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Related Concept Videos

Analgesia and Pain Management01:25

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Pain is critical to various clinical pathologies, provoking an urgent need for effective management. Pain, whether acute or chronic, is a complex neurochemical process. Its alleviation depends on the type, with nonopioid analgesics effective for mild to moderate pain, such as musculoskeletal or inflammatory pain, while neuropathic pain responds best to anticonvulsants, tricyclic antidepressants, or serotonin/norepinephrine reuptake inhibitors. For severe acute or chronic pain, opioids may be...
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Nociception—the ability to feel pain—is essential for an organism’s survival and overall well-being. Noxious stimuli such as piercing pain from a sharp object, heat from an open flame, or contact with corrosive chemicals are first detected by sensory receptors, called nociceptors, located on nerve endings. Nociceptors express ion channels that convert noxious stimuli into electrical signals. When these signals reach the brain via sensory neurons, they are perceived as pain.
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Pain serves as a critical warning signal that alerts the body to potential or actual harm. When mechanical pressure on the skin is intense, such as from a sharp pinch, the sensation transitions from touch to pain. Similarly, extreme temperatures, like a hot pot handle, convert the sensation of heat into pain. Pain can also result from overstimulation of other senses, such as blinding light, loud noise, or the intense heat from habañero peppers. This ability to sense pain is essential for...
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Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery
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A Bayesian model for chronic pain.

Anna-Lena Eckert1, Kathrin Pabst1, Dominik M Endres1

  • 1Theoretical Cognitive Science Group, Department of Psychology, Philipps-University Marburg, Marburg, Germany.

Frontiers in Pain Research (Lausanne, Switzerland)
|October 28, 2022
PubMed
Summary
This summary is machine-generated.

Pain perception arises from combining prior beliefs with sensory data using Bayesian inference. Chronic pain may result from biased inference, which this computational model simulates and explores treatment options for.

Keywords:
Bayesian inferencebelief-propagationchronic paincomputational psychiatryfree energygraphical modelsinteroceptionpredictive coding

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Area of Science:

  • Computational Neuroscience
  • Pain Perception Modeling
  • Bayesian Inference

Background:

  • The human mind integrates multi-modal sensory information for coherent experience.
  • Pain perception is hypothesized to be an inferential process, not just a direct sensory response.
  • Chronic pain may involve biased inference, misinterpreting harmless stimuli as painful.

Purpose of the Study:

  • To present a computational model of interoceptive inference and pain experience.
  • To investigate the role of Bayesian inference in healthy and chronic pain perception.
  • To simulate treatment-resistant chronic pain and explore mathematical treatment strategies.

Main Methods:

  • Developed a Bayesian graphical network model with hidden (inferred pain state) and observable (sensory information) layers.
  • Utilized variational inference and free-energy minimization for model learning over time.
  • Manipulated model parameters to simulate healthy and chronic pain states.

Main Results:

  • The computational model successfully reproduced key characteristics of both healthy and chronic pain perception.
  • Model parameters were systematically adjusted to demonstrate the emergence of biased inference leading to chronic pain.
  • Simulations explored the potential for mathematical approaches to understand and treat chronic pain.

Conclusions:

  • Pain perception can be understood as a Bayesian inferential process influenced by prior beliefs and sensory data.
  • Chronic pain may arise from maladaptive inference, where priors lead to over-inference of pain.
  • Computational modeling offers a framework for understanding pain mechanisms and developing mathematically informed treatments.