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
2014
A large scale (N=102) functional neuroimaging study of error processing in a Go/NoGo task
Steele VR, Claus ED, Aharoni E, Harenski C, Calhoun VD, Pearlson G, Kiehl KA. A large scale (N=102) functional neuroimaging study of error processing in a Go/NoGo task. Behavioural Brain Research 2014, 268: 127-138. PMID: 24726752, PMCID: PMC4095785, DOI: 10.1016/j.bbr.2014.04.001.Peer-Reviewed Original ResearchConceptsGo/NoGo taskError processingNoGo taskResponse inhibitionFunctional magnetic resonance imaging studyBilateral inferior frontal gyrusInferior frontal gyrusLateral prefrontal areasPresent fMRI resultsMagnetic resonance imaging studyResonance imaging studyNeural correlatesFMRI resultsFrontal gyrusPrefrontal areasAnterior cingulateNeural systemsHealthy participantsTaskLarge sampleProcessingImaging studiesPrimary purposeCingulateGyrus