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Decision-Making Under Uncertainty

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Neuroeconomics

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Abstract

All decision-making takes place under uncertainty, even in controlled laboratory circumstances. The Bayesian brain hypothesis, a widely accepted theoretical framework of brain function, prescribes that the brain uses probability distributions to store parameter values, rather than point estimates, and is thus able to use uncertainty on various parameters. This allows for investigating value-based decision-making under natural circumstances when information needs to be extracted from noisy input, and it may also impact on decisions based on propositional information. In this chapter, I present experimental approaches to neural representations of uncertainty in value-based decision-making.

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Acknowledgments

I would like to thank Quentin Huys, Marc Guitart Masip, Deborah Talmi and Matthias Staib, for helpful comments on a first draft of this manuscript.

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Authors and Affiliations

  1. University of Zurich, Zurich, Switzerland

    Dominik R. Bach

  2. University College London, London, UK

    Dominik R. Bach

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  1. Dominik R. Bach
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Correspondence to Dominik R. Bach .

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Editors and Affiliations

  1. Differentielle and Biologische Psychologie, Rheinische Friedrich-Wilhelms- Universität Bonn, Bonn, Germany

    Martin Reuter

  2. Department of Molecular Psychology, Institute for Psychology and Education, Ulm University, Ulm, Germany and Key Laboratory for NeuroInformation, School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Christian Montag

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Bach, D.R. (2016). Decision-Making Under Uncertainty. In: Reuter, M., Montag, C. (eds) Neuroeconomics. Studies in Neuroscience, Psychology and Behavioral Economics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35923-1_6

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