CRCNS: Transcortical and spinal circuit contributions to hand shaping in primates - Real-time neuromorphic implementation for robotic demonstration

机器人工程主要依靠规定的算法进行集中控制。这导致机器人的通用性有限，因为每个功能都必须预先编程。相比之下，动物依靠分布在全身的适应性强的神经网络，将大脑信号转换和调节为特定的、协调良好的肌肉动作和纠正。现在已经有可能记录灵长类动物脊髓中控制手部功能部分的这些大型神经网络发出的信号。因此，我们的目标是提取这些神经网络的功能特征，并通过控制仿生机械手和人类尸体的手来验证它们的功能。这一验证将允许对抓取功能的生物学机制进行首次物理测试，并将有助于了解手部残疾和治疗，例如中风、脊髓损伤和脑瘫。它还将推出新一代多功能机器人，这些机器人利用我们的神经系统机制。总体目标是创建一个颈椎的合成功能模拟物，以控制生物机器人手中的多种抓取方式。这是由于专门的大规模并行计算机芯片的出现而成为可能，这种芯片允许实现由数百个模拟神经元及其峰值动态组成的网络（神经形态芯片）。因此，在这个项目中，我们将从灵长类动物（日本）的神经系统中提取用于控制手的网络架构，并将其实现为神经形态电路，以创建一类新的多功能机械手（美国）。使用专门的记录系统，将记录数百个脊髓中间神经元和α运动神经元的神经数据，这些神经数据来自于清醒的、有行为的猴子在操作过程中的颈脊髓，同时也记录了肌电图和手部运动。这将是迄今为止关于手部颈部控制的最完整的数据集（目的1）。然后，我们将使用最先进的大规模集成芯片创建该神经回路的神经形态实现。特别注意将实施生理有效版本的α - γ运动神经元相互作用，和现实的可塑性规则。我们还将创建一种领域特定语言，允许将一般神经解剖学电路翻译成神经形态代码，使一般神经科学界可以使用该技术（目标2）。我们将测试、完善和验证神经形态电路，通过使用神经形态芯片来控制神经机器人的手，使用被编程为肌肉的电动机和传感器来复制肌肉纺锤体和高尔基肌腱器官的功能（目标3）。我们还将控制人类尸体的手来验证神经形态控制器对人类手的解剖。这将为更好地理解手的功能和残疾铺平道路，并为新型神经机械机器人、假肢和脑控手的概念提供证据。日本国立信息通信技术研究所（NICT）正在资助一个伙伴项目。该项目由以下NSF项目联合资助：残疾与康复工程、计算神经科学合作研究、鲁棒智能和思维、机器和运动Nexus项目。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Engineering of robots primarily relies on prescribed algorithms for centralized control. This results in robots with limited versatility because every function must be preprogrammed. Animals, by contrast, rely on adaptable neuronal networks distributed throughout the body that convert and modulate brain signals into specific and well-coordinated muscle actions and corrections. It has now become possible to record signals from these large neuronal networks in primates in the part of the spinal cord controlling hand function. Therefore, our goal is to extract the functional features of these neuronal networks, and validate their function by controlling bio-inspired robotic hands, as well as human cadaveric hands. This validation will allow the first physical test of the biological mechanisms for grasp function, and will help understand hand disabilities and treatments in, for example, stroke, spinal cord injury and cerebral palsy. It will also launch a new generation of versatile robots that use the mechanisms of our nervous system.The overall goal is to create a synthetic functional analogue of the cervical spine that controls multiple grasp modalities in bio-robotic hands. This is made possible by the advent of specialized massively parallel computer chips that allow the implementation of networks of hundreds of simulated neurons and their spiking dynamics (neuromorphic chips). Therefore, in this project, we will extract network architectures for the control of the hand from the nervous system of primates (Japan) and implement them as neuromorphic circuits to create a new class of versatile robotic hands (USA). Using specialized recording system, will record neural data from hundreds of spinal interneurons and alpha motoneurons in the cervical spinal cord of awake, behaving monkeys during manipulation—while also recording EMG and hand kinematics. This will be the most complete data set to date for cervical control of the hand (Aim 1). Then, we will create neuromorphic implementations of that neural circuitry using state of the art very large scale integration chips. Special attention will be paid to implementing physiologically valid versions of alpha-gamma motoneuron interactions, and realistic plasticity rules. We will also create a Domain Specific Language that allows the translation of general neuroanatomical circuits into neuromorphic code to make this technology accessible by the general neuroscience community (Aim 2). We will test, refine and validate the neuromorphic circuits by using the neuromorphic chips to control neuro-robotic hands using electric motors programmed to behave as muscles, and sensors to replicate the function of muscle spindles and Golgi tendon organs (Aim 3). We will also control cadaveric human hands to validate the neuromorphic controller for the anatomy of the human hand. This will pave the way to a better understanding of hand function and disability and serve as the proof of concept for a new class of neuromechanical robotic, prosthetic and brain-controlled hands.A companion project is being funded by the National Institute of Information and Communications Technology, Japan (NICT). This project is jointly funded by the following NSF programs: Disability and Rehabilitation Engineering, Collaborative Research in Computational Neuroscience, Robust Intelligence, and Mind, Machine and Motor Nexus program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.