Evidence map›Paper›PMID 35414125›Full record

ArticleNature methods2022

Multi-animal pose estimation, identification and tracking with DeepLabCut.

Jessy Lauer, Mu Zhou, Shaokai Ye, William Menegas, Steffen Schneider, Tanmay Nath, Mohammed Mostafizur Rahman, Valentina Di Santo, Daniel Soberanes, Guoping Feng and 5 more

Abstract read
In one paragraph

Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 275 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
275citing papers in PubMed, 2 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

275 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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215 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Jessy LauerBrain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Mu ZhouBrain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Shaokai YeBrain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
William MenegasDepartment of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Steffen SchneiderBrain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Tanmay NathRowland Institute at Harvard, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-2092-7159
Mohammed Mostafizur RahmanDepartment for Molecular Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
Valentina Di SantoDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Daniel SoberanesRowland Institute at Harvard, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-9099-7294
Guoping FengDepartment of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-8021-277X
Venkatesh N MurthyDepartment for Molecular Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-2443-4252
George LauderDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
Catherine DulacDepartment for Molecular Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
Mackenzie Weygandt MathisBrain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. mackenzie@post.harvard.edu.ORCID http://orcid.org/0000-0001-7368-4456
Alexander MathisBrain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. alexander.mathis@epfl.ch.ORCID http://orcid.org/0000-0002-3777-2202

Funding

Systems-level and in situ transcriptomics deconstruction of neural circuits underlying sensorimotor transformation in an innate behaviorRF1NS116593 · NINDS · HARVARD UNIVERSITY · PI DULAC, CATHERINE, MURTHY, VENKATESH N · 2020 to 2020
$4.4M
Microcircuits underlying murine parental behaviorR01HD082131 · NICHD · HARVARD UNIVERSITY · PI DULAC, CATHERINE · 2015 to 2024
$3.5M
Systems-Level and in Situ Transcriptomics Deconstruction of Neural Circuits Underlying Sensorimotor Transformation in an Innate BehaviorR01NS116593 · NINDS · HARVARD UNIVERSITY · PI DULAC, CATHERINE, MURTHY, VENKATESH N · 2023 to 2024
$2.7M
Howard Hughes Medical InstituteNICHD NIH HHS R01 HD082131NINDS NIH HHS R01 NS116593
6 · The paper itself

Abstract

Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having highly similar looking animals that interact more closely than in typical multi-human scenarios. To take up this challenge, we build on DeepLabCut, an open-source pose estimation toolbox, and provide high-performance animal assembly and tracking-features required for multi-animal scenarios. Furthermore, we integrate the ability to predict an animal's identity to assist tracking (in case of occlusions). We illustrate the power of this framework with four datasets varying in complexity, which we release to serve as a benchmark for future algorithm development.

Indexed as

AlgorithmsAnimals

Identifiers

PMID35414125
PMCPMC9007739

What OpenQuestion holds

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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.