2025
Delineating Empirically Plausible Causal Pathways to Suicidality Among People at Clinical High Risk for Psychosis
Bronstein M, Kummerfeld E, Bearden C, Cornblatt B, Walker E, Woods S, Mathalon D, Perkins D, Cadenhead K, Addington J, Cannon T, Vinogradov S. Delineating Empirically Plausible Causal Pathways to Suicidality Among People at Clinical High Risk for Psychosis. Journal Of Psychopathology And Clinical Science 2025, 134: 239-250. PMID: 39913476, DOI: 10.1037/abn0000969.Peer-Reviewed Original ResearchConceptsClinical high riskNorth American Prodrome Longitudinal StudyClinical high-risk samplesAttenuated psychosis symptomsPathways to suicideSuicide risk reductionPsychosis symptomsCausal pathwaysDepressed moodPsychosisIntervention effortsSelf-deprecationSuicideLongitudinal studyMeasurement time pointsStudy timepointsHigh riskSymptomsInterventionHopelessnessMoodTime pointsDepressionIndividualsDirect causesConnectome-based predictive modeling of early and chronic psychosis symptoms
Foster M, Ye J, Powers A, Dvornek N, Scheinost D. Connectome-based predictive modeling of early and chronic psychosis symptoms. Neuropsychopharmacology 2025, 1-9. PMID: 40016363, DOI: 10.1038/s41386-025-02064-9.Peer-Reviewed Original ResearchConnectome-based predictive modelingPositive and Negative Syndrome ScalePsychosis symptomsSymptom networksSymptom severityBrain networksNeural correlates of CPResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingNegative Syndrome ScaleIdentified group differencesPredicted effect sizeCorrelates of CPGeneral psychopathologyNegative symptomsPositive symptomsSyndrome ScaleFrontoparietal networkNeural correlatesVirtual lesion analysisGroup differencesConnectivity changesEffect sizeLesion analysisLongitudinal studyDeep multimodal representations and classification of first-episode psychosis via live face processing
Singh R, Zhang Y, Bhaskar D, Srihari V, Tek C, Zhang X, Noah J, Krishnaswamy S, Hirsch J. Deep multimodal representations and classification of first-episode psychosis via live face processing. Frontiers In Psychiatry 2025, 16: 1518762. PMID: 40134976, PMCID: PMC11934110, DOI: 10.3389/fpsyt.2025.1518762.Peer-Reviewed Original ResearchFirst-episode psychosisPositive and Negative Syndrome ScaleFunctional near-infrared spectroscopyGlobal Assessment of FunctioningEarly psychosisNeural correlates of social cognitionFirst-episode psychosis individualsNegative Syndrome ScaleBehavior recordsAssessment of FunctioningSevere psychiatric disordersSyndrome ScaleFace processingPsychosis symptomsNeural underpinningsSocial cognitionNeural correlatesPsychiatric disordersBrain activitySocial difficultiesNeurophysiological dysfunctionPsychosisNeural characteristicsMultimodal representationsAcquisition paradigm
2024
Unique Functional Neuroimaging Signatures of Genetic Versus Clinical High Risk for Psychosis
Schleifer C, Chang S, Amir C, O'Hora K, Fung H, Kang J, Kushan-Wells L, Daly E, Di Fabio F, Frascarelli M, Gudbrandsen M, Kates W, Murphy D, Addington J, Anticevic A, Cadenhead K, Cannon T, Cornblatt B, Keshavan M, Mathalon D, Perkins D, Stone W, Walker E, Woods S, Uddin L, Kumar K, Hoftman G, Bearden C. Unique Functional Neuroimaging Signatures of Genetic Versus Clinical High Risk for Psychosis. Biological Psychiatry 2024, 97: 178-187. PMID: 39181389, DOI: 10.1016/j.biopsych.2024.08.010.Peer-Reviewed Original ResearchBrain signal variabilityClinical high riskCHR individualsTD controlsSubthreshold psychosis symptomsResting-state functional MRIFunctional brain alterationsAssociated with psychosisFunctional brain measuresGroup difference mapCopy number variantsCase-control differencesPsychosis symptomsNeural substratesBrain alterationsBrain measuresLocal connectivityFunctional MRIFunctional connectivityCortical regionsNeuroimaging signaturesNeurodevelopmental disordersPsychosisHigh riskBrain mappingApplication of hyperalignment to resting state data in individuals with psychosis reveals systematic changes in functional networks and identifies distinct clinical subgroups
Anderson Z, Turner J, Ashar Y, Calhoun V, Mittal V. Application of hyperalignment to resting state data in individuals with psychosis reveals systematic changes in functional networks and identifies distinct clinical subgroups. Aperture Neuro 2024, 4 DOI: 10.52294/001c.91992.Peer-Reviewed Original ResearchFrontal connectivityPsychosis groupBaseline connectivityResting state functional connectivityPatterns of neural activitySubgroups of psychosisBrain-based biomarkersSample of individualsResting state dataBrain dataFollow-up analysisPsychosis symptomsFrontal cortexIndividual differencesFunctional connectivityPsychosisClinical populationsDiagnostic categoriesNeural activityClinical subpopulationsNetwork topographyClinically relevant differencesFunctional networksRelated disordersHealthy controls
2023
The reliability and validity of the revised Green et al. paranoid thoughts scale in individuals at clinical high‐risk for psychosis
Williams T, Walker E, Strauss G, Woods S, Powers A, Corlett P, Schiffman J, Waltz J, Gold J, Silverstein S, Ellman L, Zinbarg R, Mittal V. The reliability and validity of the revised Green et al. paranoid thoughts scale in individuals at clinical high‐risk for psychosis. Acta Psychiatrica Scandinavica 2023, 147: 623-633. PMID: 36905387, PMCID: PMC10463775, DOI: 10.1111/acps.13545.Peer-Reviewed Original ResearchConceptsCHR individualsClinical controlFull psychosisHealthy controlsGeneral populationPsychosis symptomsCHR participantsPoor social functioningGreen Paranoid Thoughts ScalePsychosisGroup differencesSocial functioningConfirmatory factor analysisParanoid Thoughts ScaleInterview measuresSeverity continuumTwo-factor structureCritical populationSelf-report measuresPresent studyDiscriminant validityPsychometric indicesParanoid thoughtsIndividualsParticipants
2022
Three prominent self-report risk measures show unique and overlapping utility in characterizing those at clinical high-risk for psychosis
Williams TF, Powers AR, Ellman LM, Corlett PR, Strauss GP, Schiffman J, Waltz JA, Silverstein SM, Woods SW, Walker EF, Gold JM, Mittal VA. Three prominent self-report risk measures show unique and overlapping utility in characterizing those at clinical high-risk for psychosis. Schizophrenia Research 2022, 244: 58-65. PMID: 35597134, PMCID: PMC9829103, DOI: 10.1016/j.schres.2022.05.006.Peer-Reviewed Original ResearchConceptsProdromal Questionnaire-BriefPositive symptomsSelf-report questionnairesSpecific positive symptomsStructured Clinical InterviewClinical high riskCriterion validityHealthy controlsSpecific symptomsHigh riskDiscriminant validityPsychosis symptomsClinical InterviewCHR individualsStrong convergent validitySymptomsPsychosis riskNeuropsychological testsConsistent significant correlationLimited specificitySignificant correlationConvergent validityPsychosisConstruct validityQuestionnaireTiming of cannabis exposure relative to prodrome and psychosis onset in a community-based first episode psychosis sample
Kline ER, Ferrara M, Li F, D'Souza DC, Keshavan M, Srihari VH. Timing of cannabis exposure relative to prodrome and psychosis onset in a community-based first episode psychosis sample. Journal Of Psychiatric Research 2022, 147: 248-253. PMID: 35066293, PMCID: PMC8882157, DOI: 10.1016/j.jpsychires.2022.01.039.Peer-Reviewed Original ResearchConceptsCannabis exposurePublic health significancePsychosis onsetPsychotic disordersHealth significanceFirst-episode psychosis samplePsychosis sampleFirst exposureFirst-episode psychosis servicesWorse premorbid functioningAdverse prognostic factorAssociation of ageImpact of cannabisPsychosis PreventionSymptom onsetPrognostic factorsOverall incidenceEarly psychosis sampleConsecutive admissionsOverall burdenPsychotic illnessPsychosis servicesPsychosis symptomsGreater severityYounger age
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
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