Abstract
Ongoing pain is often driven by direct activation of pain-sensing neurons and neuroimmune mediated sensitization. These heightened states of pain alter physiology, reduce motor function, and alter motivation to engage in normal behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in nonverbal animals. Here in mice, we capture the physiological state of sensitized pain neurons at different time points post-inflammation and used computational tools to automatically map behavioral signatures of evoked and spontaneous displays of pain. First, retrograde labeling coupled with electrophysiology of neurons innervating the site of localized inflammation defined critical time points of pain sensitization. Next, we used high-speed videography combined with supervised and unsupervised machine learning tools and uncovered sensory-evoked defensive coping postures to pain. Using 3D pose analytics inspired by natural language processing, we identify movement sequences that correspond to robust representations of ongoing pain states. Surprisingly, with this analytical framework, we find that a commonly used anti-inflammatory painkiller does not return an animal’s behavior back to a pre-injury state. Together, these findings reveal the previously unidentified signatures of pain and analgesia at timescales when inflammation induces heightened pain states.
Competing Interest Statement
The authors have declared no competing interest.
