Neural circuit mechanisms of value-based decision-making and reinforcement learning

A. Soltani, W. Chaisangmongkon, X. J. Wang

Research output: Chapter in Book/Report/Conference proceedingChapter


Despite groundbreaking progress, currently we still know preciously little about the biophysical and circuit mechanisms of valuation and reward-dependent plasticity underlying adaptive choice behavior. For instance, whereas phasic firing of dopamine neurons has long been ascribed to represent reward-prediction error (RPE), only recently has research begun to uncover the mechanism of how such a signal is computed at the circuit level. In this chapter, we will briefly review neuroscience experiments and mathematical models on reward-dependent adaptive choice behavior and then focus on a biologically plausible, reward-modulated Hebbian synaptic plasticity rule. We will show that a decision-making neural circuit endowed with this learning rule is capable of accounting for behavioral and neurophysiological observations in a variety of value-based decision-making tasks, including foraging, competitive games, and probabilistic inference. Looking forward, an outstanding challenge is to elucidate the distributed nature of reward-dependent processes across a large-scale brain system.

Original languageEnglish (US)
Title of host publicationDecision Neuroscience
Subtitle of host publicationAn Integrative Perspective
PublisherElsevier Inc.
Number of pages13
ISBN (Electronic)9780128053317
ISBN (Print)9780128053089
StatePublished - Oct 10 2016


  • Competitive game
  • Computational principles
  • Matching law
  • Neural circuit mechanism
  • Probabilistic inference
  • Single-neuron physiology
  • Valuation computation
  • Value-based adaptive choice behavior

ASJC Scopus subject areas

  • General Medicine
  • General Neuroscience


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