Before revision: The size of publicly available data in cognitive neuro-imaging has increased a lot in recent years, thanks to strong research and community efforts . Exploiting this wealth of data demands new methods to turn the heterogeneous cognitive information held in different task-fMRI studies into common-universal-cognitive models.
After revision: We show in this paper how to extract shared brain representations that predict mental processes across many cognitive neuroimaging studies. Focused cognitive-neuroimaging experiments study precise mental processes with carefully-designed cognitive paradigms; however the cost of imaging limits their statistical power. On the other hand, large-scale databasing efforts increase considerably the sample sizes, but cannot ask precise cognitive questions. To address this tension, we develop new methods that turn the heterogeneous cognitive information held in different task-fMRI studies into common-universal-cognitive models.