Multiscale models of proprioceptive encoding to reveal mechanisms of impaired sensorimotor control

本体感觉编码的多尺度模型揭示感觉运动控制受损的机制

• 批准号: 10612452
• 负责人: Timothy C Cope
• 金额: $ 58.24万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-16 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10612452
• 关键词: Address; Affect; Biological; Biomechanics; Biophysics; Cerebral Palsy; Clinical; Clinical assessments; Computer Models; Consensus; Coupling; Data; Decerebration procedure; Diagnosis; Diagnostic; Disease; Dissociation; Dyskinetic syndrome; Dystonia; Electromyography; Funding; Goals; Health; Human; Hyperreflexia; Impairment; Individual; Joints; Lead; Left; Leg; Limb structure; Measures; Mechanics; Methods; Modeling; Motion; Motor; Motor output; Movement; Movement Disorders; Muscle; Muscle Fibers; Muscle Hypertonia; Muscle Spindles; Muscle Tension; Nervous System Physiology; Neurologic; Neuromechanics; Neurosciences; Organ; Parkinson Disease; Parkinsonian Disorders; Physics; Preparation; Property; Rattus; Research; Resistance; Robotics; Role; Sensory; Severities; Signal Transduction; Spinal; Spinal cord injury; Stretching; Stroke; Symptoms; System; Tendon structure; Testing; Tissues; Validation; Vertebral column; Work; biological systems; biomechanical model; biophysical model; clinically relevant; in silico; in vivo; insight; instrument; kinematics; motor impairment; multi-scale modeling; nervous system disorder; neural; neuromechanism; neuromuscular; novel; predictive signature; robotic system; sensory input; simulation; spasticity; treatment strategy; virtual; virtual reality

PROJECT SUMMARY Our long-term goal is to identify neural mechanisms and the functional roles of sensorimotor signals in health and disease as needed to guide mechanistically targeted diagnoses, assessments, and treatments for neurological movement disorders. Here we address the scientific barriers to understanding and treating a broad class of movement disorder symptoms recently defined as joint hyper-resistance, which encompass spasticity in stroke, spinal cord injury, or cerebral palsy; parkinsonian rigidity, and hypertonia. The objective of this collaborative, interdisciplinary proposal is to identify neural mechanisms of hyper-resistance and dissociate their relative roles in abnormal movement. We will focus on the neural mechanisms underlying two clinically- defined neural contributions to hyper-resistance: non-velocity dependent involuntary background activation and velocity-dependent stretch hyper-reflexia. We hypothesize that increased spinal excitability in many neurological disorders causes involuntary background activation and velocity-dependent stretch hyper-reflexia via three dissociable neural mechanisms: 1) alpha-drive to extrafusal muscle fibers increasing background muscle tension, 2) gamma-drive to specialized intrafusal muscle fibers in muscle spindles sensory organs, increasing their sensitivity to muscle stretch, and 3) sensorimotor gain of the spinal transformation of monosynaptic sensory input into motor output. Our proposed tests of this hypothesis will advance understanding of the important, yet still unresolved relative contributions made by these neural mechanisms to hyper-resistance. Based on our neuromechanical and multiscale modeling advances in the prior funding period, in Aim 1 we will develop a multiscale in silico neuromuscular circuit model to predict how independent changes in alpha- drive, gamma-drive, and sensorimotor gain differentially affect clinically-relevant movements such as the tendon tap and pendulum test. In Aim 2, we will characterize the relative increases in alpha-drive, gamma-drive, and sensorimotor gain across clinically-relevant spinal excitability levels in a living biological neuromuscular circuit in vivo using a decerebrate rat preparation. In Aim 3 we will identify clinically-relevant movement abnormalities across spinal excitability levels in a novel biohybrid robotic system coupling the living neuromuscular circuit (in vivo) to a virtual biomechanical limb (in silico). A robotic controller will enforce the physics of dynamically changing inertial and gravitational forces, allowing movement to emerge from the causal interaction between the in vivo neuromuscular circuit and the virtual limb. Through the close coordination of these Aims, we will establish a computational and experimental framework to address clinical barriers (1) to determine how changes in neural mechanisms and the inertial properties of the limb could correct movement abnormalities, (2) to provide insight into how these mechanisms could be identified through different clinical assessment scenarios, and (3) to compare the relative effects of different treatment targets. The proposed work will likely impact both clinically-relevant human sensorimotor research and basic sensorimotor neuroscience.

项目概要 我们的长期目标是确定神经机制和感觉运动信号在健康中的功能作用 根据需要指导有针对性的诊断、评估和治疗 神经性运动障碍。在这里，我们解决理解和治疗疾病的科学障碍 广泛的运动障碍症状最近被定义为关节过度抵抗，其中包括 中风、脊髓损伤或脑瘫引起的痉挛；帕金森病强直和张力亢进。的目标 这项跨学科的协作提案旨在确定过度抵抗和解离的神经机制 它们在异常运动中的相对作用。我们将重点关注两种临床基础的神经机制： 定义的神经对超阻力的贡献：非速度依赖的非自愿背景激活和 速度依赖性牵张反射亢进。我们假设许多人的脊髓兴奋性增加 神经系统疾病导致不自主的背景激活和速度依赖性牵张反射亢进 通过三种可分离的神经机制：1）对梭外肌纤维的α驱动增加背景 肌肉张力，2) 对肌梭感觉器官中专门的梭内肌纤维的伽马驱动， 增加他们对肌肉拉伸的敏感性，以及3）脊柱转化的感觉运动增益 单突触感觉输入转化为运动输出。我们提出的对这一假设的测试将促进理解 这些神经机制对过度抵抗做出的重要但尚未解决的相对贡献。 基于我们在上一个资助期间的神经力学和多尺度建模进展，在目标 1 中，我们将 开发多尺度计算机神经肌肉回路模型来预测 α- 的独立变化 驱动、伽马驱动和感觉运动增益对临床相关运动（例如肌腱）的影响存在差异 敲击和摆锤测试。在目标 2 中，我们将描述 alpha 驱动、gamma 驱动、 和感觉运动增益在活体生物体中临床相关的脊髓兴奋性水平 使用去脑大鼠制剂进行体内神经肌肉回路。在目标 3 中，我们将确定临床相关的 新型生物混合机器人系统耦合中脊柱兴奋性水平的运动异常 活体神经肌肉回路（体内）到虚拟生物力学肢体（计算机）。机器人控制器将强制执行 动态改变惯性力和重力的物理学，允许运动从 体内神经肌肉回路和虚拟肢体之间的因果相互作用。通过密切协调 在这些目标中，我们将建立一个计算和实验框架来解决临床障碍 (1) 确定神经机制和肢体惯性特性的变化如何纠正运动 异常，（2）深入了解如何通过不同的临床来识别这些机制 评估情景，以及（3）比较不同治疗目标的相对效果。拟议的工作 可能会影响临床相关的人类感觉运动研究和基础感觉运动神经科学。