Behavioral and nociceptor states of inflammatory pain across timescales in 2D and 3D

Inflammatory pain represents a complex state involving sensitization of peripheral and central neuronal signaling. Resolving this high-dimensional interplay at the cellular and behavioral level is key to effective therapeutic development. Here, using the carrageenan model of local inflammation of the hind paw, we determine how carrageenan alters both the physiological state of sensory neurons and behaviors at rapid and continuous timescales. We identify higher excitability of sensory neurons innervating the site of inflammation by profiling their physiological state at different time points. To identify millisecond-resolved sensory-reflexive signatures evoked by inflammatory pain, we used a combination of supervised and unsupervised algorithms, and uncovered abnormal paw placement as a defining behavioral feature. For long-term detection and characterization of spontaneous behavioral signatures representative of affective-motivational pain states, we use computer vision coupled to unsupervised machine learning in an open arena. Using the non-steroidal anti-inflammatory drug meloxicam to characterize analgesic states during rapid and ongoing timescales, we identify a return to pre-injury states of some sensory-reflexive behaviors, but by and large, many spontaneous, affective-motivational pain behaviors remain unaffected. Taken together, this comprehensive exploration across cellular and behavioral dimensions reveals peripheral versus centrally mediated pain signatures that define the inflamed state, providing a framework for scaling the pain experience at unprecedented resolution.