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感觉反馈对半中心振荡器与简单运动系统耦合的动力学后果。

Dynamical consequences of sensory feedback in a half-center oscillator coupled to a simple motor system.

机构信息

Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, OH, 44106, USA.

Department of Biology, Case Western Reserve University, Cleveland, OH, 44106, USA.

出版信息

Biol Cybern. 2021 Apr;115(2):135-160. doi: 10.1007/s00422-021-00864-y. Epub 2021 Mar 3.

Abstract

We investigate a simple model for motor pattern generation that combines central pattern generator (CPG) dynamics with a sensory feedback (FB) mechanism. Our CPG comprises a half-center oscillator with conductance-based Morris-Lecar model neurons. Output from the CPG drives a push-pull motor system with biomechanics based on experimental data. A sensory feedback conductance from the muscles allows modulation of the CPG activity. We consider parameters under which the isolated CPG system has either "escape" or "release" dynamics, and we study both inhibitory and excitatory feedback conductances. We find that increasing the FB conductance relative to the CPG conductance makes the system more robust against external perturbations, but more susceptible to internal noise. Conversely, increasing the CPG conductance relative to the FB conductance has the opposite effects. We find that the "closed-loop" system, with sensory feedback in place, exhibits a richer repertoire of behaviors than the "open-loop" system, with motion determined entirely by the CPG dynamics. Moreover, we find that purely feedback-driven motor patterns, analogous to a chain reflex, occur only in the inhibition-mediated system. Finally, for pattern generation systems with inhibition-mediated sensory feedback, we find that the distinction between escape- and release-mediated CPG mechanisms is diminished in the presence of internal noise. Our observations support an anti-reductionist view of neuromotor physiology: Understanding mechanisms of robust motor control requires studying not only the central pattern generator circuit in isolation, but the intact closed-loop system as a whole.

摘要

我们研究了一种简单的运动模式生成模型,该模型将中枢模式发生器(CPG)动力学与感觉反馈(FB)机制相结合。我们的 CPG 由具有基于电导的 Morris-Lecar 模型神经元的半中心振荡器组成。CPG 的输出驱动基于实验数据的推挽式电机系统。肌肉的感觉反馈电导允许调制 CPG 活动。我们考虑了孤立的 CPG 系统具有“逃逸”或“释放”动力学的参数,并研究了抑制性和兴奋性反馈电导。我们发现,与 CPG 电导相比,增加 FB 电导会使系统对外部干扰更具鲁棒性,但对内噪声更敏感。相反,增加 CPG 电导相对于 FB 电导具有相反的效果。我们发现,具有感觉反馈的“闭环”系统比完全由 CPG 动力学决定运动的“开环”系统表现出更丰富的行为 repertoire。此外,我们发现仅由反馈驱动的运动模式,类似于链反射,仅在抑制介导的系统中发生。最后,对于具有抑制介导的感觉反馈的模式生成系统,我们发现,在存在内部噪声的情况下,逃逸和释放介导的 CPG 机制之间的区别减弱了。我们的观察结果支持神经运动生理学的反简化论观点:理解强大的运动控制机制不仅需要单独研究中枢模式发生器电路,还需要整体研究完整的闭环系统。

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