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

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.

Data availability

All the data that we can share without violating copyright (including word counts of publications) have been shared on https://github.com/neuroquery/ alongside with the analysis scripts. Everything is readily downloadable without any authorization or login required.

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.

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.

Metrics

  • 7,975
    views
  • 697
    downloads
  • 116
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Jérôme Dockès
  2. Russell A Poldrack
  3. Romain Primet
  4. Hande Gözükan
  5. Tal Yarkoni
  6. Fabian Suchanek
  7. Bertrand Thirion
  8. Gael Varoquaux
(2020)
NeuroQuery, comprehensive meta-analysis of human brain mapping
eLife 9:e53385.
https://doi.org/10.7554/eLife.53385

Share this article

https://doi.org/10.7554/eLife.53385

Further reading

    1. Neuroscience
    Nishal Pradeepbhai Shah, AJ Phillips ... EJ Chichilnisky
    Tools and Resources

    Neural implants have the potential to restore lost sensory function by electrically evoking the complex naturalistic activity patterns of neural populations. However, it can be difficult to predict and control evoked neural responses to simultaneous multi-electrode stimulation due to nonlinearity of the responses. We present a solution to this problem and demonstrate its utility in the context of a bidirectional retinal implant for restoring vision. A dynamically optimized stimulation approach encodes incoming visual stimuli into a rapid, greedily chosen, temporally dithered and spatially multiplexed sequence of simple stimulation patterns. Stimuli are selected to optimize the reconstruction of the visual stimulus from the evoked responses. Temporal dithering exploits the slow time scales of downstream neural processing, and spatial multiplexing exploits the independence of responses generated by distant electrodes. The approach was evaluated using an experimental laboratory prototype of a retinal implant: large-scale, high-resolution multi-electrode stimulation and recording of macaque and rat retinal ganglion cells ex vivo. The dynamically optimized stimulation approach substantially enhanced performance compared to existing approaches based on static mapping between visual stimulus intensity and current amplitude. The modular framework enabled parallel extensions to naturalistic viewing conditions, incorporation of perceptual similarity measures, and efficient implementation for an implantable device. A direct closed-loop test of the approach supported its potential use in vision restoration.

    1. Neuroscience
    Cuong Pham, Yuji Komaki ... Dongdong Li
    Research Article

    Brain water homeostasis not only provides a physical protection, but also determines the diffusion of chemical molecules key for information processing and metabolic stability. As a major type of glia in brain parenchyma, astrocytes are the dominant cell type expressing aquaporin water channel. How astrocyte aquaporin contributes to brain water homeostasis in basal physiology remains to be understood. We report that astrocyte aquaporin 4 (AQP4) mediates a tonic water efflux in basal conditions. Acute inhibition of astrocyte AQP4 leads to intracellular water accumulation as optically resolved by fluorescence-translated imaging in acute brain slices, and in vivo by fiber photometry in mobile mice. We then show that aquaporin-mediated constant water efflux maintains astrocyte volume and osmotic equilibrium, astrocyte and neuron Ca2+ signaling, and extracellular space remodeling during optogenetically induced cortical spreading depression. Using diffusion-weighted magnetic resonance imaging (DW-MRI), we observed that in vivo inhibition of AQP4 water efflux heterogeneously disturbs brain water homeostasis in a region-dependent manner. Our data suggest that astrocyte aquaporin, though bidirectional in nature, mediates a tonic water outflow to sustain cellular and environmental equilibrium in brain parenchyma.