Trends in Cognitive Sciences
Neuroeconomics: cross-currents in research on decision-making
Introduction
The question of how we make, and how we should make, judgments and decisions has occupied thinkers for many centuries, with different disciplines approaching the problem with characteristically different techniques. A very recent approach, popularly known as neuroeconomics, has sought to integrate ideas from the fields of psychology, neuroscience and economics in an effort to specify more accurate models of choice and decision (for reviews from the perspective of economics, see 1, 2).
How profitable the neuroeconomic approach will be is still unclear. Predictably, there are strong opinions on both sides. On the one hand, its strongest advocates (aided by some exaggerated media reporting) have presented neuroeconomics as a new paradigm that will eventually replace the classical approaches. On the other, skeptics in both communities have argued that economic models and neuroscientific techniques reflect disparate levels of analysis that have little to offer one another. Economists have, historically, been skeptical of the ability of ‘process measures’ to contribute to our understanding of economic and social behavior [3]; and neuroscientists commonly view economics as too abstract and removed from the mechanisms of interest in the brain.
Although we are perhaps not as optimistic as the most ardent believers in neuroeconomics when it comes to the time-line of progress, we do believe that the field has real potential for making important contributions to our understanding of decision-making, above and beyond what has and will continue to be learned from work within each discipline independently. This is because neuroeconomics is able to draw upon the complementary strengths of its contributing disciplines. In fact, the benefits of increasing contact between neuroscience, psychology and economics are already apparent.
The central argument of this article is that economics, psychology and neuroscience can each benefit from taking account of the insights that the other disciplines have to offer in understanding human decision-making. In the following, we first address how neuroscience can, and already has, benefited from economics' unitary perspective. We then discuss how economics can, and has begun to, be enriched by taking account of cooperation and competition between multiple specialized neural systems, before closing with some thoughts on potentially fruitful future research directions.
Section snippets
The view from economics: one unified theory
Economics contributes to the joint endeavor of neuroeconomics by bringing its insights into the diverse outcomes that can arise from the strategic and market interactions of multiple agents, and through a set of precise, formal, mathematical models to describe these interations and outcomes. However, the aspect of economics that may prove most useful to neuroscientists (and, indeed, that has already begun to bear fruit) is its embracing of a unified theoretical framework for understanding human
The view from neuroscience: multiple systems
Psychology and neuroscience also bring much to the neuroeconomics table, contributing a rich tradition of empirical research and increasingly precise methods for studying behavior and the neural mechanisms by which it is governed. Of particular relevance to economics is the growing insight into mechanisms that are responsible for the assessment of utility and execution of decision-making behavior, as outlined in the previous section. However, perhaps the single most important perspective that
The future
This article has reviewed two general ways in which the neuroeconomic endeavor can make important contributions to research on decision-making – firstly, the incorporation into neuroscience and psychology of the formal, rigorous economic modeling approach, and secondly, the awareness within the economic community of the evidence for multiple-systems involved in decision-making. One current challenge is to ensure that researchers are communicating productively; often, terms such as ‘choice’,
References (80)
Neural basis of utility estimation
Curr. Opin. Neurobiol.
(1997)- et al.
Effects of nucleus accumbens amphetamine on lateral hypothalamic brain stimulation reward
Brain Res.
(1988) Saccade reward signals in posterior cingulate cortex
Neuron
(2003)Neural correlates of behavioral preference for culturally familiar drinks
Neuron
(2004)- et al.
Uncertainty, neuromodulation, and attention
Neuron
(2005) - et al.
A surprise-quiz view of learning in economic experiments
Games Econ. Behav.
(1999) Implementation of error-processing in the human anterior cingulate cortex: a source analysis of the magnetic equivalent of the error-related negativity
Biol. Psychol.
(2003)Functional imaging of brain responses to pain. A review and meta-analysis
Clin. Neurophysiol.
(2000)Functional imaging of neural responses to expectancy and experience of monetary gains and losses
Neuron
(2001)- et al.
Neural computations that underlie decisions about sensory stimuli
Trends Cogn. Sci.
(2001)