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Poster Session A: Tuesday, August 12, 1:30 – 4:30 pm, de Brug & E‑Hall

Homeostasis After Injury: How Intertwined Inference and Control Underpin Post-Injury Pain and Behaviour

Pranav Mahajan¹, Peter Dayan², Ben Seymour¹; ¹University of Oxford, ²Max-Planck Institute

Presenter: Pranav Mahajan

Several arguments suggest that the brain might have a dedicated representation of the state of injury. This would provide an internal control system to modulate behaviour given the changed homeostatic priorities associated with injury, including pain, anxiety and mood changes appropriate to the need for heightened protection and recuperation during healing. Here, we propose a computational architecture for how this might be constructed, treating the injury as a partially observable Markov decision process (POMDP), and proposing a Bayesian decision-theoretic solution that combines inference with optimal control. We show how this offers an explanation of two core paradoxical observations: behaviours such as rubbing an injured area (conventionally viewed under the lens of gate control theory), and high propensity of transition to pathological chronic pain states. Overall, this provides a quantitative framework for mapping injury homeostasis to neural substrates, with potential for identifying novel chronic pain targets. Full paper: https://www.biorxiv.org/content/10.1101/2025.02.04.636410v2

Topic Area: Predictive Processing & Cognitive Control

Extended Abstract: Full Text PDF