Psychophysiological interaction (PPI) analysis

We next tested the relationship between functional connectivity between neural activity in the brain’s valuation and mentalizing systems and recommendation rating change. We used psychophysiological interaction (PPI) analysis²⁹. PPI tests the hypothesis that brain activity in one region (e.g., mentalizing system) can be explained by the interaction between brain activity in another region (e.g., valuation system) and a cognitive process (e.g., accepting vs. resisting peer influence). Accordingly, we used PPI to compare the strength of functional connectivity between the brain’s mentalizing and valuation systems when participants changed their recommendation ratings to be congruent with peer recommendations (recCHANGE) versus when participants did not change their recommendation ratings (NOrecCHANGE). We used the same valuation region of interest as defined above for the mean activation analyses as the seed region. Using the SPM generalized PPI toolbox³⁶, time courses in the seed region were extracted, averaged, and deconvolved with the canonical HRF using the deconvolution algorithm in SPM8 for each participant. Then, the time course in the seed region was multiplied by the behavior variable of interest (recCHANGE vs. NOrecCHANGE), and this resulting time course was re-convolved with the canonical HRF. The PPI model also included 6 motion parameters as nuisance regressors of no interest. The group-level model was then created by combining first-level contrast images using a random effects model. Finally, average parameter estimates of functional connectivity between the seed (i.e., valuation) region and target mentalizing region of interest were extracted at the group level. We then conducted a t-test for statistical inference, to determine whether the extracted parameter estimate was significantly different than zero at p < 0.05.