An Analysis of Decision under Risk in Rats

Christine M. Constantinople, Alex T. Piet, Carlos D. Brody

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

In 1979, Daniel Kahneman and Amos Tversky published a ground-breaking paper titled “Prospect Theory: An Analysis of Decision under Risk,” which presented a behavioral economic theory that accounted for the ways in which humans deviate from economists’ normative workhorse model, Expected Utility Theory [1, 2]. For example, people exhibit probability distortion (they overweight low probabilities), loss aversion (losses loom larger than gains), and reference dependence (outcomes are evaluated as gains or losses relative to an internal reference point). We found that rats exhibited many of these same biases, using a task in which rats chose between guaranteed and probabilistic rewards. However, prospect theory assumes stable preferences in the absence of learning, an assumption at odds with alternative frameworks such as animal learning theory and reinforcement learning [3–7]. Rats also exhibited trial history effects, consistent with ongoing learning. A reinforcement learning model in which state-action values were updated by the subjective value of outcomes according to prospect theory reproduced rats’ nonlinear utility and probability weighting functions and also captured trial-by-trial learning dynamics. Constantinople et al. apply prospect theory, the predominant economic theory of decision-making under risk, to rats. Rats exhibit signatures of both prospect theory and reinforcement learning. The authors present a model that integrates these frameworks, accounting for rats’ nonlinear econometric functions and also trial-by-trial learning.

Original languageEnglish (US)
Pages (from-to)2066-2074.e5
JournalCurrent Biology
Volume29
Issue number12
DOIs
StatePublished - Jun 17 2019

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Keywords

  • computational model
  • decision-making
  • prospect theory
  • rat behavior
  • reinforcement learning
  • reward
  • subjective value

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