Evidence map›Paper›PMID 32758355›Full record

ArticleeLife2020

A machine-vision approach for automated pain measurement at millisecond timescales.

Jessica M Jones, William Foster, Colin R Twomey, Justin Burdge, Osama M Ahmed, Talmo D Pereira, Jessica A Wojick, Gregory Corder, Joshua B Plotkin, Ishmail Abdus-Saboor

Open access · goldAbstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
5.4field-weighted citation impact, top 3% 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

40 citing papers in PubMed, 80 citations in OpenAlex.

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  11. Mimicking opioid analgesia in cortical pain circuits.bioRxiv : the preprint server for biology · 2025
    Article
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  16. Immune drivers of physiological and pathological pain.The Journal of experimental medicine · 2024
    Article
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  20. Review
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

10 authors at 2 institutions in 1 country.

Jessica M Jones *Department of Biology, University of Pennsylvania, Philadelphia, United States.ORCID 0000-0003-3638-255X
William Foster *Department of Biology, University of Pennsylvania, Philadelphia, United States.
Colin R Twomey *Department of Biology, University of Pennsylvania, Philadelphia, United States.
Justin BurdgeDepartment of Biology, University of Pennsylvania, Philadelphia, United States.
Osama M AhmedPrinceton Neuroscience Institute, Princeton University, Princeton, United States.
Talmo D PereiraPrinceton Neuroscience Institute, Princeton University, Princeton, United States.ORCID 0000-0001-9075-8365
Jessica A WojickDepartments of Psychiatry and Neuroscience, University of Pennsylvania, Philadelphia, United States.
Gregory CorderDepartments of Psychiatry and Neuroscience, University of Pennsylvania, Philadelphia, United States.
Joshua B PlotkinDepartment of Biology, University of Pennsylvania, Philadelphia, United States.ORCID 0000-0003-2349-6304
Ishmail Abdus-SaboorDepartment of Biology, University of Pennsylvania, Philadelphia, United States.ORCID 0000-0003-2120-0063
University of Pennsylvania · USPrinceton University · US

Funding

Dissecting Sensorimotor Pathways Underlying Social Interactions: Models, Circuits, and BehaviorR01NS104899 · NINDS · PRINCETON UNIVERSITY · PI BIALEK, WILLIAM, MURTHY, MALA · 2018 to 2022
$2.4M
Determining the functions of molecularly defined populations of nociceptors in spinal and dental painR00DE026807 · NIDCR · UNIVERSITY OF PENNSYLVANIA · PI ABDUS-SABOOR, ISHMAIL JOHN · 2018 to 2020
$904k
Deconstructing the network mechanisms of chronic pain and reward in the amygdalaR00DA043609 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI CORDER, GREGORY · 2019 to 2021
$744k
NIDA NIH HHS R00 DA043609NIDCR NIH HHS R00 DE026807NIH HHS R01 NS104899NINDS NIH HHS R01 NS104899
6 · The paper itself

Abstract

Objective and automatic measurement of pain in mice remains a barrier for discovery in neuroscience. Here, we capture paw kinematics during pain behavior in mice with high-speed videography and automated paw tracking with machine and deep learning approaches. Our statistical software platform, PAWS (Pain Assessment at Withdrawal Speeds), uses a univariate projection of paw position over time to automatically quantify seven behavioral features that are combined into a single, univariate pain score. Automated paw tracking combined with PAWS reveals a behaviorally divergent mouse strain that displays hypersensitivity to mechanical stimuli. To demonstrate the efficacy of PAWS for detecting spinally versus centrally mediated behavioral responses, we chemogenetically activated nociceptive neurons in the amygdala, which further separated the pain-related behavioral features and the resulting pain score. Taken together, this automated pain quantification approach will increase objectivity in collecting rigorous behavioral data, and it is compatible with other neural circuit dissection tools for determining the mouse pain state.

Indexed as

AnimalsAutomation, LaboratoryFemaleMaleMicePain MeasurementTime Factorsautomationhigh-speed videographymachine learningmouseneural circuitsneurosciencepainsomatosensation

Identifiers

PMID32758355
PMCPMC7434442
OpenAlexW3047805832

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.