1. Neuroscience
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NeuroQuery, comprehensive meta-analysis of human brain mapping

  1. Jérôme Dockès  Is a corresponding author
  2. Russell A Poldrack
  3. Romain Primet
  4. Hande Gözükan
  5. Tal Yarkoni
  6. Fabian Suchanek
  7. Bertrand Thirion
  8. Gael Varoquaux  Is a corresponding author
  1. INRIA, France
  2. Stanford University, United States
  3. University of Texas at Austin, United States
  4. Télécom Paris University, France
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Cite this article as: eLife 2020;9:e53385 doi: 10.7554/eLife.53385

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 7547 neuroscience terms across 13459 neuroimaging publications. The resulting meta-analytic tool, neuroquery.org, can ground hypothesis generation and data-analysis priors on a comprehensive view of published findings on the brain.

Article and author information

Author details

  1. Jérôme Dockès

    Parietal, INRIA, Palaiseau, France
    For correspondence
    jerome@dockes.org
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5304-2496
  2. Russell A Poldrack

    Department of Psychology, Stanford University, Stanford, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6755-0259
  3. Romain Primet

    Parietal, INRIA, Palaiseau, France
    Competing interests
    No competing interests declared.
  4. Hande Gözükan

    Parietal, INRIA, Palaiseau, France
    Competing interests
    No competing interests declared.
  5. Tal Yarkoni

    Department of Psychology, University of Texas at Austin, Austin, United States
    Competing interests
    No competing interests declared.
  6. Fabian Suchanek

    Data, Intelligence, and Graphs, Télécom Paris University, Palaiseau, France
    Competing interests
    No competing interests declared.
  7. Bertrand Thirion

    Parietal, INRIA, Paris, France
    Competing interests
    No competing interests declared.
  8. Gael Varoquaux

    Parietal, INRIA, Palaiseau, France
    For correspondence
    gael.varoquaux@inria.fr
    Competing interests
    Gael Varoquaux, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1076-5122

Funding

Digiteo (2016-1270D - Projet MetaCog)

  • Jérôme Dockès

National Institutes of Health (R01MH096906)

  • Tal Yarkoni

Agence Nationale de la Recherche (ANR-16- CE23-0007-01)

  • Fabian Suchanek

H2020 European Research Council (785907 (HBP SGA2))

  • Bertrand Thirion

H2020 European Research Council (826421 (VirtualbrainCloud))

  • Bertrand Thirion

Canada First Research Excellence Fund (Healthy Brains for Healthy Lives initiative)

  • Gael Varoquaux

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Thomas Yeo, National University of Singapore, Singapore

Publication history

  1. Received: November 6, 2019
  2. Accepted: March 3, 2020
  3. Accepted Manuscript published: March 4, 2020 (version 1)
  4. Version of Record published: April 17, 2020 (version 2)

Copyright

© 2020, Dockès et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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