...
首页> 外文期刊>Neurocomputing >Biological modeling the undulatory locomotion of C. elegans using dynamic neural network approach
【24h】

Biological modeling the undulatory locomotion of C. elegans using dynamic neural network approach

机译:使用动态神经网络方法对秀丽隐杆线虫的波动运动进行生物学建模

获取原文
获取原文并翻译 | 示例
           

摘要

This paper provides an undulatory locomotion model of C. elegans to achieve the chemotaxis behaviors based on the biological neuronal and neuromuscular structure. The on-cell and off-cell mechanism, as well as the proprioceptive mechanism is incorporated into the locomotion model. The nervous system of C elegans is modeled by a dynamic neural network (DNN) that involves two parts: head DNN and motor neurons. The head DNN perceives the outside concentrations and generates the undulatory wave to the body. The motor neurons are responsible for transiting the undulatory wave along the body. The body of C elegans is represented as a multi-joint rigid link model with 11 links. The undulatory locomotion behavior is achieved by using the DNN to control the lengths of muscles on ventral and dorsal sides, and then using the muscle lengths to control the angles between two consecutive links. In this work, the relations between the outputs of DNN and muscle lengths, as well as the muscle lengths and the angles between two consecutive links, are determined. Furthermore, owing to the learning capability of DNN, a set of nonlinear functions that are designed to represent the chemotaxis behaviors of C elegans are learned by the head DNN. The testing results show good performance of the locomotion model for the chemotaxis behaviors of finding food and avoiding toxin, as well as slight and 12 turns. At last, quantitative analyses by comparing with the experiment results are provided to verify the realness and effectiveness of the locomotion model, which could serve as a prototype for other footless animals. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文提供了秀丽隐杆线虫的波动运动模型,以基于生物神经元和神经肌肉结构实现趋化行为。细胞上和细胞外机制以及本体感受机制都被纳入了运动模型。秀丽隐杆线虫的神经系统由动态神经网络(DNN)建模,该网络涉及两个部分:头部DNN和运动神经元。头部DNN感知外界浓度并向身体产生起伏波。运动神经元负责使波动波沿着身体传播。秀丽隐杆线虫的主体表示为具有11个链接的多关节刚性链接模型。通过使用DNN控制腹侧和背侧的肌肉长度,然后使用肌肉长度控制两个连续链接之间的角度,可以实现起伏的运动行为。在这项工作中,确定DNN的输出和肌肉长度之间的关系,以及两个连续链接之间的肌肉长度和角度。此外,由于DNN的学习能力,头部DNN可以学习一组用来表示线虫趋化行为的非线性函数。测试结果表明,该运动模型对于发现食物和避免毒素的趋化行为表现出良好的性能,并且轻微旋转了12圈。最后,通过与实验结果的比较进行定量分析,以验证运动模型的真实性和有效性,该模型可以作为其他无足动物的原型。 (C)2016 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Neurocomputing》 |2016年第19期|207-217|共11页
  • 作者单位

    Chongqing Univ Posts & Telecommun, Chongqing Key Lab Computat Intelligence, Chongqing 400065, Peoples R China|Natl Univ Singapore, Singapore 117576, Singapore;

    Natl Univ Singapore, Singapore 117576, Singapore;

    Chongqing Univ Posts & Telecommun, Chongqing Key Lab Computat Intelligence, Chongqing 400065, Peoples R China;

    Chongqing Univ Posts & Telecommun, Chongqing Key Lab Computat Intelligence, Chongqing 400065, Peoples R China;

    Chongqing Univ Posts & Telecommun, Chongqing Key Lab Computat Intelligence, Chongqing 400065, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Undulatory locomotion; Dynamic neural networks; C. elegans;

    机译:波动运动;动态神经网络;C。线虫;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号