Meta‐analysis of functional imaging data using replicator dynamics

Abstract

Despite the rapidly growing number of meta‐analyses in functional neuroimaging, the field lacks formal mathematical tools for the quantitative and qualitative evaluation of meta‐analytic data. We propose to use replicator dynamics in the meta‐analysis of functional imaging data to address an important aspect of neuroimaging research, the search for functional networks of cortical areas that underlie a specific cognitive task. The replicator process requires as input only a list of activation locations, and it results in a network of locations that jointly show significant activation in most studies included in the meta‐analysis. These locations are likely to play a critical role in solving the investigated cognitive task. Our method was applied to a meta‐analysis of the Stroop interference task using data provided by the publicly accessible database BrainMap DBJ. Hum Brain Mapp 25:165–173, 2005.