Visuomotor Prosthetic for Paralysis

瘫痪视觉运动假肢

• 批准号: 10399978
• 负责人: RICHARD A ANDERSEN
• 金额: $ 73.7万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10399978
• 关键词: Accidents; Address; Advanced Development; Algorithms; Amyotrophic Lateral Sclerosis; Anatomy; Area; Ballistics; Behavioral; Body mass index; Body part; Brain; Brain region; California; Clinical Trials; Code; Cognitive; Complex; Computers; Conduct Clinical Trials; Contralateral; Data; Development; Devices; Electrodes; FDA approved; Freedom; Future; Goals; Hand; Healthcare; Hospitals; Human; Implant; Individual; Institutes; Ipsilateral; Joints; Knowledge; Limb structure; Los Angeles; Medical Device; Memory; Microelectrodes; Motor; Motor Cortex; Movement; Multiple Sclerosis; Neurons; Outcome; Paralysed; Parietal Lobe; Participant; Patient Recruitments; Patients; Pattern; Performance; Peripheral Nervous System Diseases; Persons; Phase; Population; Property; Prosthesis; Prosthesis Design; Quadriplegia; Quality of life; Research; Research Design; Robotics; Sampling; Self-Help Devices; Side; Signal Transduction; Site; Specificity; Speed; Spinal Cord Lesions; Stroke; System; Technology; Testing; Time; Translating; Universities; Vision; Volition; Work; arm; design; experimental study; improved; medical schools; motor behavior; neural prosthesis; neurophysiology; neuroprosthesis; neuroregulation; neurosurgery; practical application; relating to nervous system; visual motor

The objective of the proposed research is to obtain scientific knowledge of visuomotor transformations in posterior parietal cortex (PPC) and primary motor cortex (M1) from tetraplegic subjects in a clinical trial to advance the development of neural prosthetics. We have shown in clinical trials conducted over the past 6 years that PPC can control neural prosthetics for assisting tetraplegic subjects. Other groups have concentrated on M1 and likewise find control for neural prosthetics. In our studies of PPC we have found that besides trajectory signals to move robotic limbs or control computer cursors, there are a plethora of visuomotor signals that represent intended movements of most of the body, movement goals, cognitive strategies, and even memory signals. Our central hypothesis is that PPC and M1 will encode visuomotor parameters in both similar and different ways, and that algorithms can be developed to leverage those signals from the two areas that are complimentary to improve prosthetic range and performance. Implants will be made in both M1 and PPC, enabling simultaneous recording in the same subjects, elevating concerns of comparing data from different labs collected in different individuals with different implants and different tasks. This central hypothesis will be tested in two broad aims, for which we have substantial preliminary data. Aim 1 will examine the control of the body by the two areas. It is hypothesized that M1 will demonstrate strong specificity for the contralateral limb (implants will be made in the hand knob) whereas PPC will code movements for most of the body and on both contra and ipsilateral sides by leveraging its partially mixed encoding of parameters (subaim 1a). Whereas M1 is hypothesized to code spatial variables exclusively during attempted or imagined actions, it is hypothesized that PPC also encodes cognitive spatial variables in task appropriate reference frames (subaim 1b). In subaim 1c we will examine how multiple body parts are combined in movement representations, hypothesizing that M1 and PPC will employ a diverse set of mechanisms including linear summation, non-linear combinations, and movement suppression expressed in different ways as a function of brain area and the specific movement set. Aim 2 will examine the temporal aspects of encoding in the two areas. In subaim 2a we will test the hypothesis that the neural dynamics during sustained periods of movement are largely unchanging in both areas. In subaim 2b we hypothesize that, during sequential movements, M1 codes only the ongoing movement whereas PPC codes both the current and subsequent movements. Finally, in subaim 2c we will examine the coding of movement speed, with the hypothesis that there are separate subspaces in both M1 and PPC for direction and speed of movement.

拟议研究的目的是获得视觉转换的科学知识 在一个临床研究中，来自四肢瘫痪受试者的后顶叶皮层（PPC）和初级运动皮层（M1） 推进神经修复术发展的试验我们已经在临床试验中证明， 在过去的6年里，PPC可以控制神经假肢，以协助四肢瘫痪的主题。其他群体 专注于M1，并同样找到了神经修复的控制。在我们对PPC的研究中， 发现除了移动机器人肢体或控制计算机光标的轨迹信号外， 过多的视觉信号代表了身体大部分的预期运动， 目标，认知策略，甚至记忆信号。我们的中心假设是PPC和M1将 以类似和不同的方式对可视化参数进行编码，并且算法可以 开发利用这些信号从两个领域是互补的，以改善假肢 范围和性能。植入物将在M1和PPC中制造，从而能够同时记录 相同的主题，提高了对不同实验室收集的数据进行比较的关注， 不同植入物和不同任务的个体。 这一中心假设将在两个广泛的目标中得到检验，我们有大量的初步数据。 目标1将检查两个区域对身体的控制。假设M1将 证明对侧肢体具有很强的特异性（将在手柄中制造植入物） 而PPC将编码身体大部分以及对侧和同侧的运动， 利用其参数的部分混合编码（子目标1A）。假设M1编码为 空间变量专门在尝试或想象的行动，它是假设，PPC也 在任务适当的参考框架中编码认知空间变量（子目标1b）。在子目标1c中， 将研究多个身体部位如何在运动表征中组合，假设 M1和PPC将采用一组不同的机制，包括线性求和、非线性 组合，以及以不同方式表达的运动抑制作为脑区的函数， 具体的动作设置。 目标2将研究这两个领域中编码的时间方面。在子目标2a中，我们将测试 假设在持续运动期间的神经动力学在很大程度上是不变的， 这两个领域。在子目标2b中，我们假设，在顺序运动期间，M1仅编码 正在进行的运动，而PPC编码当前和随后的运动。最后，在Subaim中， 2c我们将检查运动速度的编码，假设存在单独的 M1和PPC中的子空间用于移动方向和速度。