Classical computational approaches to modeling the basal ganglia

Ahmed A. Moustafa, V. Srinivasa Chakravarthy

Research output: Chapter in Book / Conference PaperChapter

Abstract

There have been several modelling approaches to simulate BG structure and function. In this chapter, we discuss major modelling frameworks that have been proposed to simulate many functions of the BG. Many of such modelling studies are classical approaches in the field of BG modelling, which have been repeatedly to simulate many BG functions. In short, here we discuss the following model approaches: dimensionality reduction models, action section selection models, Go/NoGo models, reinforcement learning (RL) models of the basal ganglia, and Actor-Critic models. Importantly, this chapter mainly provides an overview of main architectures used to simulate the BG structure and function. In addition, we discuss many other models, such as those of gait, reaching, and other in the following chapters.
Original languageEnglish
Title of host publicationComputational Neuroscience Models of the Basal Ganglia
EditorsV. Srinivasa Chakravarthy, Ahmed A. Moustafa
Place of PublicationSingapore
PublisherSpringer Nature
Pages41-58
Number of pages18
ISBN (Electronic)9789811084942
ISBN (Print)9789811084935
DOIs
Publication statusPublished - 2018

Keywords

  • Parkinson's disease
  • basal ganglia
  • dopamine
  • neurons

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