Dr. Zilverstand is a psychologist and neuroimaging expert, faculty in the Department of Psychiatry and Behavioral Science and member of the Medical Discovery Team on Addiction. She leads an interdisciplinary team focused on investigating how individual differences contribute to human drug addiction. Her research group analyzes existing large-scale multimodal data sets, in addition to acquiring their own data by employing 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.
- Wang C, Song S, d'Oleire Uquillas F, Zilverstand A, Song H, Chen H, Zou Z. Altered brain network organization in romantic love as measured with resting-state fMRI and graph theory. Brain Imaging Behav. 2020 Jan 2. doi: 10.1007/s11682-019-00226-0.
- Zilverstand A, Goldstein RZ. Dual models of drug addiction: the impaired Response Inhibition and Salience Attribution (iRISA) model. In Verdejo-Garcia, A. (Ed.). Cognition and addiction: A Researcher’s Guide From Mechanisms Towards Interventions. Amsterdam, Netherlands: Elsevier, 2019.
- Song S, Zilverstand A, Gui W, Li HJ, Zhou X. Effects of single-session versus multi-session non-invasive brain stimulation on craving and consumption in individuals with substance dependence or eating disorders: A meta-analysis. Brain Stimul. 2019;12(3):606-618.
- Zilverstand A, Huang A, Goldstein R. Neuroimaging impaired response inhibition and salience attribution in human drug addiction. Neuron. 2018;98:886-903.
- Zilverstand A, O’Halloran R, Goldstein R. Resting-state and structural brain connectivity in individuals with stimulant addiction. In Pickard, H., Ahmed, S. (Eds.). The Routledge Handbook of Philosophy and Science of Addiction. New York, NY: Taylor & Francis, 2018.
- Moeller SJ, Zilverstand A, Konova AB, Kundu P, Parvaz MA, Preston-Campbell R, Bachi K, Alia-Klein N, Goldstein RZ. Neural correlates of drug-biased choice in currently-using and abstinent individuals with cocaine use disorder. Biol Psychiatry Cogn Neurosci Neuroimaging. 2018;3:485-494.
- Zilverstand, A., Sorger, B., Slaats-Willemse, D., Kan, C.C., Goebel, R., & Buitelaar, J.K. (2017). fMRI neurofeedback training for increasing anterior cingulate cortex activation in adult attention deficit hyperactivity disorder. An exploratory randomized, single-blinded study. PLoS One. 2017;12:e0170795.
- Zilverstand A, Parvaz MA, Goldstein RZ. Neuroimaging cognitive reappraisal in clinical populations to define neural targets for enhancing emotion regulation. A systematic review. Neuroimage 2017;151:105-116.
- Song S, Zilverstand A, Song H, d’Oleire Uquillas F, Wang Y, Xie C, Cheng L, Zou Z. The influence of emotional interference on cognitive control: A meta-analysis of neuroimaging studies using the emotional Stroop task. Sci Rep. 2017;7:2088.
- Zilverstand A, Parvaz MA, Moeller SJ, Goldstein RZ. Cognitive interventions for addiction medicine: Understanding the underlying neurobiological mechanisms. Prog Brain Res. 2016;224:285-304.
- Zilverstand A, Sorger B, Sarkheil P, Goebel R. fMRI neurofeedback facilitates anxiety regulation in females with spider phobia. Front Behav Neurosci. 2015;9:148.
- Sarkheil P., Zilverstand A, Schneider F, Goebel R, Mathiak K. fMRI neurofeedback enhances emotion regulation as evidenced by a reduced amygdala response. Behav Brain Res.2015;281:326-332.
- Zilverstand A, Sorger B, Zimmermann J, Kaas A, Goebel R. Windowed correlation: A suitable tool for providing dynamic fMRI-based functional connectivity neurofeedback on task difficulty. PLoS One. 2014;9(1): e85929.