Evolving central pattern generators with varying number of neurons

Jeisung Lee, Daeeun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Central pattern generator (CPG) is a kind of neural circuit which can be observed in many animals showing rhythmic patterns of actions. The CPG neural circuit can produce complex rhythmic patterns by receiving only simple signals from the brain. Generally, the CPG neural models can be applied to solve robotic problems, or to understand the underlying neural mechanism for rhythmic animal behaviours. In this paper, we focus on how a small number of neurons generate the variable frequencies and phase of motor actions, and inspect what is the capacity of a varying number of neurons as a CPG model. The performance measure consists of frequency variability, input/output response rate, and phase shift. We have used evolutionary computation to measure the best performance for each number of CPG neurons ranging from two to eight neurons, and the result shows that four neurons or more can easily generate variable frequencies and anti-phase difference for left and right motor actions.

Original languageEnglish
Title of host publicationAdvances in Artificial Life
Subtitle of host publicationDarwin Meets von Neumann - 10th European Conference, ECAL 2009, Revised Selected Papers
Number of pages8
EditionPART 1
Publication statusPublished - 2011
Event10th European Conference of Artificial Life, ECAL 2009 - Budapest, Hungary
Duration: 2009 Sept 132009 Sept 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5777 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other10th European Conference of Artificial Life, ECAL 2009

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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