2020
Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience
Gold JM, Corlett PR, Strauss GP, Schiffman J, Ellman LM, Walker EF, Powers AR, Woods SW, Waltz JA, Silverstein SM, Mittal VA. Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience. Schizophrenia Bulletin 2020, 46: 1346-1352. PMID: 32648913, PMCID: PMC7707066, DOI: 10.1093/schbul/sbaa091.Peer-Reviewed Original ResearchConceptsClinical high riskComputational cognitive neuroscienceNew behavioral measureCognitive neuroscienceBehavioral measuresPsychosis risk predictionCognitive mechanismsTrait vulnerabilityDisorganization symptomsNeural systemsPsychosis symptomsPsychosis riskSpecialized interviewsPhenotype measuresNeuroscienceCHR assessmentTreatment targetsPsychotic disordersCourse of illnessInterview methodPsychosisNew treatment targetsIllness progressionPositive predictive valueMeasures
2016
Hallucinations as Top-Down Effects on Perception
Powers AR, Kelley M, Corlett PR. Hallucinations as Top-Down Effects on Perception. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2016, 1: 393-400. PMID: 28626813, PMCID: PMC5469545, DOI: 10.1016/j.bpsc.2016.04.003.Peer-Reviewed Original ResearchContemporary cognitive neuroscienceCognitive science communityHigh-level cognitionPredictive coding modelHierarchical brain networksCognitive penetrationPerceptual priorsCognitive neurosciencePerceptual processesCognitive neuropsychiatryComputational neuroimagingModular viewMental organizationCoding modelBrain networksPerceptionMental illnessHierarchical modelCognitionNeuroscienceStimuliNeuroimagingHallucinationsNeuropsychiatryFindings