 |
 |
Hi, We're having some trouble with the interpretation of a PPI result. We found a positive significant interaction (this was in an event-related design), but wanted to know what kind of relationships this resulted from. For instance, was there a positive correlation in one condition and a negative correlation in the other; or a positive and a zero correlation; or a more versus less positive correlation, etc. What one of our colleagues tried was to run the PPI with each condition separately, and then use the T- and contrast values to determine whether the relationship in that condition was positive, negative or around zero. A negative regression weight was found, which we at first thought might imply some sort of negative interaction. However, we're not quite sure whether this is a valid approach. We also used simulated data to try to understand how the analysis works, and this resulted in the expected PPIs, but the per-condition didn't seem to bear any absolute relationship to the simulated regression coefficients. For instance, in one condition we modelled impulses in a certain "dependent" voxel as 10 times an impulse in the independent voxel (which we used for the VOI). In the other condition, the scaling factor was 1. But this resulted in a positive and negative "partial PPI" rather than more and less positive values. So our primary question is, should we even be expecting these per-condition PPIs to provide a meaningful value, in the sense that negative values for one condition imply a true negative physiological interaction in that condition? Thanks very much in advance.