The Neurobiology of Impulsive Decision-Making and Reinforcement Learning in Nonhuman Animals

Stephanie M. Groman

Research output: Chapter in Book/Report/Conference proceedingChapter

12 Scopus citations

Abstract

Impulsive decisions are those that favor immediate over delayed rewards, involve the acceptance of undue risk or uncertainty, or fail to adapt to environmental changes. Pathological levels of impulsive decision-making have been observed in individuals with mental illness, but there may be substantial heterogeneity in the processes that drive impulsive choices. Understanding this behavioral heterogeneity may be critical for understanding associated diverseness in the neural mechanisms that give rise to impulsivity. The application of reinforcement learning algorithms in the deconstruction of impulsive decision-making phenotypes can help bridge the gap between biology and behavior and provide insights into the biobehavioral heterogeneity of impulsive choice. This chapter will review the literature on the neurobiological mechanisms of impulsive decision-making in nonhuman animals; specifically, the role of the amine neuromodulatory systems (dopamine, serotonin, norepinephrine, and acetylcholine) in impulsive decision-making and reinforcement learning processes is discussed. Ultimately, the integration of reinforcement learning algorithms with sophisticated behavioral and neuroscience techniques may be critical for advancing the understanding of the neurochemical basis of impulsive decision-making.

Original languageEnglish (US)
Title of host publicationCurrent Topics in Behavioral Neurosciences
PublisherSpringer Science and Business Media Deutschland GmbH
Pages23-52
Number of pages30
DOIs
StatePublished - 2020

Publication series

NameCurrent Topics in Behavioral Neurosciences
Volume47
ISSN (Print)1866-3370
ISSN (Electronic)1866-3389

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

  • Acetylcholine
  • Decision making
  • Dopamine
  • Impulsivity
  • Norepinephrine
  • Reinforcement learning
  • Serotonin

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