A novel computational approach to pain perception modelling within a Bayesian framework using quantitative sensory testing
Drusko A, Baumeister D, McPhee Christensen M, Kold S, Fisher V, Treede R, Powers A, Graven-Nielsen T, Tesarz J. A novel computational approach to pain perception modelling within a Bayesian framework using quantitative sensory testing. Scientific Reports 2023, 13: 3196. PMID: 36823292, PMCID: PMC9950064, DOI: 10.1038/s41598-023-29758-8.Peer-Reviewed Original ResearchConceptsHierarchical Gaussian FilterPrior expectationsRelevant individual differencesPain perceptionLearning-based interventionsTesting paradigmCognitive processesSensory evidenceIndividual differencesPsychophysical paradigmInferential processesVisual cuesElectrical cutaneous stimulusPrior weightingPerceptionPain stimuliPrior beliefsIndividual levelNociceptive inputBeliefsGreater relianceStimuliStrong weightingAcute pain stimuliParadigm