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

Author:

Jones Jessica M1ORCID,Foster William1,Twomey Colin R1,Burdge Justin1,Ahmed Osama M2,Pereira Talmo D2ORCID,Wojick Jessica A3,Corder Gregory3,Plotkin Joshua B1ORCID,Abdus-Saboor Ishmail1ORCID

Affiliation:

1. Department of Biology, University of Pennsylvania, Philadelphia, United States

2. Princeton Neuroscience Institute, Princeton University, Princeton, United States

3. Departments of Psychiatry and Neuroscience, University of Pennsylvania, Philadelphia, United States

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.

Funder

National Institutes of Health

Army Research Office

Defense Advanced Research Projects Agency

Burroughs Wellcome Fund

mindCORE

David and Lucile Packard Foundation

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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