Am I correct in thinking that, when assessing functional connectivity with
the vanila approach, one should also remove the main effects (or 'driving
effects') of the stimulus to reduce more coincidental (and non-interactive)
aspects of the correlation a la Haynes et al., 2005; Macaluso et al, 2000)?
Resulting regressions are assessed on the residuals of the main stimulus-
effect. I am not completely sure how to achieve this (to remove the main
effect). It may be a simple matter of having a separate regressor for
the stimulus and the regressor-ROI but this seems a bit too easy.
I would quite like to know how though....
All the best
Scott
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