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Neural Mechanisms of Leg Motor Control in Crayfish: Insights for Neurobiologically-Inspired Autonomous Systems

Neural Mechanisms of Leg Motor Control in Crayfish: Insights for Neurobiologically-Inspired Autonomous Systems

Didier Le Ray, Morgane Le Bon-Jego, Daniel Cattaert
Copyright: © 2009 |Pages: 22
ISBN13: 9781599049960|ISBN10: 1599049961|ISBN13 Softcover: 9781616925376|EISBN13: 9781599049977
DOI: 10.4018/978-1-59904-996-0.ch002
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MLA

Le Ray, Didier, et al. "Neural Mechanisms of Leg Motor Control in Crayfish: Insights for Neurobiologically-Inspired Autonomous Systems." Advancing Artificial Intelligence through Biological Process Applications, edited by Ana B. Porto Pazos, et al., IGI Global, 2009, pp. 20-41. https://doi.org/10.4018/978-1-59904-996-0.ch002

APA

Le Ray, D., Le Bon-Jego, M., & Cattaert, D. (2009). Neural Mechanisms of Leg Motor Control in Crayfish: Insights for Neurobiologically-Inspired Autonomous Systems. In A. Porto Pazos, A. Pazos Sierra, & W. Buño Buceta (Eds.), Advancing Artificial Intelligence through Biological Process Applications (pp. 20-41). IGI Global. https://doi.org/10.4018/978-1-59904-996-0.ch002

Chicago

Le Ray, Didier, Morgane Le Bon-Jego, and Daniel Cattaert. "Neural Mechanisms of Leg Motor Control in Crayfish: Insights for Neurobiologically-Inspired Autonomous Systems." In Advancing Artificial Intelligence through Biological Process Applications, edited by Ana B. Porto Pazos, Alejandro Pazos Sierra, and Washington Buño Buceta, 20-41. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-59904-996-0.ch002

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Abstract

Computational neuroscience has a lot to gain from invertebrate research. In this chapter focusing on the sensory-motor network that controls leg movement and position in crayfish, we describe how simple neural circuitry can integrate variable information to produce an adapted output function. We describe how a specific sensor encodes the dynamic and static parameters of leg movements, and how the central motor network assimilates and reacts to this information. We then present an overview of the regulatory mechanisms thus far described that operate at the various levels of this sensory-motor network to organize and maintain the system into a dynamic range. On the basis of this simple animal model, some basic neurobiological concepts are presented which may provide new insights for engineering artificial autonomous systems.

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