At the core of drug addiction is impairment in the brain's reward system where hypersensitivity to drug- related stimuli comes at the expense of insufficient salience attributed to all other non-drug-related reinforcers. This hypersensitivity t drug-related stimuli renders individuals with cocaine use disorder (CUD) particularly vulnerable to craving (and drug use), especially when presented with drug-related cues. Nevertheless, when instructed to volitionally inhibit cue-induced craving in a laboratory environment, some CUD reported lower craving and showed decreased activity in the brain regions that process the motivational value of rewards including drug-related cues (orbitofrontal cortex), thereby retaining some level of control over their drug- related cue reactivity. We propose to capitalize on this willed control of craving, using electroencephalogram (EEG) and subsequently ascertained event-related potentials (ERP) techniques, coupled with a Brain- Computer Interface (BCI) based real-time feedback system, to help bolster such cognitive control in drug addiction. In the current proposal, we aim to test the hypothesis that, when asked to volitionally reappraise drug stimuli, CUD will be able to modulate functionally significant drug-cue-induced electrocortical markers. We also hypothesize that providing a real-time feedback (generated by a BCI platform with advanced signal processing algorithms) of one's own EEG/ERP neuronal markers of drug-cue reactivity will be associated with reduced drug-seeking and craving and enhanced inhibitory control in treatment-seeking CUD. Given that EEG- and ERP-based BCI systems are non-invasive, ambulatory and affordable, this proposal has important clinical implications. In particular, once tested and validated, this system could be implemented in treatment centers for reducing drug-cue reactivity/drug-seeking/craving and enhancing self-control. Because a BCI-based real- time feedback system incorporates each patient's own brain signature of illness, it could be used to design an individually tailored treatment program to prevent relapse. Thus, given my background in biomedical engineering and graduate research experience in EEG data acquisition, signal processing, data analysis and the support, expertise and extensive supervision of the sponsor and the co-sponsors, I believe I am at a unique juncture in undertaking this multidisciplinary and technologically cutting-edge research proposal. Therefore, obtaining NRSA support to integrate my course work, research experience with the proposed research training plan will help me develop as an independent scientist, with a niche in implementing engineering principles to advance clinical and interventional neuroscience.

Public Health Relevance

Craving is theorized to be a manifestation of conditioned psychophysiological response to drug-related stimuli, a key contributor for relapse and compulsive drug use in cocaine dependence and reduction of such craving is a critical treatment target and outcome measure. Recently, it was shown that some addicted individuals retain some cognitive control over their craving. We propose to extend these finding and reinforce cognitive control over craving with real-time feedback of one's own neural signature of drug-cue reactivity. In particular, we test the novel hypothesis that CUD can be trained efficiently to volitionally control their drug-cue reactivity using real-time feedback of their own brain signatur of illness, and that this training will result in reduced drug- seeking in these individuals.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Postdoctoral Individual National Research Service Award (F32)
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Special Emphasis Panel (ZRG1-F02A-J (20))
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Bjork, James M
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Icahn School of Medicine at Mount Sinai
Schools of Medicine
New York
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Moeller, Scott J; Zilverstand, Anna; Konova, Anna B et al. (2018) Neural Correlates of Drug-Biased Choice in Currently Using and Abstinent Individuals With Cocaine Use Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging 3:485-494
Alia-Klein, Nelly; Preston-Campbell, Rebecca N; Moeller, Scott J et al. (2018) Trait anger modulates neural activity in the fronto-parietal attention network. PLoS One 13:e0194444
McFarland, Dennis J; Parvaz, Muhammad A; Sarnacki, William A et al. (2017) Prediction of subjective ratings of emotional pictures by EEG features. J Neural Eng 14:016009
Parvaz, Muhammad A; Moeller, Scott J; d'Oleire Uquillas, Federico et al. (2017) Prefrontal gray matter volume recovery in treatment-seeking cocaine-addicted individuals: a longitudinal study. Addict Biol 22:1391-1401
Zilverstand, Anna; Parvaz, Muhammad A; Goldstein, Rita Z (2017) Neuroimaging cognitive reappraisal in clinical populations to define neural targets for enhancing emotion regulation. A systematic review. Neuroimage 151:105-116
Parvaz, Muhammad A; Moeller, Scott J; Malaker, Pias et al. (2017) Abstinence reverses EEG-indexed attention bias between drug-related and pleasant stimuli in cocaine-addicted individuals. J Psychiatry Neurosci 42:78-86
Moeller, Scott J; Fleming, Stephen M; Gan, Gabriela et al. (2016) Metacognitive impairment in active cocaine use disorder is associated with individual differences in brain structure. Eur Neuropsychopharmacol 26:653-62
Parvaz, Muhammad A; Gabbay, Vilma; Malaker, Pias et al. (2016) Objective and specific tracking of anhedonia via event-related potentials in individuals with cocaine use disorders. Drug Alcohol Depend 164:158-165
Zilverstand, Anna; Parvaz, Muhammad A; Moeller, Scott J et al. (2016) Cognitive interventions for addiction medicine: Understanding the underlying neurobiological mechanisms. Prog Brain Res 224:285-304
Konova, Anna B; Moeller, Scott J; Parvaz, Muhammad A et al. (2016) Converging effects of cocaine addiction and sex on neural responses to monetary rewards. Psychiatry Res Neuroimaging 248:110-8

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