Neuronal Circuit Computation of Choice

Research output: Chapter in Book/Report/Conference proceedingChapter


All of the models developed in preceding chapters present analyses at the level of action potential firing rates in major output neurons. This is, however, only one kind of neurbiological modeling. A large and dynamic community of theorists also develop more biophysically detailed models that often make detailed and testable predictions about the dynamics of both neuronal firing rates and behavior. This chapter presents an example of that approach in the study of decision making. The chapter begins by developing biophysically plausible accumulator models of the type described in Chapter 19. It then goes on to show how such a circuit can be endowed with realistic reward-dependent learning to guide value-based decision making. A detailed explanation of how models of this kind account for dopamine-dependent reward learning is provided. The chapter concludes with a discussion of the behavior of models of this class in strategic games, during probabilistic inference and during "irrational" decision making.

Original languageEnglish (US)
Title of host publicationNeuroeconomics
Subtitle of host publicationDecision Making and the Brain: Second Edition
PublisherElsevier Inc.
Number of pages19
ISBN (Print)9780124160088
StatePublished - Sep 2013


  • Biophysical Modeling
  • Drift Diffusion
  • Network Modeling
  • Neural Dynamics
  • Value Learning

ASJC Scopus subject areas

  • General Neuroscience


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