Non-linear Characterization of the Stretch Reflex Arc and its Neuromodulation

描述(申请人提供)：伸展反射弧(SRA)是姿势控制和肌肉收缩最简单和最基本的调节机制。了解这一重要生物控制系统的功能细节可以(A)产生早期发现/治疗肌萎缩侧索硬化症(ALS)等神经肌肉疾病的新工具，(B)有助于解释某些病理情况，如继发性脊髓损伤(SCI)的痉挛，以及(C)导致新型硅控制系统(自适应传感器、非线性控制器、机器人中的新型运动控制等)的发展。本研究的总体目标是建立SRA的数据真实非线性动力学模型，并考察调节性神经传递对SRA整体稳定性的影响。我们的具体目标是：1.在一个良好的体外实验台上，通过电生理和力学测量来表征SRA的基本成分(DRG细胞、运动神经元、骨骼肌)和亚系统(即DRG-AE运动神经元、运动神经元-AE肌)的非线性动力学。2.利用在Aim 1中获得的组件模型，并将这些组件模型与文献中的标准模型进行集成，以重建SRA在模拟中的整体动态响应。3.量化神经递质5-羟色胺和去甲肾上腺素对DRG-AE运动神经元节段非线性动力学的影响。4.比较单胺类递增驱动与健康状态下SRA的整体动态反应。为了实现我们的具体目标，将利用实验、分析和计算机模拟技术的融合。宽泛地说，模拟SRA成分的实验将包括以电流钳模式向膜片钳细胞注入带限白噪声电流，同时记录动作电位(或肌肉的收缩力量)。模拟子系统的实验将使用与上述类似的方法，不同之处在于将获得突触前和突触后细胞的双膜片钳记录。分析将涉及按照线性和非线性过滤器(核)对组件或子系统模型进行量化--将利用优化技术来限制模型的复杂性。获得的非线性部件和子系统模型将在计算机模拟中对接，以重现通过实验观察到的SRA的总体行为。公共卫生相关性：伸展反射弧(SRA)的直接或间接参与与ALS、帕金森氏病等疾病以及脊髓损伤后痉挛的产生有关。更深入地了解SRA的动态非线性行为及其神经调节可以(A)帮助了解这些疾病的运动症状的发展，(B)导致早期发现的新方法，以及(C)为非侵入性监测可能的治疗效果提供新的策略。SRA的非线性动态模型对于开发生物和人造部件之间的任何接口也将是至关重要的--无论是神经驱动的假肢还是网络驱动的肌肉系统。

DESCRIPTION (provided by applicant): The Stretch Reflex Arc (SRA) is the simplest and most fundamental regulatory mechanism of posture control and muscle contraction. Understanding the details of the functioning of this important biological control system could (a) result in novel tools for the early detection/therapies of neuromuscular diseases such as Amyotrophic Lateral Sclerosis (ALS), (b) help explain certain pathological conditions such as spasticity that are secondary to Spinal Cord Injury (SCI), as well as (c) lead to the development of novel in-silico control systems (adaptive sensors, non-linear controllers, novel movement control in robotics, etc). The overall goal in the proposed study is to establish a data-true non-linear dynamic model of the SRA and examine the effects of modulatory neurotransmission on the overall stability of the SRA. Our specific aims are: 1. To characterize the nonlinear dynamics of the basic elements (DRG cells, motoneurons, skeletal muscle) and subsystems (namely, DRG AE motoneuron, motoneuron AE muscle) of the SRA by using electrophysiological and mechanical measurements in a well defined in vitro test bed. 2. To recreate the overall dynamic response of the SRA in simulation by utilizing component models obtained in aim 1 and integrating those with standard models from literature for components for which cultures are not available in our laboratory. 3. To quantify the effect of the neurotransmitters serotonin and norepinephrine on the non-linear dynamics of the DRG AE motoneuron segment. 4. To compare the overall dynamic response of the SRA under increased monoaminergic drive with that obtained under healthy conditions. Towards achieving our specific aims, the confluence of experimental, analytical, and computer simulation techniques will be exploited. Broadly, experiments for modeling SRA components will involve bandlimited white noise current injection in current clamp mode into patch-clamped cells with concurrent recording of action potentials (or contraction force in the case of the muscle). Experiments for modeling subsystems will use similar methodology as stated above except that dual patch clamp recordings on a presynaptic and a postsynaptic cell will be obtained. Analysis will involve quantification of component or subsystem models in terms of linear and non-linear filters (kernels) - optimization techniques will be utilized to restrict the complexity of the models. Nonlinear component and subsystem models obtained would be interfaced in computer simulation to recreate the overall experimentally observed behavior of the SRA. PUBLIC HEALTH RELEVANCE: The direct or indirect involvement of the stretch reflex arc (SRA) has been implicated in diseases such as ALS, Parkinson's disease and in generation of spasticity after Spinal Cord Injury. Deeper understanding of the dynamic non-linear behavior of the SRA and its neuromodulation could (a) help to understand the development of the motor symptoms of these diseases, (b) result in novel methods for early detection, and (c) offer novel strategies for noninvasive monitoring of the effectiveness of possible therapies. A non-linear dynamic model of the SRA would also be of critical importance to the development of any interface between biological and man-made components - be it neuronally driven prosthetics or cyber driven musculature.