Lersch, Friedrich EFriedrich ELerschFrickmann, Fabienne Conny SaraFabienne Conny SaraFrickmannUrman, Richard DRichard DUrmanBurgermeister, GabrielGabrielBurgermeisterSiercks, KayaKayaSiercksLuedi, Markus MMarkus MLuediStraumann, SvenSvenStraumann2024-10-252024-10-252023-11https://boris-portal.unibe.ch/handle/20.500.12422/168572PURPOSE 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.enActive inference Analgesia Anesthesia Bayes’ theorem Markov blanket Pain Predictive coding600 - Technology::610 - Medicine & healtharticle10.48350/1846073742154010.1007/s11916-023-01122-5