Analgesia for the Bayesian Brain: How Predictive Coding Offers Insights Into the Subjectivity of Pain.
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BORIS DOI
Date of Publication
November 2023
Publication Type
Article
Division/Institute
Author
Lersch, Friedrich E | |
Urman, Richard D | |
Burgermeister, Gabriel | |
Siercks, Kaya | |
Luedi, Markus M |
Subject(s)
Series
Current pain and headache reports
ISSN or ISBN (if monograph)
1534-3081
Publisher
Springer
Language
English
Publisher DOI
PubMed ID
37421540
Uncontrolled Keywords
Description
PURPOSE OF REVIEW
In order to better treat pain, we must understand its architecture and pathways. Many modulatory approaches of pain management strategies are only poorly understood. This review aims to provide a theoretical framework of pain perception and modulation in order to assist in clinical understanding and research of analgesia and anesthesia.
RECENT FINDINGS
Limitations of traditional models for pain have driven the application of new data analysis models. The Bayesian principle of predictive coding has found increasing application in neuroscientific research, providing a promising theoretical background for the principles of consciousness and perception. It can be applied to the subjective perception of pain. Pain perception can be viewed as a continuous hierarchical process of bottom-up sensory inputs colliding with top-down modulations and prior experiences, involving multiple cortical and subcortical hubs of the pain matrix. Predictive coding provides a mathematical model for this interplay.
In order to better treat pain, we must understand its architecture and pathways. Many modulatory approaches of pain management strategies are only poorly understood. This review aims to provide a theoretical framework of pain perception and modulation in order to assist in clinical understanding and research of analgesia and anesthesia.
RECENT FINDINGS
Limitations of traditional models for pain have driven the application of new data analysis models. The Bayesian principle of predictive coding has found increasing application in neuroscientific research, providing a promising theoretical background for the principles of consciousness and perception. It can be applied to the subjective perception of pain. Pain perception can be viewed as a continuous hierarchical process of bottom-up sensory inputs colliding with top-down modulations and prior experiences, involving multiple cortical and subcortical hubs of the pain matrix. Predictive coding provides a mathematical model for this interplay.
File(s)
| File | File Type | Format | Size | License | Publisher/Copright statement | Content | |
|---|---|---|---|---|---|---|---|
| s11916-023-01122-5.pdf | text | Adobe PDF | 2.26 MB | published |