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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

基本信息

批准号：
10436158
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
项目类别：
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/10436158
关键词：
Address Affect Biological Biomechanics Biophysics Cerebral Palsy Cerebrum Clinical Clinical assessments Computer Models Consensus Coupling Data Diagnosis Diagnostic Disease Dyskinetic syndrome Dystonia Electromyography Funding Goals Gravitation 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 Validation Work base biological systems biomechanical model biophysical model clinically relevant in silico in vivo insight instrument kinematics motor impairment multi-scale modeling nervous system disorder neuromechanism neuromuscular novel predictive signature relating to nervous system robotic system sensory input simulation spasticity treatment strategy virtual virtual reality

项目摘要

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.

项目总结