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Canonical models of rational choice fail to account for many forms of motivated adaptive behaviors, specifically in domains such as food selections. To describe behavior in such emotion- and reward-laden scenarios, researchers have proposed dual-process models that posit competition between a slower, analytic faculty and a fast, impulsive, emotional faculty. In this paper, we examine the assumptions and limitations of these approaches to modeling motivated choice. We argue that models of this form, though intuitively attractive, are biologically implausible. We describe an approach to motivated choice based on sequential sampling process models that can form a solid theoretical bridge between what is known about brain function and environmental influences upon choice. We further suggest that the complex and dynamic relationships between biology, behavior, and environment affecting choice at the individual level must inform aggregate models of consumer choice. Models using agent-based complex systems may further provide a principled way to relate individual and aggregate consumer choices to the aggregate choices made by businesses and social institutions. We coin the term "brain-to-society systems" choice model for this broad integrative approach.

This article presents an introduction to and analysis of an emerging area of research, namely decision neuroscience, whose goal is to integrate research in neuroscience and behavioral decision making. The article includes an exposition of (1) how the exponential accumulation of knowledge in neuroscience can potentially enrich research on decision making, (2) the range of techniques in neuroscience that can be used to shed light on various decision making phenomena, (3) examples of potential research in this emerging area, and (4) some of the challenges readers need to be cognizant of while venturing into this new area of research.