Model-based predictions for dopamine

Angela J. Langdon, Melissa J. Sharpe, Geoffrey Schoenbaum, Yael Niv

Research output: Contribution to journalReview article

28 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1-7
Number of pages7
JournalCurrent Opinion in Neurobiology
Volume49
DOIs
StatePublished - Apr 2018

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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