Valuation for Risky and Uncertain Choices

Philippe N. Tobler, Elke U. Weber

Research output: Chapter in Book/Report/Conference proceedingChapter

26 Scopus citations

Abstract

In this chapter, we describe how risk and ambiguity impact the value of choice options, how this impact can be modelled formally and how it is implemented in the brain. In particular, we give an overview of two distinct ways of how risky choice options can be decomposed - either into outcomes and probabilities as proposed in economics or into statistical moments of the probability distribution like mean, variance, or skewness, as proposed in finance theory. The components of either approach appear to be represented in common and, at least to some extent, in separate brain regions, which include the dopaminergic midbrain, striatum and the orbitofrontal cortex. Activity in different (prefrontal and striatal) brain regions also supports the distinction between decisions from experience, when knowledge about risk is learned through trial and error versus decisions from description, when it is described symbolically. The fact that the principal components of formal models from economics and finance theory and their behavioral versions that provide better descriptive fit are represented in the brain provides converging support for these models.

Original languageEnglish (US)
Title of host publicationNeuroeconomics
Subtitle of host publicationDecision Making and the Brain: Second Edition
PublisherElsevier Inc.
Pages149-172
Number of pages24
ISBN (Print)9780124160088
DOIs
StatePublished - Sep 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Neuroscience

Keywords

  • Ambiguity
  • Decision making
  • Description
  • Dopamine
  • Expected utility theory
  • Experience
  • Mean-variance-skewness
  • Neuroimaging
  • Neurophysiology
  • Prefrontal cortex
  • Prospect theory
  • Risk
  • Striatum

Fingerprint

Dive into the research topics of 'Valuation for Risky and Uncertain Choices'. Together they form a unique fingerprint.

Cite this