Evidence map›Paper›PMID 34764476›Full record

ArticleNature neuroscience2021

A data-driven framework for mapping domains of human neurobiology.

Elizabeth Beam, Christopher Potts, Russell A Poldrack, Amit Etkin

Open access · greenAbstract read
In one paragraph

Article in Nature neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
4.1field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 68 citations in OpenAlex.

  1. Pooled it
  2. Evidence for domain-general arousal from semantic and neuroimaging meta-analyses reconciles opposing views on arousal.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Pooled it
  3. Article
  4. Article
  5. An Interactive Brain Atlas of Knowledge.bioRxiv : the preprint server for biology · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Never-Ending Learning for Explainable Brain Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Elizabeth BeamWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
Christopher PottsDepartment of Linguistics, Stanford University, Stanford, CA, USA.
Russell A PoldrackWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-6755-0259
Amit EtkinWu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA. amitetkin@altoneuroscience.com.ORCID http://orcid.org/0000-0001-8259-3521
Neurosciences Institute · USStanford University · US

Funding

A “Circuits-First” Platform for Personalized Neurostimulation TreatmentDP1MH116506 · NIMH · STANFORD UNIVERSITY · PI ETKIN, AMIT · 2017 to 2021
$5.2M
Computational ontology of brain systems across the human neuroimaging literatureF30MH120956 · NIMH · STANFORD UNIVERSITY · PI BEAM, ELIZABETH HELEN · 2020 to 2022
$87k
NIMH NIH HHS DP1 MH116506NIMH NIH HHS F30 MH120956
6 · The paper itself

Abstract

Functional neuroimaging has been a mainstay of human neuroscience for the past 25 years. Interpretation of functional magnetic resonance imaging (fMRI) data has often occurred within knowledge frameworks crafted by experts, which have the potential to amplify biases that limit the replicability of findings. Here, we use a computational approach to derive a data-driven framework for neurobiological domains that synthesizes the texts and data of nearly 20,000 human neuroimaging articles. Across multiple levels of domain specificity, the structure-function links within domains better replicate in held-out articles than those mapped from dominant frameworks in neuroscience and psychiatry. We further show that the data-driven framework partitions the literature into modular subfields, for which domains serve as generalizable prototypes of structure-function patterns in single articles. The approach to computational ontology we present here is the most comprehensive characterization of human brain circuits quantifiable with fMRI and may be extended to synthesize other scientific literatures.

Indexed as

NeurosciencesPsychiatryBrainBrain MappingHumansMagnetic Resonance ImagingNeurobiologyNeuroimaging

Identifiers

PMID34764476
PMCPMC8761068
OpenAlexW3212575075

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.