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Neuroeconomics of Simple Choice and Uncertainty

October 16, 2017 - October 20, 2017

Coordinator: John O’Doherty

California Institute of Technology, Pasadena. USA



Peter Bossaerts, University of Melbourne, Australia

Wolfram Schultz, Cambridge University, UK

Catharine Winstanley, University of British Columbia, Vancouver, Canada

Sophie Deneve, Ecole Normale Superieure, Paris, France

Lesley Fellows, McGill University, Montreal, Canada

Aldo Rustichini, University of Minnesota, Minneapolis, USA

John O’Doherty, California Institute of Technology, Pasadena, USA


Neuroeconomics or decision neuroscience (as it is sometimes also called) emerged approximately 15 years ago and is focused on gaining an understanding of the neural computations underlying the capacity to make decisions. It is highly inter-disciplinary in flavor, borrowing theoretical ideas, experimental approaches and methods from a variety of more established disciplines including economics, cognitive psychology, animal learning, computer science and artificial intelligence, cognitive and systems neuroscience among others.

This Workshop will critically analyze some of the emerging themes in this field. It will first cover theoretical concepts in economics, reinforcement-learning and computational neuroscience that are utilized in order to study the neural substrates of decision-making, including economic constructs such as expected utility, risk and ambiguity. We will consider reinforcement-learning theories as they have been applied to the brain and behavior including model-based and model-free reinforcement learning, and we will examine computational models of decision making including Bayesian approaches, drift diffusion models and other methods.

The Workshop will then delve into key issues of the neural basis of decision-making. The role of different brain regions and neural systems in encoding valuation and utility, and in computing choices will be critically evaluated focusing on the orbitofrontal cortex, striatum and parietal cortex. The neural basis of reinforcement-learning, including the specific contribution of dopamine and other neurotransmitters will also be a focus. The extent to which neural systems encode different forms of uncertainty, including risk, expected uncertainty and estimation uncertainty will be considered. The contribution of converging methods and techniques in animals and humans, including lesion studies, electrophysiology, neuroimaging and other approaches for addressing these research questions will be evaluated.

We will also explore the potential contribution of neuroeconomics tools for gaining a better understanding of individual differences in learning and decision-making capabilities across individuals, as well as the promise that the neuroeconomics approach holds for yielding a better understanding into the nature of the decision-making deficits that occur in psychiatric disease. Finally, we will consider societal implications for neuroeconomics research in terms of the potential advances that might be realized for understanding better how individuals, groups and social systems operate.


October 16, 2017
October 20, 2017