Visuomotor Prosthetic for Paralysis

瘫痪视觉运动假肢

• 批准号: 10090436
• 负责人: RICHARD A ANDERSEN
• 金额: $ 77.59万
• 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/10090436
• 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; 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.

拟议的研究的目的是获得视觉运动转化的科学知识 在临床中的四脑受试者的后顶叶皮层（PPC）和原发性运动皮层（M1）中 试验以推动神经假体的发展。我们已经在进行的临床试验中显示 PPC可以控制神经假体以协助四边形受试者的6年。其他小组 已经集中在M1上，并同样找到控制神经假体的控制。在我们对PPC的研究中，我们有 发现除了移动机器人四肢或控制计算机光标的轨迹信号外，还有一个 代表大多数身体的预期运动，运动的众多视觉运动信号 目标，认知策略甚至记忆信号。我们的中心假设是PPC和M1将 用相似和不同的方式编码视觉运动参数，并且算法可以是 开发的目的是利用这两个领域的信号，以提高假肢 范围和性能。植入物将在M1和PPC中进行，以同时记录 相同的主题，提高了比较来自不同实验室的数据的关注点 具有不同植入物和不同任务的个人。 该中心假设将以两个广泛的目的进行检验，我们拥有大量的初步数据。 AIM 1将检查两个区域对身体的控制。假设M1将 证明对侧肢体的特异性很强（植入物将在手旋钮中制成） 而PPC将对大多数身体以及对立和同侧的编码运动进行编码 利用其部分混合的参数编码（Subaim 1A）。而M1被认为是代码 空间变量仅在尝试或想象的动作期间，假设PPC也是如此 在适当的参考帧（Subaim 1b）中编码认知空间变量。在Subaim 1C中 将研究如何在运动表示中组合多个身体部位，假设 M1和PPC将采用多种机制，包括线性求和，非线性 组合和运动抑制以不同的方式表达，作为大脑区域的功能 特定运动集。 AIM 2将检查两个领域编码的时间方面。在Subaim 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没有改变 这两个领域。在Subaim 2b中，我们假设在顺序运动中，M1仅代码 持续的运动，而PPC则代码当前和后续运动。最后，在Subaim 2C我们将检查运动速度的编码，并假设有不同 M1和PPC中的子空间，用于运动的方向和速度。