Neural activity causally underlies human cognition and behavior. Investigating the neurobiological principles and computational mechanisms governing brain activity during decision-making provides a way to improve theories of human behavior in the natural as well as social sciences (Glimcher & Rustichini 2004; Rustichini, 2009; Fehr & Rangel, 2009). In this context, the discipline of Neuroeconomics was originally conceived as an endeavor to interrogate neural activity during economic decision-making with the aim of evaluating competing decision theories (Rustichini, 2008; Glimcher, Camerer, Fehr & Poldrack 2009). From this origin, Neuroeconomics has evolved into a full-fledged enterprise of consilience; an attempt to not only test and bridge, but truly unify natural science and social science explanations of human behavior (Wilson, 1998; Glimcher & Rustichini, 2004; Rangel, Camerer & Montague, 2008).This dissertation binds two neuroeconomic studies of decision-making with an introduction and concluding commentary. The introduction presents a brief introduction to Neuroeconomics, meant to locate both research studies in the existing literature and philosophy of this field. The conclusion provides a brief appraisal of the role of Neuroeconomics in further advancing the kind of research into decision-making reported here. Both studies in this dissertation comprise investigations of human behavior during experience-based decision-making, with a special focus on the fundamental value computations that underlie such choice behavior.Study 1 investigates the role of neural reinforcement signals during learning of a strategic decision task from experience.Study 2 investigates the moderating effect of intelligence on neural reinforcement signals during a sequential binary choice task.Study 1 is reproduced from (Hawes, Vostroknutov & Rustichini 2013), and study 2 is reproduced from (Hawes, DeYoung, Gray & Rustichini; under review).