Hi CONN experts,
Suppose I have a set of conditions, say rest, stim1 and stim2
I've been wondering if it is correct to do gPPI using the task conditions after having used the Effect of stim1 and Effect of stim2 as confounds in the denoising step.
The way I see it, the Effect of these confounds are regressed out from the BOLD signal in an i-th region/voxel, by estimating:
yi = yi'+beta1i*conv(hrf,stim1)-beta2i*conv(hrf,stim2)
where yi' is the denoised signal

On the other hand, gPPI estimates the betas of the following model, given the target and seed regions/voxels i and k, respectively
yi' = beta1ik*conv(hrf,stim1)*yk'+beta2*conv(hrf,stim2)*yk'+   (PPI interactions)
        beta1i*conv(hrf,stim1)+beta2i*conv(hrf,stim2)+   (main effect of conditions)
        betak*yk'  (main effect of seed)
which may seem to be controlling for the effect of the conditions for the second time.

Is this correct? Is so, is it acceptable? Is it irrelevant, i.e. after denoising, the main effect of the conditions in the gPPI model will not be significant (estimates beta1i=beta2i=0)? Or should I denoise without using the Effects of the conditions if gPPI is intended?

Thank you!