Tyrone Cannon
Clark L. Hull Professor of Psychology and Professor of PsychiatryCards
About
Research
Publications
2025
Psychosis-proneness is associated with reduced cognitive error-monitoring during instrumental learning
Zhao W, McDougle S, Cannon T. Psychosis-proneness is associated with reduced cognitive error-monitoring during instrumental learning. Schizophrenia Research Cognition 2025, 43: 100408. PMID: 41438020, PMCID: PMC12719759, DOI: 10.1016/j.scog.2025.100408.Peer-Reviewed Original ResearchPost-error slowingPsychosis-pronenessError monitoringPositive schizotypyWorking memoryInstrumental learningMultidimensional Schizotypy Scale-BriefLearning tasksExecutive function deficitsInstrumental learning taskImpaired error monitoringReinforcement learning taskCognitive inflexibilityBelief inflexibilityWM loadWM capacityWM limitationsCognitive profilePost-errorSchizotypyFunctional deficitsVisuomotorBriefInflexibilityPerformance monitoringTheta Oscillations Assessed from a Passive Auditory Oddball Paradigm in Individuals at Clinical High-Risk for Psychosis and Healthy Controls: Associations with Clinical Outcomes and Mismatch Negativity
Hua J, Roach B, Hamilton H, Bachman P, Belger A, Carrión R, Duncan E, Johannesen J, Light G, Niznikiewicz M, Addington J, Bearden C, Cadenhead K, Perkins D, Stone W, Walker E, Woods S, Cannon T, Mathalon D. Theta Oscillations Assessed from a Passive Auditory Oddball Paradigm in Individuals at Clinical High-Risk for Psychosis and Healthy Controls: Associations with Clinical Outcomes and Mismatch Negativity. Biological Psychiatry Global Open Science 2025, 100664. DOI: 10.1016/j.bpsgos.2025.100664.Peer-Reviewed Original ResearchCHR-CInter-trial phase coherenceAuditory oddball paradigmHealthy controlsClinical high riskCHR-PMismatch negativityCHR-NCNorth American Prodrome Longitudinal Study 2High riskTheta oscillationsClinical outcomesGeneration of theta oscillationsAssociated with clinical outcomesMismatch negativity deficitsOddball paradigmPsychosis conversionMismatch negativity amplitudeCHR-P samplesEvent-related oscillationsCHR-P individualsPassive auditory oddball paradigmFollow-upSchizophrenia biomarkersStandard tonesNeighborhood Characteristics and Social Functioning: Exploring Shared and Distinct Psychosocial Pathways Among Individuals at Clinical High-Risk for Psychosis
Yuan Q, Feurer C, Zhou Q, Carrion R, Addington J, Bearden C, Cadenhead K, Cannon T, Cornblatt B, Keshavan M, Mathalon D, Perkins D, Stone W, Woods S, Walker E, Ku B. Neighborhood Characteristics and Social Functioning: Exploring Shared and Distinct Psychosocial Pathways Among Individuals at Clinical High-Risk for Psychosis. Schizophrenia Bulletin 2025, sbaf192. PMID: 41212179, DOI: 10.1093/schbul/sbaf192.Peer-Reviewed Original ResearchNeighborhood socioeconomic deprivationNeighbourhood social fragmentationSocioeconomic deprivationNeighborhood characteristicsAssociated with social functioningContextual risk factorsSocial functioningHigh riskStudy phase 3Impaired social functioningRisk factorsCHR-PSocial fragmentationClinical high riskParticipant's addressGlobal assessmentCHR-P individualsPsychosocial pathwaysGlobal Assessment of FunctioningAssessment of functioningEffective interventionsStructural assessmentStructured Assessment of Violence RiskEnvironmental factorsAssessment of Violence RiskShift in sex and age of individuals at a clinical high risk (CHR) for psychosis: relation to differences in recruitment methods and effect on sample characteristics
Farina E, Mourgues-Codern C, Stimler K, Kenney J, Saxena A, Mukhtar H, Addington J, Bearden C, Cadenhead K, Cannon T, Cornblatt B, Ellman L, Gold J, Keshavan M, Mathalon D, Mittal V, Perkins D, Schiffman J, Silverstein S, Strauss G, Stone W, Walker E, Waltz J, Corlett P, Powers A, Woods S. Shift in sex and age of individuals at a clinical high risk (CHR) for psychosis: relation to differences in recruitment methods and effect on sample characteristics. Schizophrenia 2025, 11: 123. PMID: 41053030, PMCID: PMC12501016, DOI: 10.1038/s41537-025-00663-5.Peer-Reviewed Original ResearchClinical high riskClinical high-risk samplesNorth American Prodrome Longitudinal StudyOvert psychotic disordersSample characteristicsSample of individualsNegative symptomsPsychotic disordersPsychosis riskSelf-referralRecruitment sourcesBetween-study differencesComputerized assessmentHierarchical regressionPsychosisRecruitment source effectsClinical implicationsLongitudinal studyGeneral symptomsDemographic differencesClinical profileSymptomsParticipantsClinical heterogeneitySex2.67 Long-Term Outcomes of Youth at Clinical High-Risk for Psychosis: Does Lifetime Substance Use Play a Role?
Bianchi S, Addington J, Bearden C, Cannon T, Carrión R, Keshavan M, Mathalon D, Perkins D, Stone W, Walker E, Woods S, Cadenhead K. 2.67 Long-Term Outcomes of Youth at Clinical High-Risk for Psychosis: Does Lifetime Substance Use Play a Role? Journal Of The American Academy Of Child And Adolescent Psychiatry 2025, 64: s214. DOI: 10.1016/j.jaac.2025.08.187.Peer-Reviewed Original ResearchPredictors and Moderators of Long-Term Outcome of Persons at Clinical High Risk for Psychosis: Methods and Preliminary Data
Cadenhead K, Kennedy L, Mirzakhanian H, Addington J, Bearden C, Cannon T, Carrión R, Keshavan M, Mathalon D, Perkins D, Stone W, Walker E, Woods S. Predictors and Moderators of Long-Term Outcome of Persons at Clinical High Risk for Psychosis: Methods and Preliminary Data. Schizophrenia Bulletin 2025, sbaf133. PMID: 40856400, DOI: 10.1093/schbul/sbaf133.Peer-Reviewed Original ResearchClinical high riskClinical high-risk criteriaLong-term outcomesNorth American Prodrome Longitudinal Study sitesClinical high-risk participantsRates of affective disordersHigh riskLife courseNon-converter groupHigh-risk youthAssessment of individualsPsychosis statesAffective disordersPsychosocial functioningPsychosisTrajectory of diagnosisLonger-term outcomesClinical/functional outcomesLong-term assessmentGeneral populationBaseline dataParticipantsPreliminary dataEarly dataPersonsDecoding Psychosis Risk: Neuroanatomical Correlates of the NAPLS-2 Calculator in the PRONIA Cohort
Neuner L, Weyer C, Kambeitz-Ilankovic L, Korda A, Dwyer D, Antonucci L, Kambeitz J, Upthegrove R, Salokangas R, Hietala J, Pantelis C, Lencer R, Wood S, Brambilla P, Borgwardt S, Bertolino A, Romer G, Meisenzahl E, Dannlowski U, Falkai P, Cannon T, Koutsouleris N, Hahn L, Haas S, Hasan A, Hoff C, Khanyaree I, Krämer C, Melo A, Muckenhuber-Sternbauer S, Köhler Y, Oeztuerk O, Penzel N, Popovic D, Rangnick A, von Saldern S, Sanfelici R, Spangemacher M, Tupac A, Fernanda Urquijo M, Weiske J, Wosgien A, Blume K, Hedderich D, Julkowski D, Kaiser N, Lichtenstein T, Milz R, Nikolaides A, Pilgram T, Seves M, Wassen M, Andreou C, Egloff L, Harrisberger F, Heitz U, Lenz C, Leanza L, Mackintosh A, Smieskova R, Studerus E, Walter A, Widmayer S, Day C, Lowri Griffiths S, Iqbal M, Pelton M, Mallikarjun P, Stainton A, Lin A, Denissoff A, Ellilä A, From T, Heinimaa M, Ilonen T, Jalo P, Laurikainen H, Luutonen A, Mäkela A, Paju J, Pesonen H, Säilä R, Toivonen A, Turtonen O, Botterweck S, Kluthausen N, Antoch G, Caspers J, Wittsack H, Blasi G, Pergola G, Caforio G, Fazio L, Quarto T, Gelao B, Romano R, Andriola I, Falsetti A, Barone M, Passiatore R, Sangiuliano M, Surmann M, Bienek O, Beatriz Solana A, Abraham M, Schirmer T, Altamura C, Belleri M, Bottinelli F, Ferro A, Re M, Monzani E, Sberna M, D’Agostino A, Del Fabro L, Perna G, Nobile M, Alciati A, Balestrieri M, Bonivento C, Cabras G, Fabbro F, Garzitto M, Piccin S. Decoding Psychosis Risk: Neuroanatomical Correlates of the NAPLS-2 Calculator in the PRONIA Cohort. Schizophrenia Bulletin 2025, sbaf135. PMID: 40856416, DOI: 10.1093/schbul/sbaf135.Peer-Reviewed Original ResearchGray matter volumeWhite matter volumeNeuroanatomical correlatesPsychosis riskMatter volumeCHR-PNAPLS-2Moderation analysisNorth American Prodrome Longitudinal StudyClinical high-risk stateHippocampal gray matter volumeEarly Psychosis ManagementAnterior cingulate cortexCerebellar white matter volumeVoxel-based morphometryRecent-onset depressionLongitudinal studyRisk scoreHigh-risk statePsychosis managementDiagnostic boundariesPost-hocVerbal memoryCingulate cortexPsychosocial deficitsPrediction of antipsychotic medication inception in antipsychotic-naive youth at clinical high risk for psychosis
Mukhtar H, Zhou D, Farina E, Saxena A, Cahill J, Addington J, Bearden C, Cadenhead K, Cannon T, Cornblatt B, Keshwan M, Mathalon D, Perkins D, Stone W, Cho Y, Powers A, Walker E, Woods S. Prediction of antipsychotic medication inception in antipsychotic-naive youth at clinical high risk for psychosis. Psychological Medicine 2025, 55: e241. PMID: 40842369, PMCID: PMC12404330, DOI: 10.1017/s0033291725101372.BooksClinical high riskCHR-PLifetime historyAugmentation of antidepressant treatmentComorbid major depressionAP useAntidepressant treatmentPositive symptomsMajor depressionAP medicationNAPLS-2Independent predictorsCHR-P.High riskBaseline clinical variablesPsychosisBaseline predictorsClinical variablesParticipantsBaseline characteristicsUnivariate analysisLogistic regression modelsObservational cohortMultivariate analysisAP initiationVictimization and engagement with the legal system among individuals at clinical high risk (CHR) for psychosis
Du A, Kennedy L, Addington J, Bearden C, Cannon T, Carrion R, Keshavan M, Mathalon D, Perkins D, Stone W, Walker E, Woods S, Cadenhead K. Victimization and engagement with the legal system among individuals at clinical high risk (CHR) for psychosis. Schizophrenia Research 2025, 284: 7-15. PMID: 40737766, DOI: 10.1016/j.schres.2025.07.015.Peer-Reviewed Original ResearchLegal systemLegal historyPerpetrators of crimesVictims of crimeHistory of victimizationClinical high-risk youthClinical high riskHistorical risk factorsReport victimizationLegal issuesVictimsCrimeComorbid mental illnessMental illnessYouthClinical high-risk participantsPsychotic illnessLife risk factorsPsychosis symptomsPerpetratorsViolencePsychosisHealthy controlsStudy-3EngagementThe moderating role of lifetime social engagement on the relationship between C-reactive protein and negative symptoms among young adults at clinical high risk for psychosis
Goldsmith D, Yuan Q, Addington J, Bearden C, Cadenhead K, Cannon T, Carrión R, Keshavan M, Mathalon D, Perkins D, Stone W, Tsuang M, Woods S, Walker E, Ku B. The moderating role of lifetime social engagement on the relationship between C-reactive protein and negative symptoms among young adults at clinical high risk for psychosis. Brain Behavior And Immunity 2025, 129: 890-897. PMID: 40730261, PMCID: PMC12360851, DOI: 10.1016/j.bbi.2025.07.023.Peer-Reviewed Original ResearchConceptsScale of Psychosis-risk SymptomsNegative symptomsCHR-P groupClinical high riskCHR-PC-reactive proteinAssociated with negative symptomsNorth American Prodrome Longitudinal StudySocial engagementDevelopment of negative symptomsPsychosis-risk symptomsSimple slope analysesCHR-P individualsYoung adultsHealthy controlsCHR-P subjectsLevels of social engagementSocial engagement levelsEarly developmental periodDepressive symptomsSimple slopesHC subjectsPsychosisHigh riskC-reactive protein values