Classical computational approaches to modeling the basal ganglia

Ahmed A. Moustafa*, V. Srinivasa Chakravarthy

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review


There have been several modeling approaches to simulate BG structure and function. In this chapter, we discuss major modeling frameworks that have been proposed to simulate many functions of the BG. Many of such modeling studies are classical approaches in the field of BG modeling, 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
Number of pages18
ISBN (Electronic)978-981-10-8494-2
ISBN (Print)978-981-13-4168-7, 978-981-10-8493-5
Publication statusE-pub ahead of print - 22 Mar 2018
Externally publishedYes

Publication series

NameCognitive Science and Technology
ISSN (Print)2195-3988
ISSN (Electronic)2195-3996


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