Meta-analysis of psychophysiological interactions: Revisiting cluster-level thresholding and sample sizes.

Within the neuroimaging community, coordinate based meta-analyses (CBMAs) are essential for aggregating findings across studies and testing whether those studies report similar anatomical locations. This approach has been predominantly applied to studies that focus on whether activation of a brain region is associated with a given psychological process. In a recent paper, we used CBMA to examine a distinct set of studies-that is, those focusing on whether connectivity between brain regions is modulated by a given psychological process (Smith et al. [2016]: Hum Brain Mapp 37:2904-2917). Specifically, we reviewed 284 studies examining brain connectivity with psychophysiological interactions (PPI). Our meta-analytic results indicated that PPI yields connectivity patterns that are consistent across studies and that can be specific for a given psychological process and seed region. After publication of our findings, we learned that the analysis software we used to conduct our CBMAs (GingerALE v2.3.3) contained an implementation error that led to results that were more liberal than intended. Here, we comment on the impact of this implementation error on the results of our paper, new recommendations for sample sizes in CBMAs, and the importance of communication between software users and developers. We show that our key claims are supported in a reanalysis and that our results are robust to new guidelines on sample sizes. Hum Brain Mapp 38:588-591, 2017.