Meta-analysis of functional imaging data using replicator dynamics.
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.
Neumann
Jane
J
Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. neumann@cbs.mpg.de
Lohmann
Gabriele
G
Derrfuss
Jan
J
von Cramon
D Yves
DY
D001921:Brain / Q000502:physiology; D003627:Data Interpretation, Statistical; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data*; D015201:Meta-Analysis as Topic