Andrew Sheldon, MD/PhD
Clinical FellowDownloadHi-Res Photo
About
Titles
Clinical Fellow
Solnit Integrated Program, Yale Child Study Center
Biography
Andrew Sheldon received his undergraduate training at the University of California Berkley with a concentration in Physics before attending the University of Wisconsin School of Medicine and Public Health for his M.D. PhD where he applied computational methods and modeling to neuroimaging data to better understand the interactions between attention and working memory. After completing this work in 2019, he was accepted into the Solnit integrated research track combined residency and fellowship in adult and child psychiatry, where he currently works in the Al Powers lab using computational modeling approaches to understand the neural mechanisms underlying hallucinations, in addition to his clinical psychiatry duties caring for children and adolescents through the Yale Child Study Center and Yale New Haven Children's hospital.
Appointments
Child Study Center
Clinical FellowPrimary
Other Departments & Organizations
Education & Training
- MD/PhD
- University of Wisconsin Madison School of Medicine and Public Health, Neuroscience (2019)
Research
Research at a Glance
Yale Co-Authors
Frequent collaborators of Andrew Sheldon's published research.
Albert Powers, MD, PhD
Ely Sibarium
Claire Bien
Maximillian Greenwald
Publications
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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsCH 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 StatementsCitationsAltmetricMeasuring Voluntary Control Over Hallucinations: The Yale Control Over Perceptual Experiences (COPE) Scales
Mourgues C, Hammer A, Fisher V, Kafadar E, Quagan B, Bien C, Jaeger H, Thomas R, Sibarium E, Negreira AM, Sarisik E, Polisetty V, Eken H, Imtiaz A, Niles H, Sheldon AD, Powers AR. Measuring Voluntary Control Over Hallucinations: The Yale Control Over Perceptual Experiences (COPE) Scales. Schizophrenia Bulletin 2022, 48: 673-683. PMID: 35089361, PMCID: PMC9077437, DOI: 10.1093/schbul/sbab144.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsAuditory verbal hallucinationsPositive clinical outcomesClinical outcomesPilot studyQuality of lifeConvergent validityFrequent auditory verbal hallucinationsExperiences ScaleClinical measuresConventional treatmentNovel interventionsSymptom severitySignificant distressClinical scalesComprehensive batteryPsychosis-spectrum diagnosisVerbal hallucinationsSound psychometric propertiesAVH contentVoluntary controlPsychometric propertiesHallucinationsControl ScaleValidation studyIntervention
2021
Computational Mechanism for the Effect of Psychosis Community Treatment: A Conceptual Review From Neurobiology to Social Interaction
Benrimoh D, Sheldon A, Sibarium E, Powers AR. Computational Mechanism for the Effect of Psychosis Community Treatment: A Conceptual Review From Neurobiology to Social Interaction. Frontiers In Psychiatry 2021, 12: 685390. PMID: 34385938, PMCID: PMC8353084, DOI: 10.3389/fpsyt.2021.685390.Peer-Reviewed Original ResearchCitationsAltmetricConceptsComputational modelAssertive community treatmentProcessing-based accountExperience of psychosisEvidence-based clinical interventionsCommunity treatmentPrevious computational modelsCognitive resourcesPositive psychotic symptomsComputational underpinningsComputational mechanismsSocial interactionStrong social elementSensory informationPositive symptomsConceptual reviewClinical interventionsEarly psychosisSocial elementsCandidate mechanismPsychotic symptomsNeurobiologyPsychosisConceptual paperMultiple levels