Our research combines multiple levels of computational modeling and experimental work to
understand the neural mechanisms underlying reinforcement learning, decision making and
cognitive control. We develop neural circuit and algorithmic models that simulate systems-level
interactions between multiple brain areas (primarily prefrontal cortex and basal ganglia and their
modulation by dopamine). We test theoretical predictions of the models using various
neuropsychological, pharmacological, genetic, and imaging (primarily EEG) techniques.