Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders
Steele VR, Rao V, Calhoun VD, Kiehl KA. Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders. NeuroImage 2015, 145: 265-273. PMID: 26690808, PMCID: PMC4903946, DOI: 10.1016/j.neuroimage.2015.12.013.Peer-Reviewed Original ResearchConceptsLow psychopathic traitsPsychopathic traitsPersonality traitsNeural measuresElevated psychopathic traitsHigh psychopathic traitsVoxel-based morphometry dataNon-incarcerated youthSupport vector machine (SVM) learning modelStructural magnetic resonance imagingNeural correlatesAdolescent offendersAdolescent participantsGroup membershipClinical groupsHealthy controlsParalimbic systemNuanced modelsPersonality disorderFuture behaviorIncarcerated individualsYouthPsychopathyMachine learning modelsLearning modelDysfunctional error-related processing in female psychopathy
Maurer JM, Steele VR, Edwards BG, Bernat EM, Calhoun VD, Kiehl KA. Dysfunctional error-related processing in female psychopathy. Social Cognitive And Affective Neuroscience 2015, 11: 1059-1068. PMID: 26060326, PMCID: PMC4927025, DOI: 10.1093/scan/nsv070.Peer-Reviewed Original ResearchConceptsPost-error processingError-related processingEvent-related potential componentERN/NeFemale psychopathsAdult female offendersHare Psychopathy ChecklistPotential gender differencesError monitoringCognitive domainsERP componentsNeural correlatesResponse inhibitionNoGo taskNeurocognitive studiesAffective deficitsPsychopathic traitsAffective dysfunctionMale psychopathsFemale psychopathyPsychopathy ChecklistPsychopathic personalityPCA measuresFemale offendersPotential components