Lersch, Friedrich E; Frickmann, Fabienne C S; Urman, Richard D; Burgermeister, Gabriel; Siercks, Kaya; Luedi, Markus M; Straumann, Sven (2023). Analgesia for the Bayesian Brain: How Predictive Coding Offers Insights Into the Subjectivity of Pain. Current pain and headache reports, 27(11), pp. 631-638. Springer 10.1007/s11916-023-01122-5
|
Text
s11916-023-01122-5.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (2MB) | Preview |
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.
Item Type: |
Journal Article (Review Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > Clinic and Policlinic for Anaesthesiology and Pain Therapy > Partial clinic Insel 04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > Clinic and Policlinic for Anaesthesiology and Pain Therapy |
UniBE Contributor: |
Frickmann, Fabienne Conny Sara, Straumann, Sven |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
1534-3081 |
Publisher: |
Springer |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
10 Jul 2023 11:00 |
Last Modified: |
12 Dec 2023 00:12 |
Publisher DOI: |
10.1007/s11916-023-01122-5 |
PubMed ID: |
37421540 |
Uncontrolled Keywords: |
Active inference Analgesia Anesthesia Bayes’ theorem Markov blanket Pain Predictive coding |
BORIS DOI: |
10.48350/184607 |
URI: |
https://boris.unibe.ch/id/eprint/184607 |
Actions (login required)
 |
Edit item |