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: 10385747
• 负责人: Sridevi V. Sarma
• 金额: $ 33.26万
• 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/10385747
• 关键词: Affect; Agonist; Amyotrophic Lateral Sclerosis; Anatomy; Animals; Architecture; Area; Behavioral; Biological Models; Brain; Brain region; Cerebellum; Cheetahs; Data; Dependence; Derivation procedure; Device Designs; Devices; Disease; Feedback; Financial compensation; Frequencies; Generations; Goals; Injections; Injury; Joints; Lead; Lidocaine; Modeling; Modernization; Monkeys; Motor; Motor Cortex; Motor Neurons; Movement; Movement Disorders; Multiple Sclerosis; Muscimol; Muscle; Neurons; Outcome; Paresis; Parkinson Disease; Patients; Performance; Physiologic pulse; Play; Primates; Process; Research; Role; Running; Self-Help Devices; Signal Transduction; Speed; Spinal Cord; Spinal cord injury; Stroke; System; Testing; Theoretical model; Torque; Training; Translations; antagonist; arm; control theory; density; design; exoskeleton; experimental study; neural prosthesis; neurophysiology; neuroprosthesis; nonhuman primate; performance tests; programs; receptor; relating to nervous system; skills; theories; transmission process; visual feedback

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.

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。在动物中 王国，背景包括追逐猎物的捕食者的行动 速度，就像追逐瞪羚的猎豹一样。感觉运动控制系统（SC）负责此类 动作及其性能显然取决于神经元的计算能力，大脑和大脑之间的延迟 肌肉和肌肉动力学。尽管有这些明显的因素，这些因素限制了速度 动物可以跟踪移动的物体，跟踪SC的性能及其对神经的依赖性 尚未明确量化计算，延迟和肌肉动力学。在这个程序中，我们将建立 根据使用反馈控制原理和适当简化的模型开发的新理论 SC确定神经计算，延迟和肌肉在快速运动的产生过程中如何相互作用。 因此，如果一个组件被妥协，我们可以利用其他组件来还原 带有辅助神经假体设备的运动性能。 程序目标是首先参数化主要因素（大脑和身体）限制快速运动 并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， 参数化和量化的相互作用将在受试者中通过实验测试 操纵（i）神经计算能力，（ii）传播延迟和（iii）肌肉动力学。如果 实验与理论之间存在差异，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 将利用通过“促进”其他参数的赔偿来应用赔偿，以解释某些参数的退化。 更具体地说，我们将为受到神经受损的受试者设计辅助神经假体设备 房地产以恢复快速运动的性能。例如，如果一级运动皮层受到损害 由于疾病或损害，我们可以通过添加必要的补偿性来操纵肌肉动力学 恢复运动性能的力量，更重要的是恢复快速而敏捷的运动。就是一个 应该通过我们的SCS模型和理论来告知补偿。