Research in her laboratory focuses on characterizing the diverse learning and decision-making processes that support adaptive motivated behavior. Specifically, she focuses on understanding the cognitive, computational, and neural processes engaged to predict positive and negative environmental events and evaluate potential responses, as well as how these processes change over the course of development and vary across individuals. She uses an array of methodological techniques to pursue these questions including neuroimaging, psychophysiology, computational modeling, and genetics, in conjunction with experimental paradigms that draw upon both animal learning and economic decision theories. She received her B.S. in Symbolic Systems from Stanford University and her PhD in Psychology from New York University.