Vaughn R Steele, PhD
Assistant Professor of Psychiatry; Division of Addiction Sciences, Yale Department of Psychiatry
Research & Publications
Biography
News
Coauthors
Selected Publications
- Parameter space in optimization of NIBS in addictionSteele V. Parameter space in optimization of NIBS in addiction Brain Stimulation 2023, 16: 140. DOI: 10.1016/j.brs.2023.01.082.
- Characterizing Impulsivity in Individuals with Heroin Use DisorderKang T, Zhang Y, Zhao J, Li X, Jiang H, Niu X, Xie R, Ding X, Steele V, Yuan T. Characterizing Impulsivity in Individuals with Heroin Use Disorder International Journal Of Mental Health And Addiction 2022, 1-16. DOI: 10.1007/s11469-022-00941-8.
- How an Exemplar of Chronic Neuromodulation for Cocaine Use Disorder is a Path Forward for Treating Substance Use DisordersSteele V. How an Exemplar of Chronic Neuromodulation for Cocaine Use Disorder is a Path Forward for Treating Substance Use Disorders Biological Psychiatry 2022, 91: s37. DOI: 10.1016/j.biopsych.2022.02.110.
- Response Inhibition Circuit Dysregulation in Substance Use Disorders Identified With Event-Related Potential-Derived Functional ConnectivitySteele V, Tootell A, Butler D, Fix S, Stevens M, Pearlson G, Bernat E. Response Inhibition Circuit Dysregulation in Substance Use Disorders Identified With Event-Related Potential-Derived Functional Connectivity Biological Psychiatry 2021, 89: s350. DOI: 10.1016/j.biopsych.2021.02.873.
- Accelerated Intermittent Theta-Burst Stimulation as a Treatment for Cocaine Use Disorder: A Proof-of-Concept StudySteele VR, Maxwell AM, Ross TJ, Stein EA, Salmeron BJ. Accelerated Intermittent Theta-Burst Stimulation as a Treatment for Cocaine Use Disorder: A Proof-of-Concept Study Frontiers In Neuroscience 2019, 13: 1147. PMID: 31736689, PMCID: PMC6831547, DOI: 10.3389/fnins.2019.01147.
- Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road aheadEkhtiari H, Tavakoli H, Addolorato G, Baeken C, Bonci A, Campanella S, Castelo-Branco L, Challet-Bouju G, Clark VP, Claus E, Dannon PN, Del Felice A, den Uyl T, Diana M, di Giannantonio M, Fedota JR, Fitzgerald P, Gallimberti L, Grall-Bronnec M, Herremans SC, Herrmann MJ, Jamil A, Khedr E, Kouimtsidis C, Kozak K, Krupitsky E, Lamm C, Lechner WV, Madeo G, Malmir N, Martinotti G, McDonald W, Montemitro C, Nakamura-Palacios EM, Nasehi M, Noël X, Nosratabadi M, Paulus M, Pettorruso M, Pradhan B, Praharaj SK, Rafferty H, Sahlem G, Salmeron BJ, Sauvaget A, Schluter RS, Sergiou C, Shahbabaie A, Sheffer C, Spagnolo PA, Steele VR, Yuan TF, van Dongen J, Van Waes V, Venkatasubramanian G, Verdejo-García A, Verveer I, Welsh J, Wesley MJ, Witkiewitz K, Yavari F, Zarrindast MR, Zawertailo L, Zhang X, Cha YH, George TP, Frohlich F, Goudriaan AE, Fecteau S, Daughters SB, Stein EA, Fregni F, Nitsche MA, Zangen A, Bikson M, Hanlon CA. Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road ahead Neuroscience & Biobehavioral Reviews 2019, 104: 118-140. PMID: 31271802, PMCID: PMC7293143, DOI: 10.1016/j.neubiorev.2019.06.007.
- 115. Developing Treatment Targets for Substance Use Disorders With Machine Learning ClassifiersSteele V. 115. Developing Treatment Targets for Substance Use Disorders With Machine Learning Classifiers Biological Psychiatry 2019, 85: s48. DOI: 10.1016/j.biopsych.2019.03.129.
- Addiction: Informing drug abuse interventions with brain networks.Steele, V. R., Ding, X., & Ross, T. J. (2019). Addiction: Informing drug abuse interventions with brain networks. In B.C. Munsell, G. Wu, L. Bonilha, & P.J. Laurienti (Ed.) Connectomics: Applications to Neuroimaging (pp. 101-123). Elsevier.
- Chapter 6 Addiction: Informing drug abuse interventions with brain networksSteele V, Ding X, Ross T. Chapter 6 Addiction: Informing drug abuse interventions with brain networks 2019, 101-122. DOI: 10.1016/b978-0-12-813838-0.00006-6.
- Reward Circuitry and Drug AddictionSteele, V. R., Pariyadath, V., Goldstein, R. Z., & Stein, E. A. (2018). Reward Circuitry and Drug Addiction. In D.S. Charney, P. Sklar, J.D. Buxbaum, & E. J. Nestler (Ed.) Neurobiology of Mental Illness (pp. 587-600). Oxford University Press.
- Machine Learning of Functional Magnetic Resonance Imaging Network Connectivity Predicts Substance Abuse Treatment CompletionSteele 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.
- Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imagingSteele VR, Anderson NE, Claus ED, Bernat EM, Rao V, Assaf M, Pearlson GD, Calhoun VD, Kiehl KA. Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging NeuroImage 2016, 132: 247-260. PMID: 26908319, PMCID: PMC4860744, DOI: 10.1016/j.neuroimage.2016.02.046.
- Error-Related Processing in Adult Males With Elevated Psychopathic TraitsSteele VR, Maurer JM, Bernat EM, Calhoun VD, Kiehl KA. Error-Related Processing in Adult Males With Elevated Psychopathic Traits Personality Disorders Theory Research And Treatment 2016, 7: 80-90. PMID: 26479259, PMCID: PMC4710563, DOI: 10.1037/per0000143.
- Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offendersSteele 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.
- Multimodal imaging measures predict rearrestSteele VR, Claus ED, Aharoni E, Vincent GM, Calhoun VD, Kiehl KA. Multimodal imaging measures predict rearrest Frontiers In Human Neuroscience 2015, 9: 425. PMID: 26283947, PMCID: PMC4522570, DOI: 10.3389/fnhum.2015.00425.
- Dysfunctional error-related processing in female psychopathyMaurer 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.
- Psychopathy, attention, and oddball target detection: New insights from PCL‐R facet scoresAnderson NE, Steele VR, Maurer JM, Bernat EM, Kiehl KA. Psychopathy, attention, and oddball target detection: New insights from PCL‐R facet scores Psychophysiology 2015, 52: 1194-1204. PMID: 25912522, PMCID: PMC5648055, DOI: 10.1111/psyp.12441.
- A large scale (N=102) functional neuroimaging study of error processing in a Go/NoGo taskSteele 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.
- Brain Potentials Measured During a Go/NoGo Task Predict Completion of Substance Abuse TreatmentSteele 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.
- A large scale (N=102) functional neuroimaging study of response inhibition in a Go/NoGo taskSteele VR, Aharoni E, Munro GE, Calhoun VD, Nyalakanti P, Stevens MC, Pearlson G, Kiehl KA. A large scale (N=102) functional neuroimaging study of response inhibition in a Go/NoGo task Behavioural Brain Research 2013, 256: 529-536. PMID: 23756137, PMCID: PMC4437665, DOI: 10.1016/j.bbr.2013.06.001.
- Separable processes before, during, and after the N400 elicited by previously inferred and new information: Evidence from time–frequency decompositionsSteele VR, Bernat EM, van den Broek P, Collins PF, Patrick CJ, Marsolek CJ. Separable processes before, during, and after the N400 elicited by previously inferred and new information: Evidence from time–frequency decompositions Brain Research 2012, 1492: 92-107. PMID: 23165117, PMCID: PMC3534777, DOI: 10.1016/j.brainres.2012.11.016.
- Reversing presentation order of semantically related words reverses memoryWesterberg C, Steele V, Marsolek C. Reversing presentation order of semantically related words reverses memory Journal Of Cognitive Psychology 2008, 20: 69-90. DOI: 10.1080/09541440701237872.