Neuroeconomics is the newest of the economic sciences with a focus on how the embodied human brain interacts with its institutional and social environment to make economic decisions. This paper presents an overview of neuroeconomics methods and reviews a number of results in this emerging field of study.

The goal of neuroeconomics is a mathematical theory of how the brain implements decisions, that is tied to behaviour. This theory is likely to show some decisions for which rational-choice theory is a good approximation, to provide a deeper level of distinction among competing behavioural alternatives, and to provide empirical inspiration for economics to incorporate more nuanced ideas about endogeneity of preferences, individual difference, emotions, endogeneous regulation of states, and so forth. I also address some concerns about rhetoric and practical (...) epistemology. Neuroscience articles are necessarily speculative and the science has proceeded rapidly because of that rhetorical convention. Single-study papers are encouraged and are necessarily limited in what can be inferred, so the sturdiest cumulation of results, and the best guide forward, comes in review journals which compile results and suggest themes. The potential of neuroeconomics is in combining the clearest experimental paradigms and statistical methods in economics, with the unprecedented capacity to measure a range of neural and cognitive activity that economists like Edgeworth, Fisher and Ramsey daydreamed about but did not have. (shrink)

A great deal of philosophy of mind in the modern era has been driven by an intense aversion to Cartesian dualism. In the 1950s, materialists claimed to have succeeded once and for all in exorcising the Cartesian ghost by identifying the mind with the brain. In subsequent decades, cognitive science put scientific meat on this metaphysical skeleton by explicating mental processes as digital computation implemented in the brain's hardware.

Neuroeconomics is examined critically using data on the response times of subjects who were asked to express their preferences in the context of the Allais Paradox. Different patterns of choice are found among the fast and slow responders. This suggests that we try to identify types of economic agents by the time they take to make their choices. Nevertheless, it is argued that it is far from clear if and how neuroeconomics will change economics.

I distinguish between two styles of research that are both called . Neurocellular economics (NE) uses the modelling techniques and mathematics of economics to model relatively encapsulated functional parts of brains. This approach rests upon the fact that brains are, like markets, massively distributed information-processing networks over which executive systems can exert only limited and imperfect governance. Harrison's (2008) deepest criticisms of neuroeconomics do not apply to NE. However, the more famous style of neuroeconomics is behavioural economics in the scanner. (...) This is often motivated by complaints about conventional economics frequently heard from behavioural economists. It attempts to use neuroimaging data to justify arguments for replacing standard aspects of microeconomic theory by facts and conjectures about human psychology. Harrison's grounds for unease about neuroeconomics apply to most BES, or at least to its explicit methodology. This methodology is naively reductionist and illegitimately assumes that economics should not do what all successful science does, namely, model abstract aspects of its target phenomena instead of would-be complete and fully ecologically situated facsimiles of them. (shrink)

As an emerging discipline, neuroeconomics faces considerable methodological and practical challenges. In this paper, I suggest that these challenges can be understood by exploring the similarities and dissimilarities between the emergence of neuroeconomics and the emergence of cognitive and computational neuroscience two decades ago. From these parallels, I suggest the major challenge facing theory formation in the neural and behavioural sciences is that of being under-constrained by data, making a detailed understanding of physical implementation necessary for theory construction in neuroeconomics. (...) Rather than following a top-down strategy, neuroeconomists should be pragmatic in the use of available data from animal models, information regarding neural pathways and projections, computational models of neural function, functional imaging and behavioural data. By providing convergent evidence across multiple levels of organization, neuroeconomics will have its most promising prospects of success. (shrink)

The following is a set of reading notes on, and questions for, the Neuroeconomics enterprise. My reading of neuroscience evidence seems to be at odds with basic conceptions routinely assumed in the Neuroeconomics literature. I also summarize methodological concerns regarding design, implementation, and statistical evaluation of Neuroeconomics experiments.

In this study, Don Ross explores the relationship of economics to other branches of behavioral science, asking, in the course of his analysis, under what interpretation economics is a sound empirical science. The book explores the relationships between economic theory and the theoretical foundations of related disciplines that are relevant to the day-to-day work of economics -- the cognitive and behavioral sciences. It asks whether the increasingly sophisticated techniques of microeconomic analysis have revealed any deep empirical regularities -- whether technical (...) improvement represents improvement in any other sense. Casting Daniel Dennett and Kenneth Binmore as its intellectual heroes, the book proposes a comprehensive model of economic theory that, Ross argues, does not supplant, but recovers the core neoclassical insights, and counters the caricaturish conception of neoclassicism so derided by advocates of behavioral or evolutionary economics. Because he approaches his topic from the viewpoint of the philosophy of science, Ross devotes one chapter to the philosophical theory and terminology on which his argument depends and another to related philosophical issues. Two chapters provide the theoretical background in economics, one covering developments in neoclassical microeconomics and the other treating behavioral and experimental economics and evolutionary game theory. The three chapters at the heart of the argument then apply theses from the philosophy of cognitive science to foundational problems for economic theory. In these chapters, economists will find a genuinely new way of thinking about the implications of cognitive science for economics, and cognitive scientists will find in economic behavior, a new testing site for the explanations of cognitive science. (shrink)

William Uttal is concerned that in an effort to prove itself a hard science, psychology may have thrown away one of its most important methodological tools—a critical analysis of the fundamental assumptions that underlie day-to-day empirical research. In this book Uttal addresses the question of localization: whether psychological processes can be defined and isolated in a way that permits them to be associated with particular brain regions. New, noninvasive imaging technologies allow us to observe the brain while it is actively (...) engaged in mental activities. Uttal cautions, however, that the excitement of these new research tools can lead to a neuroreductionist wild goose chase. With more and more cognitive neuroscientific data forthcoming, it becomes critical to question their limitations as well as their potential. Uttal reviews the history of localization theory, presents the difficulties of defining cognitive processes, and examines the conceptual and technical difficulties that should make us cautious about falling victim to what may be a "neo-phrenological" fad. (shrink)

In treating cognition as problem solving, Andy Clark suggests, we may often abstract too far from the very body and world in which our brains evolved to guide...