an image; you
could do this by editing an spm t image, a results image, or a contrast image;
see:
http://www.mrc-cbu.cam.ac.uk/Imaging/External/vol_corr.html#DefVVOI
for how to edit the image to get an ROI.
However, doing the stats is a harder problem. You could hack spm_spm.m to do
it for you, but it would be a reasonable amount of work. A very useful bit of
work though; perhaps somebody could write an SPM toolbox?
All regards,
Matthew
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