The Role of Chaotic Dynamics in Motor Pattern Generation

混沌动力学在运动模式生成中的作用

• 批准号: 9975490
• 负责人: Peter Rowat
• 金额: $ 36.05万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9975490&HistoricalAwards=false
• 关键词: Role; Chaotic; Dynamics; Motor; Pattern

IBN-9975490The role of chaotic dynamics in motor pattern generationPI: Peter F. Rowat, Co-PI: R.C.ElsonHow do animals produce and control repetitive behaviors such as walking, swimming, or chewing? In a variable or hostile environment, the ability to produce fast, appropriate, and flexible responses to new sensory information is of vital importance. The physical system of bones and muscles that produces movements is driven by neural signals - parallel trains of action potentials -- passing from underlying biological circuits known as central pattern generators (CPGs) to the muscles. The research problem is to understand the basic principles of production of these signals, or motor patterns, by a CPG. Many neural "building blocks" with which a CPG produces repetitive movements are now known. What is not well understood is how flexibility and responsiveness is built into a CPG. Biological substances known as neuromodulators can directly alter the properties of neural circuits, on a relatively slow time-scale. Could dynamical properties of CPG circuits directly contribute to flexibility and environmental responsiveness?From theoretical studies, it is known that a chaotic system has intrinsic properties, which could be very useful for the production of variable and environmentally responsive output. Its output is highly variable but in a structured way and techniques for the control of a chaotic system are now well known. At the same time, experimental studies of biological CPGs show that a significant amount of variability or jitter is always present. This project experimentally investigates the biological variability, on the one hand, and on the other, develops theoretical models of how a chaotic system can be used to impart flexibility of response into a motor system. There is a continual interaction between experimental data collection and model building. The variability in the data will be analyzed to determine the relative contributions of noise and deterministic -- chaotic - dynamics. Two well-known CPGs from the lobster stomatogastric system are used and recordings are made from small sub-circuits of these CPGs. Recently developed nonlinear analysis algorithms are used for this analysis. The control of intrinsic neuronal dynamics by synaptic connections within a CPG are studied using the same analysis algorithms. Simulated synaptic connections will be constructed between real biological neurons and computer-based model neurons. The dynamical control of a stomatogastric CPG will be studied by using simulated sensory feedback from an identified sensory neuron. Here the feedback loop from CPG to periphery and back via re-afferent circuits is closed by a computer-based model. In parallel with these experiments and data analysis, a chaos-based model system for the control of a robotic motor system, will be developed in simulations. It is designed around a robust, chaotic core and a dynamic, sensorimotor controller that utilizes recent chaos-control algorithms. There are many parallels between this design and properties of biological sensorimotor systems. The project will extend our knowledge about the role of biological variability and also the design of flexible robotic controllers.

IBN-9975490混沌动力学在运动模式生成中的作用。Rowat，Co-PI：R.C. Elson动物是如何产生和控制重复行为的，比如走路、游泳或咀嚼？在多变或恶劣的环境中，对新的感官信息做出快速、适当和灵活反应的能力至关重要。产生运动的骨骼和肌肉的物理系统是由神经信号驱动的-动作电位的平行序列-从被称为中央模式发生器（CPG）的底层生物回路传递到肌肉。研究的问题是要了解这些信号的生产，或运动模式的基本原则，由CPG。现在已经知道了许多CPG产生重复运动的神经“构建块”。 目前尚不清楚的是，灵活性和响应能力是如何融入中央政府的。被称为神经调质的生物物质可以在相对缓慢的时间尺度上直接改变神经回路的特性。CPG电路的动力学特性是否能直接影响灵活性和环境响应性？从理论研究中可以看出，混沌系统具有固有的特性，这对于产生可变且对环境敏感的输出非常有用。它的输出是高度可变的，但在一个结构化的方式和技术控制的混沌系统现在是众所周知的。同时，生物CPG的实验研究表明，总是存在大量的可变性或抖动。 本项目一方面通过实验研究生物学的可变性，另一方面，开发如何使用混沌系统来赋予运动系统响应灵活性的理论模型。 实验数据收集和模型构建之间存在持续的相互作用。将分析数据的可变性，以确定噪声和确定性-混沌-动力学的相对贡献。两个著名的CPG从龙虾的口胃系统的使用和记录，从这些CPG的小的子电路。最近开发的非线性分析算法用于此分析。使用相同的分析算法研究了CPG内的突触连接的内在神经元动力学的控制。模拟的突触连接将在真实的生物神经元和基于计算机的模型神经元之间构建。将通过使用来自识别的感觉神经元的模拟感觉反馈来研究口胃CPG的动态控制。在这里，通过基于计算机的模型闭合了从CPG到外周和经由再传入回路返回的反馈回路。在这些实验和数据分析的同时，一个基于混沌的模型系统的机器人电机系统的控制，将在模拟开发。它是围绕一个强大的，混沌的核心和一个动态的，sensorimotor控制器，利用最近的混沌控制算法。这种设计和生物感觉运动系统的特性之间有许多相似之处。该项目将扩展我们对生物变异性的作用以及灵活的机器人控制器设计的知识。