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Hi John > I'm trying to implement a first-level GLM with EVs representing > condition (two levels,negative affect and neutral), activity within > a specific region over that time series (say, avg. amygdala > activity), and their interaction. My main interest is in the > interaction effect as a representation of connectivity between the > specific region (amygdala) and the rest of the brain, as a function > of negative affect (what I believe is often referred to as an > analysis of "psychophysiological interactions"). I haven't seen > anything on this listserv or in the FSL documentation on how > specifically to carry this out via FEAT (let me know if I've missed > anything). But I imagine I could carry it out by extracting post- > processed intensity values within the amygdala, dumping this to a > text file and adding it as a column in the design matrix to be run > on that same time series. I could then add an EV for my task to > the same design matrix, and use the GUI option to multiply them > together for the interaction. My questions are: > > 1) Does this approach seem valid? If FLS does a good whitening job and removes all structured cardiac noise this approach sounds fine with me too. However, since amygdala is located very close to the middle cerebral artery, the signal in an amygdala voxel is typically quite contaminated by cardiac pulsation. So if the FSL prewhitening is not perfect you are likely to end up with vascular components in your connectivity map. Best Torben E. Lund Danish Research Centre for MR