Meta-analysis of functional imaging data using replicator dynamics

Hum Brain Mapp. 2005 May;25(1):165-73. doi: 10.1002/hbm.20133.


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.

MeSH terms

  • Brain / physiology
  • Data Interpretation, Statistical
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Magnetic Resonance Imaging / statistics & numerical data*
  • Meta-Analysis as Topic*