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

  • 8,311
    views
  • 742
    downloads
  • 137
    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
    Sven Ohl, Martin Rolfs
    Research Article

    Detecting causal relations structures our perception of events in the world. Here, we determined for visual interactions whether generalized (i.e. feature-invariant) or specialized (i.e. feature-selective) visual routines underlie the perception of causality. To this end, we applied a visual adaptation protocol to assess the adaptability of specific features in classical launching events of simple geometric shapes. We asked observers to report whether they observed a launch or a pass in ambiguous test events (i.e. the overlap between two discs varied from trial to trial). After prolonged exposure to causal launch events (the adaptor) defined by a particular set of features (i.e. a particular motion direction, motion speed, or feature conjunction), observers were less likely to see causal launches in subsequent ambiguous test events than before adaptation. Crucially, adaptation was contingent on the causal impression in launches as demonstrated by a lack of adaptation in non-causal control events. We assessed whether this negative aftereffect transfers to test events with a new set of feature values that were not presented during adaptation. Processing in specialized (as opposed to generalized) visual routines predicts that the transfer of visual adaptation depends on the feature similarity of the adaptor and the test event. We show that the negative aftereffects do not transfer to unadapted launch directions but do transfer to launch events of different speeds. Finally, we used colored discs to assign distinct feature-based identities to the launching and the launched stimulus. We found that the adaptation transferred across colors if the test event had the same motion direction as the adaptor. In summary, visual adaptation allowed us to carve out a visual feature space underlying the perception of causality and revealed specialized visual routines that are tuned to a launch’s motion direction.

    1. Neuroscience
    Ulrike Pech, Jasper Janssens ... Patrik Verstreken
    Research Article

    The classical diagnosis of Parkinsonism is based on motor symptoms that are the consequence of nigrostriatal pathway dysfunction and reduced dopaminergic output. However, a decade prior to the emergence of motor issues, patients frequently experience non-motor symptoms, such as a reduced sense of smell (hyposmia). The cellular and molecular bases for these early defects remain enigmatic. To explore this, we developed a new collection of five fruit fly models of familial Parkinsonism and conducted single-cell RNA sequencing on young brains of these models. Interestingly, cholinergic projection neurons are the most vulnerable cells, and genes associated with presynaptic function are the most deregulated. Additional single nucleus sequencing of three specific brain regions of Parkinson’s disease patients confirms these findings. Indeed, the disturbances lead to early synaptic dysfunction, notably affecting cholinergic olfactory projection neurons crucial for olfactory function in flies. Correcting these defects specifically in olfactory cholinergic interneurons in flies or inducing cholinergic signaling in Parkinson mutant human induced dopaminergic neurons in vitro using nicotine, both rescue age-dependent dopaminergic neuron decline. Hence, our research uncovers that one of the earliest indicators of disease in five different models of familial Parkinsonism is synaptic dysfunction in higher-order cholinergic projection neurons and this contributes to the development of hyposmia. Furthermore, the shared pathways of synaptic failure in these cholinergic neurons ultimately contribute to dopaminergic dysfunction later in life.