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

Abstract

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—i.e., those focusing on whether connectivity between brain regions is modulated by a given psychological process (Smith et al., 2016). Specifically, we reviewed 284 studies examining brain connectivity 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.

Interpretation of published meta-analytical studies affected by implementation errors in the GingerALE software

“…Consistent with a few other authors of studies that used versions of GingerALE now known to have been affected by these implementation errors (e.g. Smith & Delgado, 2017), we have done this, and we summarise our findings below. We also use our experience to make suggestions for the interpretation of other published meta-analytical studies affected by the GingerALE software errors, and discuss the implications for interpreting statistical analyses more generally that may be affected by similar problems relating to the use of non-open-source, third party software products.…”

Reward Sensitivity Enhances Ventrolateral Prefrontal Cortex Activation during Free Choice

“…Recent meta-analytic work has demonstrated that PPI produces consistent and specific patterns of task-dependent brain connectivity across studies (Smith and Delgado, 2016; Smith et al, 2016a). For each individual, we extracted BOLD time-series from the peak voxel within a mask of the VLPFC cluster.…”

A Brief Anatomical Sketch of Human Ventromedial Prefrontal Cortex

“…roles that vmPFC plays in the many functions linked with the region (see Figure 2). Indeed, recent metaanalytic work illustrates how distinct vmPFC functions modulate its co-activation with other regions: emotion increases vmPFC co-activation with the amygdala whereas social cognition increases vmPFC coactivation with the temporal parietal junction 16,17 . These observations highlight how structural and functional imaging methods can combine to help characterize vmPFC function 18 .…”