Mapping the neuroethological signatures of pain, analgesia, and recovery in mice

Manon Bohic, Luke A. Pattison, Z. Anissa Jhumka, Heather Rossi, Joshua K. Thackray, Matthew Ricci, Nahom Mossazghi, William Foster, Simon Ogundare, Colin R. Twomey, Helen Hilton, Justin Arnold, Max A. Tischfield, Eric A. Yttri, Ewan St. John Smith, Ishmail Abdus-Saboor, Victoria E. Abraira

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Ongoing pain is driven by the activation and modulation of pain-sensing neurons, affecting physiology, motor function, and motivation to engage in certain behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in non-verbal animals. Here, in mice, we used site-specific electrophysiology to define key time points corresponding to peripheral sensitivity in acute paw inflammation and chronic knee pain models. Using supervised and unsupervised machine learning tools, we uncovered sensory-evoked coping postures unique to each model. Through 3D pose analytics, we identified movement sequences that robustly represent different pain states and found that commonly used analgesics do not return an animal's behavior to a pre-injury state. Instead, these analgesics induce a novel set of spontaneous behaviors that are maintained even after resolution of evoked pain behaviors. Together, these findings reveal previously unidentified neuroethological signatures of pain and analgesia at heightened pain states and during recovery.

Original languageEnglish (US)
Pages (from-to)2811-2830.e8
JournalNeuron
Volume111
Issue number18
DOIs
StatePublished - Sep 20 2023
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Neuroscience

Keywords

  • analgesia
  • behavior
  • computer vision
  • electrophysiology
  • machine learning
  • motion sequencing
  • mouse
  • nociception
  • pain
  • recovery

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