2017
Machine Learning of Functional Magnetic Resonance Imaging Network Connectivity Predicts Substance Abuse Treatment Completion
Steele VR, Maurer JM, Arbabshirani MR, Claus ED, Fink BC, Rao V, Calhoun VD, Kiehl KA. Machine Learning of Functional Magnetic Resonance Imaging Network Connectivity Predicts Substance Abuse Treatment Completion. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2017, 3: 141-149. PMID: 29529409, PMCID: PMC5851466, DOI: 10.1016/j.bpsc.2017.07.003.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonanceSubstance abuse treatment programsAnterior cingulate cortexSubstance abuse treatmentSubstance abuse treatment completionCingulate cortexAbuse treatmentSubstance abuse treatment outcomesSubstance useTreatment programFNC analysisTreatment completionLong-term outcomesResponse inhibitionNeural network connectionsNetwork connectivity measuresClinical assessment measuresPositive outcomesSubstance abusersPattern classification modelAssessment measuresIllicit drug useIncarcerated participantsDepressive symptomatologyTreatment interventions
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