Our lab is guided by three overarching questions:
How do we control our behaviors and temptations to meet our goals?
Why are these self-control processes compromised in some but not others?
Can we restore these behavioral control deficits with neuroscience-informed interventions?
Active projects
Predicting craving and relapse using neurobehavioral markers of goals and habits in opioid use disorder
Opioid use related deaths impose a devastating toll on individual and public health, necessitating the identification of neuroscience-based biomarkers of severity and recovery. This project applies naturalistic, longitudinal, and computational tools to study motivational control (i.e., balance between goals and habits), which putatively underlies drug addiction, during inpatient opioid use disorder treatment to predict prospective craving and relapse. Insights from this project may ultimately be applied to help curb the impact of the opioid epidemic in our communities.
Modulation of the prefrontal cortex to enhance value-based decision-making in drug addiction
The prefrontal cortex underpins motivational control, and impairments in this balance are thought to drive compulsive drug use in people with addiction. This project employs structural and functional MRI to map, and transcranial direct current stimulation to enhance the neural systems underlying goals and habits in people with substance use disorders. We will also test the clinical utility of the neurobehavioral estimates of motivational control to predict prospective craving and drug use, with the aim of identifying meaningful biomarkers of relapse risk and vulnerability.
Using real-world clinical data to examine substance use patterns before and after novel interventions
Existing pharmacotherapies for alcohol and tobacco use disorders remain limited, warranting neuroscience-informed investigations of novel interventions. Emerging evidence points to glucagon-like peptide-1 (GLP-1) receptor agonists, originally developed for treatment of diabetes and obesity, as candidates for reducing substance use. In this project, we are leveraging real-world clinical data via electronic health record databases to detect substance use patterns changes before and after GLP-1 treatment initiation at the population level. Importantly, we are investigating the underlying affective and motivational factors that may explain treatment response, which has the potential to enhance personalized interventions to reduce substance use.