A machine-vision approach for automated pain measurement at millisecond timescales.
automation
high-speed videography
machine learning
mouse
neural circuits
neuroscience
pain
somatosensation
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
06 08 2020
06 08 2020
Historique:
received:
26
03
2020
accepted:
05
08
2020
pubmed:
8
8
2020
medline:
13
2
2021
entrez:
8
8
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 32758355
doi: 10.7554/eLife.57258
pii: 57258
pmc: PMC7434442
doi:
pii:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Defense Advanced Research Projects Agency
ID : D17AC00005
Pays : International
Organisme : NIDCR NIH HHS
ID : R00 DE026807
Pays : United States
Organisme : NIDA NIH HHS
ID : R00 DA043609
Pays : United States
Organisme : Army Research Office
ID : W911NF-17-1-0083
Pays : International
Organisme : NIH HHS
ID : R01 NS104899
Pays : United States
Informations de copyright
© 2020, Jones et al.
Déclaration de conflit d'intérêts
JJ, WF, CT, JB, OA, TP, JW, GC, JP, IA No competing interests declared
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