Conference Paper

A Motor Control Model of the Nematode C. e1egaans

Graduate Sch. of Eng., Hiroshima Univ.
DOI: 10.1109/ROBIO.2004.1521900 Conference: Robotics and Biomimetics, 2004. ROBIO 2004. IEEE International Conference on
Source: IEEE Xplore

ABSTRACT This paper focuses on the nematode C. elegans which has a relatively simple structure, and is one of the most analyzed organisms among multicellular ones. We aim to develop a mathematical model of this organism to analyze control mechanisms with respect to locomotion. First, a new motor control model of the C. elegans is proposed, which includes both of the neuronal circuit model and the dynamic model of the body. Then, the effectiveness of the proposed model is verified through a series of computer simulations

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    ABSTRACT: This paper focuses on the nematode , which has a relatively simple structure, and is one of the most analyzed organisms among multicellular ones. We aim to develop a computer model of this organism to analyze control mechanisms with respect to its movements. First, a neuronal circuit model for directional control and a kinematic model of the muscle body are proposed. Then, by integrating the two models, we construct the whole body model of . The effectiveness of the proposed model is verified through a series of computer simulations.
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    ABSTRACT: In this paper, the modeling of several complex chemotaxis behaviors of C. elegans is explored, which include food attraction, toxin avoidance, and locomotion speed regulation. We first model the chemotaxis behaviors of food attraction and toxin avoidance separately. Then, an integrated chemotaxis behavioral model is proposed, which performs the two chemotaxis behaviors simultaneously. The novelty and the uniqueness of the proposed chemotaxis behavioral models are characterized by several attributes. First, all the chemotaxis behavioral model sare on biological basis, namely, the proposed chemotaxis behavior models are constructed by extracting the neural wire diagram from sensory neurons to motor neurons, where sensory neurons are specific for chemotaxis behaviors. Second, the chemotaxis behavioral models are able to perform turning and speed regulation. Third, chemotaxis behaviors are characterized by a set of switching logic functions that decide the orientation and speed. All models are implemented using dynamic neural networks (DNN) and trained using the real time recurrent learning (RTRL) algorithm. By incorporating a speed regulation mechanism, C. elegans can stop spontaneously when approaching food source or leaving away from toxin. The testing results and the comparison with experiment results verify that the proposed chemotaxis behavioral models can well mimic the chemotaxis behaviors of C. elegans in different environments.
    Journal of Computational Neuroscience 01/2013; · 2.44 Impact Factor
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