The Effect of Perioperative Auditory Stimulation with Music on Procedural Pain: A Narrative Review.

PURPOSE OF REVIEW: Music therapy has seen increasing applications in various medical fields over the last decades. In the vast range of possibilities through which music can relieve suffering, there is a risk that-given its efficacy-the physiological underpinnings are too little understood. This review provides evidence-based neurobiological concepts for the use of music in perioperative pain management. RECENT FINDINGS: The current neuroscientific literature shows a significant convergence of the pain matrix and neuronal networks of pleasure triggered by music. These functions seem to antagonize each other and can thus be brought to fruition in pain therapy. The encouraging results of fMRI and EEG studies still await full translation of this top-down modulating mechanism into broad clinical practice. We embed the current clinical literature in a neurobiological framework. This involves touching on Bayesian "predictive coding" pain theories in broad strokes and outlining functional units in the nociception and pain matrix. These will help to understand clinical findings in the literature summarized in the second part of the review. There are opportunities for perioperative practitioners, including anesthesiologists treating acute pain and anxiety in emergency and perioperative situations, where music could help bring relieve to patients.

Analgesia for the Bayesian Brain: How Predictive Coding Offers Insights Into the Subjectivity of Pain.

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.