I study the neuroscience of behavior change. My approach is interdisciplinary and multimodal: I use diverse methods (e.g., genomics, pharmacological manipulation, functional and structural neuroimaging, real-time neurofeedback, eye tracking) to resolve the biological signals that describe individual behavior. By characterizing the neural mechanisms supporting learning, cognitive control, and decision making, I develop robust models of behavior that can inform more effective behavior change interventions across the continuum of health.
My current research focuses on three questions:
- How does motivational context shape learning and decision making?
- What drives individual differences in goal-directed decision making?
- Can computational cognitive neuroscience approaches identify novel, neurally-informed targets for more precise, personalized behavioral change intervention?
Selected works in progress
- Using attention-motivation interactions to predict therapeutic response in ADHD (with Alison Adcock, Scott Kollins, and Ian Krajbich)
- Modeling learning from 'cognitive neurostimulation' using real-time neurofeedback from the midbrain (with Alison Adcock, Jeff MacInnes, and Katie Dickerson)
- Investigating feedback learning and its relationship to perfectionism in young adults (with Alison Adcock and Nancy Zucker)
- Decomposing risk representation in parietal cortex using Bayesian analytical approaches (with McKell Carter and Scott Huettel)
- A neurodevelopmental framework for applying behavioral economics in adolescents and young adults (with Charlene Wong and Peter Ubel)
©2020 Shabnam Hakimi