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Journal of Computational Neuroscience

, Volume 38, Issue 3, pp 601–616 | Cite as

A network model comprising 4 segmental, interconnected ganglia, and its application to simulate multi-legged locomotion in crustaceans

  • M. Grabowska
  • T. I. Toth
  • C. Smarandache-Wellmann
  • S. Daun-GruhnEmail author
Article

Abstract

Inter-segmental coordination is crucial for the locomotion of animals. Arthropods show high variability of leg numbers, from 6 in insects up to 750 legs in millipedes. Despite this fact, the anatomical and functional organization of their nervous systems show basic similarities. The main similarities are the segmental organization, and the way the function of the segmental units is coordinated. We set out to construct a model that could describe locomotion (walking) in animals with more than 6 legs, as well as in 6-legged animals (insects). To this end, we extended a network model by Daun-Gruhn and Tóth (Journal of Computational Neuroscience, doi: 10.1007/s10827-010-0300-1, 2011). This model describes inter-segmental coordination of the ipsilateral legs in the stick insect during walking. Including an additional segment (local network) into the original model, we could simulate coordination patterns that occur in animals walking on eight legs (e.g., crayfish). We could improve the model by modifying its original cyclic connection topology. In all model variants, the phase relations between the afferent segmental excitatory sensory signals and the oscillatory activity of the segmental networks played a crucial role. Our results stress the importance of this sensory input on the generation of different stable coordination patterns. The simulations confirmed that using the modified connection topology, the flexibility of the model behaviour increased, meaning that changing a single phase parameter, i.e., gating properties of just one afferent sensory signal was sufficient to reproduce all coordination patterns seen in the experiments.

Keywords

Central pattern generator Inter-segmental coordination Network model Locomotion Sensory feedback Arthropods 

Notes

Acknowledgments

We would like to thank Dr. A. Büschges for useful discussions in the course of the work. The work was supported by DFG Grants to SDG: DA1182/1-1, GR3690/2-1 and GR3690/4-1.

Conflict of Interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • M. Grabowska
    • 1
  • T. I. Toth
    • 1
  • C. Smarandache-Wellmann
    • 2
  • S. Daun-Gruhn
    • 1
    Email author
  1. 1.Heisenberg Research Group of Computational Biology, Department of Animal Physiology, Institute of ZoologyUniversity of CologneCologneGermany
  2. 2.Emmy-Noether Research Group, Department of Animal Physiology, Institute of ZoologyUniversity of CologneCologneGermany

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