For centuries, decision scholars paid little attention to emotions: Decisions were modeled in normative and descriptive frameworks with little regard for affective processes. Recently, however, an emotions revolution has taken place, particularly in the neuroscientific study of decision making, putting emotional processes on an equal footing with cognitive ones. Yet disappointingly little theoretical progress has been made. The concepts and processes discussed often remain vague, and conclusions about the implications of emotions for rationality are contradictory and muddled. We discuss three complementary ways to move the neuroscientific study of emotion and decision making from agenda setting to theory building. The first is to use reverse inference as a hypothesis-discovery rather than a hypothesis-testing tool, unless its utility can be systematically quantified (e.g., through meta-analysis). The second is to capitalize on the conceptual inventory advanced by the behavioral science of emotions, testing those concepts and unveiling the underlying processes. The third is to model the interplay between emotions and decisions, harnessing existing cognitive frameworks of decision making and mapping emotions onto the postulated computational processes. To conclude, emotions (like cognitive strategies) are not rational or irrational per se: How (un)reasonable their influence is depends on their fit with the environment.
