Model-based predictions for dopamine

Curr Opin Neurobiol. 2018 Apr;49:1-7. doi: 10.1016/j.conb.2017.10.006. Epub 2017 Oct 31.

Abstract

Phasic dopamine responses are thought to encode a prediction-error signal consistent with model-free reinforcement learning theories. However, a number of recent findings highlight the influence of model-based computations on dopamine responses, and suggest that dopamine prediction errors reflect more dimensions of an expected outcome than scalar reward value. Here, we review a selection of these recent results and discuss the implications and complications of model-based predictions for computational theories of dopamine and learning.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Animals
  • Computer Simulation*
  • Dopamine / physiology*
  • Humans
  • Learning / physiology*
  • Models, Neurological*
  • Reinforcement, Psychology

Substances

  • Dopamine