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I see, then I get, but never done before. Interesting approach, normally you do fc with regard to task-related areas or in resting state. So it seems to be more ambitious approach. I'll think about. Iwo On Aug 27 2011, Peter Michalsky wrote: >> Why don't you want to get ts with variance related somehow to your >> task(s) and regress out effects of no interest? > > functional connectivity analyisis is usually done this way in order to > assure that the connectivity between regions isn't just driven by > task-related activation patterns. What we are interested in is > spontaneous synchronized brain activity. > > >>> Yes I think for your purposes it would be the latter (zeros(1:11) 1). >>> As Iwo pointed out, the "adjust data" option removes the null space of >>> your F-contrast, i.e. the zeros, from your timeseries. See lines >>> 143-153 in spm_regions. > > I've actually tried that but it gives me very odd results. The two > regions I'm looking at are almost perfectly correlated (0.99) if I > specify the F-Contrast like that. Another odd thing is that for both > regions the eigenvariate captures roughly 99% of the variance. If I > specify the contrast as (ones(1:11) 0) the eigenvariates capture a more > reasonable 60% of the variance and the correlation between the > time-courses of both regions is also in a much more plausible range. It > really looks to me as if (ones(1:11) 0) were the right way to go but I > would feel much more confident if I knew why. > -- Iwo