Evidence map›Paper›PMID 35997072›Full record

ArticleeLife2022

BehaviorDEPOT is a simple, flexible tool for automated behavioral detection based on markerless pose tracking.

Christopher J Gabriel, Zachary Zeidler, Benita Jin, Changliang Guo, Caitlin M Goodpaster, Adrienne Q Kashay, Anna Wu, Molly Delaney, Jovian Cheung, Lauren E DiFazio and 4 more

Abstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
–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

47 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Asymmetrical modulation of fear expression via GABAProceedings of the National Academy of Sciences of the United States of America · 2026
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  20. Directed cell-type recruitment during consolidation of a remote memory.bioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Christopher J GabrielDepartment of Physiology, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0003-3193-2807
Zachary ZeidlerDepartment of Physiology, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0001-6539-4360
Benita JinDepartment of Physiology, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0002-2580-8618
Changliang GuoDepartment of Neurology, University of California, Los Angeles, Los Angeles, United States.
Caitlin M GoodpasterUCLA Neuroscience Interdepartmental Program, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0002-2456-9010
Adrienne Q KashayDepartment of Psychiatry, University of California, Los Angeles, Los Angeles, United States.
Anna WuDepartment of Physiology, University of California, Los Angeles, Los Angeles, United States.
Molly DelaneyDepartment of Psychiatry, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0002-4464-7282
Jovian CheungDepartment of Psychiatry, University of California, Los Angeles, Los Angeles, United States.
Lauren E DiFazioDepartment of Psychology, University of California, Los Angeles, Los Angeles, United States.
Melissa J SharpeDepartment of Psychology, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0002-5375-2076
Daniel AharoniDepartment of Neurology, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0003-4931-8514
Scott A WilkeDepartment of Psychiatry, University of California, Los Angeles, Los Angeles, United States.
Laura A DeNardoDepartment of Physiology, University of California, Los Angeles, Los Angeles, United States.ORCID 0000-0002-7607-4773

Funding

Training Grant in Neurobehavioral GeneticsT32NS048004 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BEARDEN, CARRIE E, OPHOFF, ROEL A · 2004 to 2025
$5.8M
Training Grant in Neurobehavioral GeneticsT32MH073526 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BEARDEN, CARRIE E, GESCHWIND, DANIEL H · 2006 to 2020
$2.4M
Dopaminergic regulation of prefrontal activity patterns during behaviorK08MH116125 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WILKE, SCOTT ALLEN · 2018 to 2022
$991k
Circuit mechanisms for prefrontal control of remote memory retrievalK01MH116264 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DENARDO, LAURA ANNE · 2018 to 2021
$681k
Investigating the Recruitment of Lateral Hypothalamic Circuits for Encoding Fear Memories Following Experience with Reward LearningR21MH126278 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SHARPE, MELISSA · 2022 to 2023
$429k
NIMH NIH HHS K01 MH116264NIMH NIH HHS K08 MH116125NIMH NIH HHS R21 MH126278NIMH NIH HHS T32 MH073526NINDS NIH HHS T32 NS048004
6 · The paper itself

Abstract

Quantitative descriptions of animal behavior are essential to study the neural substrates of cognitive and emotional processes. Analyses of naturalistic behaviors are often performed by hand or with expensive, inflexible commercial software. Recently, machine learning methods for markerless pose estimation enabled automated tracking of freely moving animals, including in labs with limited coding expertise. However, classifying specific behaviors based on pose data requires additional computational analyses and remains a significant challenge for many groups. We developed BehaviorDEPOT (DEcoding behavior based on POsitional Tracking), a simple, flexible software program that can detect behavior from video timeseries and can analyze the results of experimental assays. BehaviorDEPOT calculates kinematic and postural statistics from keypoint tracking data and creates heuristics that reliably detect behaviors. It requires no programming experience and is applicable to a wide range of behaviors and experimental designs. We provide several hard-coded heuristics. Our freezing detection heuristic achieves above 90% accuracy in videos of mice and rats, including those wearing tethered head-mounts. BehaviorDEPOT also helps researchers develop their own heuristics and incorporate them into the software's graphical interface. Behavioral data is stored framewise for easy alignment with neural data. We demonstrate the immediate utility and flexibility of BehaviorDEPOT using popular assays including fear conditioning, decision-making in a T-maze, open field, elevated plus maze, and novel object exploration.

Indexed as

Behavior, AnimalSoftwareAnimalsBiomechanical PhenomenaMachine LearningRatsautomated behavioral analysisconditioned feardecision-makingdeeplabcutminicammouseneuroscienceopen-sourcerat

Identifiers

PMID35997072
PMCPMC9398447

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.