P-008 - Ascending and Descending Pain Pathways as a Coupled Control & Feedback Loop: System-theoretical Modeling

Abstract Title: Ascending and Descending Pain Pathways as a Coupled Control & Feedback Loop: System-theoretical Modeling


Background: Recent research increasingly reveals the important contributions made by ‘descending’ pain-modulating (usually attenuating) pathways and neurotransmitter systems to pain signal processing,¹ in addition to the ‘ascending’ pain-stimulus transmitting pathways. The concept that pain could be modeled as a control system, plus the introduction of a thermostat-analogous ‘nocistat’ were introduced, to our knowledge, for the first time in a prior PAINWeek presentation.² Here we propose that the ascending and descending pathways do not function independently, but instead form an interactive control & feedback loop that allows retention of beneficial protective detection of pain while also preventing the negative sequelae of excess or unnecessarily prolonged signal input.³ We embarked on modeling the ascending and descending pain pathways as a coupled control & feedback loop system to advance understanding of the basic science and ultimately to improve pain treatment.

Purpose/Objectives: The introduced model effectuates the concept of the ascending and descending pain pathways as a coupled, integrated, and interacting control & feedback loop, and that the loop maintains homeostasis for pain monitoring and response. Planned practical extension of the introduced model to patient care includes the influence of patient-specific normal and abnormal endogenous (e.g., hormones) and exogenous (e.g., demographics, experience, drug treatment, etc.) inputs. This will allow prediction of analgesic response, i.e., pharmacodynamics (PD), instead of only pharmacokinetics (PK), in PD/PK modeling, thus guiding a more optimized regimen of analgesic administration. Ultimately, such a model could provide insight into such unexplained phenomena as opioid-induced hyperalgesia and breakthrough pain.


Methods: Informed by a previous application of control system design to sensory input processes,⁴ a simple pain feedback loop was modeled as a control system comprising three time-dependent, interacting variables: sensory input S(t), pain perception P(t), and modulation M(t). The underlying coupled 1^st-order differential equations were derived and subsequently solved using the standard Runge-Kutta-4 method with constant time steps.


Results: For starters, in the developed pain model as a coupled control and feedback loop, the pain stimulus was modeled to include rapid onset and offset of (acute) pain of various magnitudes, durations, and time profiles, such as constant, linear decay/increase, and exponential decay/increase. The individual’s perception of the respective pain stimulus was calculated as a result of the overall model. The model introduced here allows for exploration of the perception of pain with or without modulation, and, in addition, can account for individual patient pain sensitivity and environmental or psychosocial influences. The model is easily expandable to other time-dependent pain stimulus functions or input, and to effects of endogenous (e.g., hormones) and exogenous (e.g., demographics, experience, drug treatment, etc.) influence.

Conclusions/Implications for future research and/or clinical care: The concept that ascending and descending pain transmission and modulation pathways could be modeled as a control loop and analyzed using control systems engineering principles with practical clinical application in mind was previously proposed, to our knowledge, for the first time.² This work presents the first actual realization of such a model, with specific simulation outcome examples given. Using the initial control system model introduced here, pain perception as a function of pain stimulus parameters (e.g., magnitude, duration, and time profile) and modulation was obtained, with some surprising results. Future work will expand the sophistication and clinical applicability of the model to phenomena, such as, but not limited to opioid-induced hyperalgesia and breakthrough pain.


References: 1. Millan: Descending control of pain. Prog Neurobiol 66:355-474, 2002.

2. Raffa et al.: Modeling pain as a control system. PAINWeek, Las Vegas, 2016.

3. Pergolizzi, Raffa & Taylor: Treating acute pain in light of the chronification of pain. Pain Mangmt Nursing, 15:391-405, 2014.

4. Fink W, et al.: (1996) Multi-layered Perceptron as a Model for the Pupillary Pathway. German J Ophthalmol 5:160-167, 1996.

5. Bassi & Fink: Optimal Attitude Control Parameters via Stochastic Optimization Framework for Autonomous Aircraft. IEEE Aero Conf Proc, 2009.