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

描述（由申请人提供）：伸展反射弧（SRA）是姿势控制和肌肉收缩的最简单和最基本的调节机制。 了解这个重要的生物控制系统的功能细节可以（a）导致神经肌肉疾病如肌萎缩性侧索硬化症（ALS）的早期检测/治疗的新工具，（B）帮助解释某些病理状况，如脊髓损伤（SCI）继发的痉挛，以及（c）导致新的计算机控制系统的开发（自适应传感器、非线性控制器、机器人中的新型运动控制等）。 在拟议的研究的总体目标是建立一个数据真实的非线性动力学模型的SRA和检查的影响，调制神经传递的整体稳定性的SRA。 我们的具体目标是：1. 通过在一个明确的体外试验床中使用电生理和力学测量来表征SRA的基本元件（DRG细胞、运动神经元、骨骼肌）和子系统（即DRG AE运动神经元、运动神经元AE肌肉）的非线性动力学。 2. 通过利用目标1中获得的组件模型，并将其与文献中的标准模型相结合，针对我们实验室中无法获得培养物的组件，在模拟中重新创建SRA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运动神经元段非线性动力学的影响。 4. 比较单胺能驱动增加与健康条件下SRA的整体动态响应。 为了实现我们的具体目标，实验，分析和计算机模拟技术的汇合将被利用。 广泛地说，用于建模SRA组件的实验将涉及以电流钳模式向膜片钳细胞中注入带限白色噪声电流，同时记录动作电位（或肌肉收缩力）。 模拟子系统的实验将使用与上述相似的方法，不同之处在于将获得突触前和突触后细胞上的双膜片钳记录。 分析将涉及线性和非线性滤波器（内核）方面的组件或子系统模型的量化-优化技术将用于限制模型的复杂性。 获得的非线性组件和子系统模型将在计算机模拟中接口，以重新创建SRA的整体实验观察行为。 公共卫生相关性：牵张反射弧（SRA）的直接或间接参与已经涉及诸如ALS、帕金森病的疾病以及脊髓损伤后痉挛的产生。 对SRA的动态非线性行为及其神经调节的更深入理解可以（a）帮助理解这些疾病的运动症状的发展，（B）导致早期检测的新方法，以及（c）提供可能治疗的有效性的非侵入性监测的新策略。 SRA的非线性动态模型对于生物和人造组件之间的任何接口的开发也至关重要-无论是神经驱动的假肢还是网络驱动的肌肉组织。

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.