Skip to Main content Skip to Navigation
Journal articles

NeuroQuery, comprehensive meta-analysis of human brain mapping

Abstract : Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms. The variety of human neuroscience concepts and terminology poses a fundamental challenge to relating brain imaging results across the scientific literature. Existing meta-analysis methods perform statistical tests on sets of publications associated with a particular concept. Thus, large-scale meta-analyses only tackle single terms that occur frequently. We propose a new paradigm, focusing on prediction rather than inference. Our multivariate model predicts the spatial distribution of neurological observations, given text describing an experiment, cognitive process, or disease. This approach handles text of arbitrary length and terms that are too rare for standard meta-analysis. We capture the relationships and neural correlates of 7 547 neuroscience terms across 13 459 neuroimaging publications. The resulting meta-analytic tool,, can ground hypothesis generation and data-analysis priors on a comprehensive view of published findings on the brain.
Complete list of metadata
Contributor : Jérôme Dockès Connect in order to contact the contributor
Submitted on : Friday, March 6, 2020 - 4:30:39 PM
Last modification on : Saturday, July 23, 2022 - 3:52:55 AM
Long-term archiving on: : Sunday, June 7, 2020 - 12:29:20 PM


  • HAL Id : hal-02485642, version 2
  • ARXIV : 2002.09261


Jérôme Dockès, Russell Poldrack, Romain Primet, Hande Gözükan, Tal Yarkoni, et al.. NeuroQuery, comprehensive meta-analysis of human brain mapping. eLife, eLife Sciences Publication, 2020. ⟨hal-02485642v2⟩



Record views


Files downloads