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We briefly describe ways in which neuroeconomics has made contributions to its contributing disciplines, especially neuroscience, and a specific way in which it could make future contributions to both. The contributions of a scientific research programme can be categorized in terms of (1) description and classification of phenomena, (2) the discovery of causal relationships among those phenomena, and (3) the development of tools to facilitate (1) and (2). We consider ways in which neuroeconomics has advanced neuroscience and economics along each line. Then, focusing on electrophysiological methods, we consider a puzzle within neuroeconomics whose solution we believe could facilitate contributions to both neuroscience and economics, in line with category (2). This puzzle concerns how the brain assigns reward values to otherwise incomparable stimuli. According to the common currency hypothesis, dopamine release is a component of a neural mechanism that solves comparability problems. We review two versions of the common currency hypothesis, one proposed by Read Montague and colleagues, the other by William Newsome and colleagues, and fit these hypotheses into considerations of rational choice.

The increasing volume, complexity, and interconnectedness of published studies in neuroscience make it difficult to determine what is known, what is uncertain, and how to contribute effectively to one's field. There is a pressing need to develop automated strategies to help researchers navigate the vastness of the published record. Simplified, interactive, and unbiased representations of previous findings (i.e., research maps) would be invaluable in preparing research surveys, in guiding experiment planning, and in evaluating research plans and contributions. Principles normally used in weighing research findings, including reproducibility and convergence, could be automated and incorporated into research maps. Here, we discuss a series of recent advances that are bringing us closer than ever to being able to derive systematic, comprehensive, but also interactive and user-friendly research maps. These maps could revolutionize the way we review the literature, plan experiments, and fund and publish science.

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