CRCNS: MOVE!-MOdeling of fast Movement for Enhancement via neuroprosthetics

CRCNS：MOVE！-通过神经修复术增强快速运动建模

• 批准号: 10352692
• 负责人: Sridevi V. Sarma
• 金额: $ 6.77万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10352692
• 关键词: Affect; Amyotrophic Lateral Sclerosis; Animals; Architecture; Biological Models; Brain; Cheetahs; Data; Dependence; Device Designs; Devices; Disease; Feedback; Financial compensation; Generations; Injury; Lead; Modeling; Modernization; Motor; Motor Cortex; Movement; Movement Disorders; Multiple Sclerosis; Muscle; Neurons; Paresis; Parkinson Disease; Patients; Performance; Play; Role; Running; Speed; Spinal cord injury; Stroke; System; Testing; Theoretical model; control theory; design; experimental study; neuroprosthesis; programs; relating to nervous system; skills; theories; transmission process

PROJECT SUMMARY Tracking fast unpredictable movements is a valuable skill, applicable in many situations. In the animal kingdom, the context includes the action of a predator chasing its prey that is running and dodging at high speeds, like a cheetah chasing a gazelle. The sensorimotor control system (SCS) is responsible for such actions and its performance clearly depends on the computing power of neurons, delays between brain and muscles, and the dynamics of muscles involved. Despite these obvious factors that set the limits on how fast an animal can track a moving object, tracking performance of the SCS and its dependence on neural computing, delays, and muscle dynamics have not been explicitly quantified. In this program, we will build upon new theory developed using feedback control principles and an appropriately simplified model of the SCS to identify how neural computing, delays, and muscles interact during the generation of fast movements. Therefore if one component is compromised, we can take advantage of the other components to restore motor performance with assistive neuroprosthetic devices. The program objectives are to first parameterize the major factors (brain and body) limiting fast movements and to derive how these parameters must interact to achieve tracking of fast movements in the SCS. Then, the parameterization and quantified interactions will be tested experimentally in subjects through manipulation of (i) neural computing power, (ii) transmission delays, and (iii) muscle dynamics. If discrepancies emerge between experiments and theory, the SCS model and theory will be modified to explain observation data. Finally, the theoretical model of interactions required to achieve tracking of fast movements will be exploited to apply compensation to account for degradation of some parameters by “boosting” others. More specifically, we will design assistive neuroprosthetic devices for subjects having compromised neural real estate to restore performance of fast movements. For example, if primary motor cortex is compromised due to disease or damage, we can manipulate muscle dynamics by adding the necessary compensatory forces to restore motor performance, and more importantly restore fast and agile movements. Just how one should compensate will be informed by our SCS model and theory.

项目摘要 跟踪快速不可预测的动作是一项有价值的技能，适用于许多情况。在动物界， 上下文包括捕食者追逐其猎物的动作，该猎物正在高速运行，就像一个 猎豹追赶瞪羚。感觉运动控制系统（SCS）负责此类行动及其 性能显然取决于神经元的计算能力，大脑和肌肉之间的延迟以及 涉及肌肉的动力学。尽管有这些明显的因素，这些因素限制了动物可以跟踪的速度 移动的对象，跟踪SC的性能及其对神经计算，延迟和肌肉的依赖 动力学尚未明确量化。在此计划中，我们将基于使用 反馈控制原则和SC的适当简化模型，以确定神经计算的方式， 延迟和肌肉在快速运动的产生过程中相互作用。因此，如果一个组件是 受到妥协，我们可以利用其他组件以辅助恢复运动性能 神经假体设备。 程序目标是首先参数化主要因素（大脑和身体），以限制快速运动和 为了得出这些参数必须如何相互作用以实现SC中快速运动的跟踪。然后， 参数化和量化相互作用将通过操纵（i）进行实验测试。 神经计算能力，（ii）传播延迟和（iii）肌肉动力学。如果在 实验和理论，SCS模型和理论将被修改以解释观察数据。最后， 实现快速运动所需的互动的理论模型将被利用以应用 通过“增强”其他参数来解释某些参数的赔偿。更具体地说，我们将 设计辅助神经假体设备，用于损害神经遗产以恢复的受试者 快速运动的性能。例如，如果因疾病或损害而损害一级运动皮层， 我们可以通过添加必要的补偿力来恢复电动机来操纵肌肉动力学 性能，更重要的是恢复快速而敏捷的运动。一个人应该如何补偿 由我们的SCS模型和理论告知。