Hi, I’m looking up literature on pros and cons (and research questions that can be answered) of using psychophysiological interaction analysis vs. multivariate autoregressive modeling. Specifically, I am thinking to justify my use of PPI over MAR, but I’m not very familiar with the latter approach. In case this is helpful – I am hoping to look at change of strength in functional connectivity between the orbitofrontal cortex and ventral striatum during anticipating reward vs. anticipating no reward.
I’d appreciate any input on this!
I don’t know much about MAR, but PPI (or generalized PPI/gPPI as the field is moving towards) is well suited for looking at changes in connectivity between two tasks, especially if the tasks are events based (as opposed to a simple block based design which a weighted GLM can handle fine). I found this video to be helpful, and it explains some things that will help you see a better effect size, such as making sure the seed region you choose has different expected activation strengths for the two tasks. gPPI may also be strengthened if you have a baseline / rest condition that you can model along with your two tasks of interest.