Evidence map›Paper›PMID 42733062›Full record

ArticleNature communications2026

The choice-wide behavioral association study: data-driven identification of interpretable behavioral components.

David B Kastner, Nicole O Yokota, Christina Y Lee, Cristofer Holobetz, Ali Chaudhry, Greer Williams, Jane N Ton, Mihika Mehra, Viktor Kharazia, Dilworth Y Parkinson and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Autism-associatedProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. DecipheringArXiv · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

David B KastnerDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA. david.kastner2@ucsf.edu.ORCID http://orcid.org/0000-0001-9681-425X
Nicole O YokotaDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.ORCID http://orcid.org/0009-0009-7295-2266
Christina Y LeeDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.ORCID http://orcid.org/0000-0003-0757-0340
Cristofer HolobetzDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
Ali ChaudhryDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.ORCID http://orcid.org/0009-0002-1142-5621
Greer WilliamsDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
Jane N TonDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
Mihika MehraDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
Viktor KharaziaDepartment of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.ORCID http://orcid.org/0000-0003-0642-6080
Dilworth Y ParkinsonAdvanced Light Source, Lawrence Berkeley National Labs, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-1817-0716
Joseph P RomanoDepartment of Statistics, Stanford University, Stanford, CA, USA.
Peter DayanMax Planck Institute for Biological Cybernetics, Tübingen, Germany.ORCID http://orcid.org/0000-0003-3476-1839

Funding

TRAINING THE NEXT GENERATION OF MENTAL HEALTH RESEARCHERSR25MH060482 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DANIEL H MATHALON, Susan M. Voglmaier · 2000 to 2026
$5.2M
Determining the information processing changes that underlie the phenotype of an ASD risk gene in ratsK08MH139983 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI David B Kastner · 2025 to 2026
$395k
NIMH NIH HHS K08 MH139983NIMH NIH HHS R25 MH060482Simons Foundation 899599U.S. Department of Health & Human Services | National Institutes of Health (NIH) K08MH139983U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) K08MH139983
6 · The paper itself

Abstract

Behavior contains rich structure across many timescales. However, there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method-the choice-wide behavioral association study: CBAS-that systematically identifies such behavioral features. CBAS extracts sequences of actions or choices that either significantly differ between groups or correlate with a covariate of interest, using a powerful resampling-based method to correct for multiple comparisons. We illustrate CBAS through application to tasks performed by flies, rats, and humans, showing that it provides unexpected and interpretable information in each case.

Indexed as

Behavior, AnimalChoice BehaviorAnimalsDecision MakingDrosophila melanogasterGenome-Wide Association StudyHumansRats

Identifiers

PMID42733062
PMCPMC13572513

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.