2023
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
2022
Conditioned Hallucinations and Prior Overweighting Are State-Sensitive Markers of Hallucination Susceptibility
Kafadar E, Fisher VL, Quagan B, Hammer A, Jaeger H, Mourgues C, Thomas R, Chen L, Imtiaz A, Sibarium E, Negreira AM, Sarisik E, Polisetty V, Benrimoh D, Sheldon AD, Lim C, Mathys C, Powers AR. Conditioned Hallucinations and Prior Overweighting Are State-Sensitive Markers of Hallucination Susceptibility. Biological Psychiatry 2022, 92: 772-780. PMID: 35843743, PMCID: PMC10575690, DOI: 10.1016/j.biopsych.2022.05.007.Peer-Reviewed Original ResearchConceptsCH rateIncoming sensory evidenceSensory evidencePerceptual statesTask performanceComputational psychiatrySubset of participantsPrior expectationsHallucination severityBehavioral dataSymptom severityPast experienceStable measureHallucinationsPsychotic symptomsHallucination frequencyTaskSymptom expressionBayesian modelState markerHallucinatorsNonhallucinatorsOverweightingPerceptionSymptom riskPerceptual pathways to hallucinogenesis
Sheldon AD, Kafadar E, Fisher V, Greenwald MS, Aitken F, Negreira AM, Woods SW, Powers AR. Perceptual pathways to hallucinogenesis. Schizophrenia Research 2022, 245: 77-89. PMID: 35216865, PMCID: PMC9232894, DOI: 10.1016/j.schres.2022.02.002.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2020
Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework
Kafadar E, Mittal VA, Strauss GP, Chapman HC, Ellman LM, Bansal S, Gold JM, Alderson-Day B, Evans S, Moffatt J, Silverstein SM, Walker EF, Woods SW, Corlett PR, Powers AR. Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework. Schizophrenia Research 2020, 226: 167-175. PMID: 32593735, PMCID: PMC7774587, DOI: 10.1016/j.schres.2020.04.017.Peer-Reviewed Original ResearchConceptsClinical high riskCHR participantsDegraded speech stimuliPredictive processing frameworkUtility of interventionsSample of participantsPerceptual inferenceSensory evidencePsychotic spectrum disordersSpeech stimuliSpeech taskComputational underpinningsBehavioral tasksEfficacy of interventionsSpectrum disorderTarget tonesParticipants' performanceComputational modelingHigh riskPoor recognitionLatent factorsSuch tasksPrior beliefsTaskAppropriate risk stratification