Hi Rick,
Thanks very much!
A recent paper (Di et al., 2017, human brain mapping 38:1723–1740) states that "imperfect decovolution may introduce spurious psychophysical interactions and how to avoid it".
I noticed that you are one of the authors of this paper.

I feel that the centering of psychological variable was mean to minimize the correlation between the main effect term and the PPI term in the GLM model.
The best method I think , also suggested in the paper, is "... In addition, AFNI suggests removing psychological effects from the physiological variable before calculating PPI, which is an effective step to minimize collinearity between the PPI term and main effects. ..."


(1) I think the procedure (removing psychological effects from physiological variable) should be done in every PPI analysis. Centering the psychological variable is seems like to hide the problem by changing the meaning of the task regressor. I suggest using a full model to explain all task related variance and noise variance such as head emotion in the seed time course and then using the residual timecourse as the physiological variable.

(2) Another thought is it might be unnecessary to use deconvolution-convolution approach because the difference between the two are trivial, at least in the case of a event related design with long trial duration.

What's your opinion?

Best,
Lz