Anna Zilverstand
,
Credentials
PhD

Assistant Professor
Biography

Bio

I am a psychologist and neuroimaging expert, a faculty member in the Department of Psychiatry and Behavioral Science, and a member of the Medical Discovery Team on Addiction. I received my PhD from Maastricht University in the Netherlands, where I developed fMRI-based neurofeedback training protocols for three different clinical populations. During my postdoctoral training at Mount Sinai, New York, I focused on the potential for personalized medical treatments in human drug addiction, investigating novel approaches for individualized treatments in cocaine-addicted individuals.

My current work focuses on establishing the existence of neurobiological subtypes in different addicted human populations, with the goal of developing individualized brain-based and technology-supported treatments for human drug addiction. My research group combines the analysis of existing large-scale multimodal data sets with the acquisition of new data through a variety of techniques such as interviewing, neurocognitive testing, questionnaires, and multi-modal neuroimaging. Novel computational methods are employed for linking social, demographic, neurocognitive, personality, and clinical measures to the neuroimaging data, to explore the existence of neurobiological subtypes within the addicted population. The goal of this research is to develop a neuroscience-derived individualized treatment for individuals who are at risk for either escalation of drug use or relapse. Within the department, I am a member of the Grand Rounds Committee.

Expertise

  • Large-scale multimodal data sets
  • MRI
  • Human drug addiction treatment

Administrative Assistant

(for academic support only)
Shelly Slominski
slomi001@umn.edu

In the Media

Research Summary

Dr. Zilverstand's current work focuses on investigating how individual differences contribute to human drug addiction. Her research group combines the analysis of existing large-scale multimodal data sets with the acquisition of new data through a variety of techniques such as interviewing, neurocognitive testing, questionnaires and multi-modal neuroimaging. Novel computational methods are employed for linking social, demographic, neurocognitive, personality and clinical measures to the neuroimaging data, to explore the existence of neurobiological subtypes within the addicted population. The goal of this research is to develop neuroscience-derived individualized treatment for individuals who are at risk for either escalation of drug use or relapse.

Teaching Summary

Dr. Zilverstand is a faculty member of the Graduate Program in Neuroscience and provides training and supervision for neuroscience, psychology and psychiatry students, residents, and fellows in the University of Minnesota Medical School.

Clinical Summary

Dr. Zilverstand's clinical interests include addiction and other Impulse Control Disorders.

Education

MS, Maastricht University
Major: Cognitive Neuroscience
PhD, Maastricht University
Major: Cognitive Neuroscience
BS, Maastricht University
Major: Psychology

Fellowships, Residencies, and Visiting Engagements

Postdoctoral Appointments,
Mount Sinai, NY, USA

Honors and Recognition

Strategic Plan Poster, Society for Research in Child Development (SRCD)
Trainee Professional Development Award, Society for Neuroscience
Senior Level Travel Award, American College of Neuropsychopharmacology
Young Investigator Travel Award, Conference for Real-Time Functional Imaging and Neurofeedback

Professional Memberships

The College on Problems of Drug Dependence
Research Society on Alcoholism
Society for Neuroscience
Society for Biological Psychiatry
Organization for Human Brain Mapping

Languages

Dutch
French
German
Spanish
Selected Publications

Selected Publications

Konova, A.B., Zilverstand, A., 2023. Deriving generalizable and interpretable brain-behavior phenotypes of cannabis use. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 8 (3): 238-240.
doi: https://doi.org/10.1016/j.bpsc.2023.01.003 PubMed ID: 36889869.
Manea, A., Zilverstand, A., Ugurbil, K., Heilbronner, S., Zimmerman, J., 2022. Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain. eLife, 11 (e75540):
doi: https://doi.org/10.7554/elife.75540 PubMed ID: 35234612.
Song*, S., Zilverstand*, A., Gui, W., Pan, X., Zhou, X, 2022. Reducing craving and consumption in individuals with drug addiction, obesity, or overeating through neuromodulation intervention: A systemic review and meta-analysis of its follow-up effects. Addiction, 117 (5): 1242-1255.
doi: https://doi.org/10.1111/add.15686 PubMed ID: 34514666.
Niklason, G., Rawls, E., Ma, S., Kummerfeld, E., Maxwell, A.M., Brucar, L.R., Drossel, G., Zilverstand, A., 2022. Explainable Machine Learning Analysis Reveals Gender Differences in the Phenotypic and Neurobiological Markers of Cannabis Use Disorder. Scientific Reports, 12 (1): 15624.
doi: https://doi.org/10.1038/s41598-022-19804-2 PubMed ID: 36115920.
Maxwell, A.M., Harrison, K., Rawls, E., Zilverstand, A. , 2022. Gender differences in the psychosocial determinants underlying the onset and maintenance of Alcohol Use Disorder. Frontiers in Neuroscience, 16 808776.
doi: https://doi.org/10.3389/fnins.2022.808776 PubMed ID: 35360152.
Parvaz, M., Malaker, P., Zilverstand, A., Moeller, S., Alia-Klein, N., Goldstein, R., 2021. Attention bias modification in drug addiction: Enhancing control of subsequent habits. Proceedings of the National Academy of Sciences, 118 (23): e2012941118.
doi: https://doi.org/10.1073/pnas.2012941118 PubMed ID: 34074751.
Yacoub, E., Grier, M., Auerbach, E., Lagore, R., Harel, N., Adriany, G., Zilverstand, A., Hayden, B., Heilbronner, S., Ugurbil, K., Zimmerman, J, 2020. Ultra-high field (10.5 T) resting state fMRI in the macaque. Neuroimage, 223 (117349):
Wang, C., Song, S., d’Oleire Uquillas, F., Zilverstand, A., Song, H., Chen, H., Zou, Z., 2020. Altered brain network organization in romantic love as measured with resting-state fMRI and graph theory.. Brain Imaging and Behavior, 14 (6): 2771-2784.
doi: https://doi.org/10.1007/s11682-019-00226-0 PubMed ID: 31898089.
Zilverstand, A., et al., 2019. A roadmap for integrating neuroscience into addiction treatment: A consensus of the neuroscience interest group of the international society of addiction medicine. Frontiers in Psychiatry, 10 877.
doi: https://doi.org/10.3389/fpsyt.2019.00877 PubMed ID: 31920740.
Colicino, E., Hazeltine, D., Schneider, K., Zilverstand, A., Bachi, K., Alia-Klein, N., Goldstein, R., Todd, A., Horton, M., 2019. Cocaine addiction severity exacerbates the negative association of lifetime lead exposure with blood pressure levels: Evidence from a pilot study. Environmental Disease , 4 (3): 75-80.
doi: https://doi.org/10.4103/ed.ed_21_19 PubMed ID: 33490759.
Selected Presentations

Selected Presentations

Zilverstand, A. K. "Computational Approaches for Understanding Drug Addiction", Yale University - Division of Addiction, New Haven, Connecticut, May 03, 2023.
Zilverstand, A. K. "Computational Approaches for Understanding Drug Addiction", Bethesda, Maryland, April 21, 2023.
Zilverstand, A. K. "Computational Approaches for Understanding Drug Addiction", International Symposium on Addiction Research, Queretaro, Mexico, March 01, 2023.
Zilverstand, A. K. "Computational Approaches for Understanding Drug Addiction", Healthy Brain and Mind Research Center, Australian Catholic University, Melbourne, Australia, November 02, 2022.
Zilverstand, A. K. "Data-mining of public data sets for understanding the complex factors underlying human drug addiction", New York State Psychiatric Institute at Columbia University, New York, New York, July 28, 2022.
Zilverstand, A. "Subtypes in Addiction and their Neurobehavioral Impairments in Approach Behavior, Negative Emotionality and Executive Function", Research Society on Alcoholism (RSA) Scientific Meeting, Orlando, Florida, June 27, 2022.
Gunner, D., Zilverstand, A. "Subtypes in Individuals with Current Cocaine Use Disorder and their Impairments in Negative Emotionality and Executive Function", Annual Scientific Meeting of the College on Problems of Drug Dependence (CPDD), Minneapolis, Minnesota, June 15, 2022.
Niklason, G., Zilverstand, A. "Family, neighborhood and individual factors linked to early sipping as identified by machine learning analysis", Annual Scientific Meeting of the College on Problems of Drug Dependence (CPDD), College on Problems of Drug Dependence (CPDD), Minneapolis, Minnesota, June 13, 2022.
Zilverstand, A. "An Empirically Derived Neurobehavioral Three-domain Model Underlying Addiction-general Subtypes: Implications for Personalized Addiction Medicine", Annual Scientific Meeting of the College on Problems of Drug Dependence (CPDD), Minneapolis, Minnesota, June 12, 2022.
Zilverstand, A. "Meta-Analytical Evidence for the Short- and Long-Term Efficacy of Neuromodulation of the Dorsolateral Prefrontal Cortex in Drug Addiction and Excessive Eating", Annual Meeting Society of Biological Psychiatry, Society of Biological Psychiatry (SOBP), New Orleans, Louisiana, April 29, 2022.
Contact

Contact

Address

Department of Psychiatry & Behavioral Sciences, F282/2A West Building, 2450 Riverside Avenue South, Minneapolis, MN 55454