2015
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 model
2013
Brain Potentials Measured During a Go/NoGo Task Predict Completion of Substance Abuse Treatment
Steele VR, Fink BC, Maurer JM, Arbabshirani MR, Wilber CH, Jaffe AJ, Sidz A, Pearlson GD, Calhoun VD, Clark VP, Kiehl KA. Brain Potentials Measured During a Go/NoGo Task Predict Completion of Substance Abuse Treatment. Biological Psychiatry 2013, 76: 75-83. PMID: 24238783, PMCID: PMC3984370, DOI: 10.1016/j.biopsych.2013.09.030.Peer-Reviewed Original ResearchConceptsEvent-related potentialsSubstance abuse treatmentAbuse treatmentResponse-locked event-related potentialsResponse-locked error-related negativityGo/NoGo taskERN/NeError-related negativityResponse inhibition taskDrug abuse relapseSubstance abuse treatment programsNeural measuresError positivityInhibition taskNoGo taskSmaller P2Sensory gatingSubstance abuseSubstance dependenceTreatment programLarge PeIncarcerated individualsParticipantsTaskTreatment completion