Computational Models of Descending Pain Regulatory Networks in Chronic Pain

With one in four people suffering from chronic pain in their lifetime, chronic pain is a global concern. Developing better computational models of the systems involved, in order to understand the processes of chronification, is vital for continued progress towards treatment. One key feature of acute and chronic pain perception is the modulation of ascending nociceptive pathways by descending regulatory networks. These descending circuits become dysfunctional in patients with chronic pain, with previous neurophysiological evidence suggesting their dysfunction may be due to disrupted cortical control of brainstem nuclei and rostral ventral medulla. There are clear neurophysiological features that mark their correct and dysfunctional behaviour, alongside data collected in rodents from other labs. However, computational models of descending pain networks are currently absent, and thus it is not clear why they become dysfunctional. Therefore, in line with the EPSRC Healthcare Technologies theme, I will use control theory to develop a computational model of these networks. I will then simulate their dysfunction by treating the ascending-descending pathways as a closed-loop control system to understand why they are dysfunctional in chronic pain. The implications of this research could provide targets for the pharmacological treatment of pain, and a computational model would provide predictions about the behaviour of these circuits, which could then become avenues for further experimental and pharmacological research.