神经系统运动节律的调控机制及电路设计

The motion control function of the nervous system is achieved through the motor rhythm generated by the central pattern generator (CPG) which is a network mainly coupled by the inhibitory synapse and is closely related to the mechanics discipline, but it has received relatively little attention, especially compared with the sensory and cognitive functions. Based on the recent experimental observations wherein the hyperpolarization activated inward cation ion flow Ih and the fast transient outward potassium ion current IA were found to play important roles in the regulation of the motor rhythm, a new neuron model and a small scale inhibitory coupled network model to simulate the CPG that controls the motion of the lobster’s stomach will be built in the present project. The content of the project will contain: to reveal the regulation mechanism of Ih and IA separately and synthetically on the rhythm of single neurons and the motor rhythm of the network with nonlinear dynamical methods, and to pay special attention to the interaction between the hyperpolarization activation characteristic of Ih and the inhibitory coupling current and the compensation effect between Ih and IA; to study the maintenance capacity of the motor rhythm to the modulation of the dynamical factors such as the coupling time delay, noise, and electromagnetic induction/interference, and the changes induced by these factors; based on the mathematical models, to design the analog circuit and the FPGA circuit for the single neuron and the CPG, to test the dynamical behaviors of the theoretical model with the circuits, to improve the performance of the circuit to a high level enough to perform the system integration. The results of the project will help to understand the regulation mechanism of the motor rhythm deeply and comprehensively and lay the foundation for the motion control like the robots.

神经系统的运动控制功能是通过中枢模式发生器-抑制耦合为主的网络-产生的运动节律实现的，与力学学科密切相关，但与感觉和认知功能相比受到的关注较少。本研究基于近期实验发现的超极化激活的内向阳离子流Ih和快速瞬态外向钾电流IA对运动节律有重要的调控作用，构建新的神经元模型和抑制耦合的小规模网络模型来模拟控制龙虾胃运动的中枢模式发生器，进行以下研究：利用非线性动力学方法揭示Ih和IA流各自和综合作用对神经元节律和网络运动节律的调控机制，特别关注Ih流的超极化激活特性与抑制耦合电流交互作用以及Ih和IA流的相互补偿作用；研究运动节律在动力学因素如耦合时滞、噪声和电磁感应/干扰作用下的维持能力和变化；基于神经元和中枢模式发生器的数学模型进行模拟电路和FPGA电路设计，测试理论模型的动力学行为，完善电路性能并进行系统集成。研究有助于全面和深入认识运动节律的调控机制，为服务于类似机器人的运动控制奠定基础。

除众所周知的感觉和认知功能，神经系统还通过运动节律实现运动控制功能。神经系统的运动节律涉及神经元和网络的复杂非线性和时空动力学，在机器人运动控制中具有应用前景。本项目通过数学建模、数值计算和理论分析相结合，研究多因素调控下的运动节律的复杂动力学，并进行了电路设计。首先，构建含有Ih流（超极化激活的阳离子流）的神经元模型，揭示Ih流等对神经元电活动行为的影响，包括抬升膜电位和改变峰/簇放电节律模式，鞍结分岔变为Hopf分岔、结点变为焦点及对应焦点的衰减振荡的频率/周期的改变，调节阈下共振的强弱和频率，以及诱发抑制后反跳(PIR)放电等违反直觉的动力学行为，并进一步揭示了PIR与分岔和平衡点类型的关系，为认识运动节律奠定了理论基础。其次，通过电流分解、分岔分析及PIR机制分析，揭示了Ih流与抑制性突触流联合调控耦合神经元网络的运动节律的复杂动力学：抑制性突触阈值较低时，增强Ih流的电导会引起反相同步节律的周期降低、频率变快；抑制性突触阈值较高时，增强Ih流的电导会引起反相同步节律的周期增加、频率变慢；提供了调控运动节律的有效措施。通过规范型分析揭示了兴奋性/抑制性耦合网络的运动节律在反相与同相同步间的转迁的反常现象及复杂动力学机制，利用分岔和相位响应曲线揭示了抑制性自反馈诱发的网络的超前同步及促进网络节律的相干共振的PIR机制，给出了调控运动节律的新手段。再次，揭示了自反馈、忆阻、噪声和时滞等调控下神经元峰/簇放电节律及网络同步和时空行为的动力学响应，包括抑制性自反馈增强放电、兴奋性自反馈降低放电等反常现象及相应的分岔机制，完善了兴奋-抑制平衡机制，揭示了兴奋或抑制调控的新功能。最后，对自反馈/忆阻调控下的运动节律及其变化进行了电路设计，验证了数学模型的结果，为利用节律控制运动奠定了基础。研究结果全面、深入认识了运动节律的生成机制和调控手段，为运动机器人的仿生控制奠定了基础。共发表 SCI 期刊论文 46 篇，培养研究生 8名。