Fully Implantable and Programmable Spike-based Codecs for Neuroprosthetics

描述（由申请人提供）：全世界有数百万人患有神经损伤和疾病，导致严重的运动障碍。残疾往往是如此严重，以至于无法养活自己或随时沟通。在过去的十年中，一种名为脑机接口（BMI）的新型医疗系统已经从研究实验室中出现，现在正准备大大改善这些患者的生活质量。BMI直接从大脑中的运动结构“读出”神经电活动，并解码这些电脉冲，以确定预期的运动。控制计算机光标的BMI系统的初始版本现在处于FDA I期临床试验中，并且许多机构积极参与临床翻译（例如，NIH，DARPA，VA）。创建控制信号，使截肢者能够用假肢（机器人）手臂和手养活自己，需要解码来自数千个电极的信号，而不是当前系统读取的数百个信号，以及将来自手臂和手的数千个传感器信号编码成数千个人工神经信号，以“写入”大脑，这还没有尝试过。缺乏运行BMI编码和解码算法（称为编解码器）所需的低功耗（以便植入）电子电路是成功临床翻译的根本障碍。到目前为止，可用的技术太耗电（数字）或算法太不灵活（模拟），无法应对挑战。神经形态工程学的最新进展使构建完全可植入和可编程的编解码器芯片成为可能。这种创新的方法结合了数字和模拟的最佳特性-可编程性和效率-同时提供比任何一种都更强大的鲁棒性。与此同时，神经科学技术的最新进展使我们有可能获得设计在编解码器芯片上运行的正确算法所需的知识。光遗传刺激现在可以用来驱动猕猴皮质中的神经元，计算机视觉现在可以用来跟踪自由移动的猴子，同时进行无线记录。我们建议利用这些最新的进展，通过以下原则性设计来显着提高假肢性能：（1）一种全新的编码器，可以通过光遗传学技术对神经活动进行时空模式化。(2)一种全新的解码器，可以在真实的世界中运行，动物可以在远没有那么受约束的环境中自由移动。(3)一种全新的植入式可编程电子设备，可以达到运行这些复杂算法所需的能效水平。我们将展示我们的成功，让一个自由活动的灵长类动物，在其前运动皮层和体感皮层分别植入了一个96微电极记录阵列和一个9通道光遗传刺激器，控制一个类似人类的机器人手臂。我们的最终目标是实现神经形态工程师的梦想：用像大脑一样工作的芯片替换受损的神经组织，帮助无数患有神经损伤的人。

DESCRIPTION (provided by applicant): Millions of people worldwide suffer from neurological injury and disease resulting in profound movement impairment. Often the disability is so severe that it is not possible to feed oneself or readily communicate. A new class of medical system termed brain-machine interfaces (BMIs) has emerged from research labs in the past decade and is now poised to dramatically improve these patients' quality of life. BMIs "read out" neural electrical activity directly from motor structures in the brain and decode these electrical impulses in order to determine the intended movement. Initial versions of BMI systems that control a computer cursor are now in FDA Phase-I clinical trials, and numerous agencies are actively engaged in clinical translation (e.g., NIH, DARPA, VA). Creating control signals to enable an amputee to feed himself with a prosthetic (robotic) arm and hand will require decoding signals from thousands of electrodes, rather than the hundred or so signals current systems read, as well as encoding thousands of sensor signals from the arm and hand into thousands of artificial neural signals to be "written into" the brain, which has not yet been attempted. The lack of low-power (so that it can be implanted) electronic circuitry needed to run BMIs' encoding and decoding algorithms (termed codecs) is a fundamental barrier to successful clinical translation. The technologies available until now are too power-hungry (digital) or too algorithmically inflexible (analog) to meet the challenge. Recent advances in neuromorphic engineering make it now possible to build a fully implantable and programmable codec chip. This innovative approach combines digital's and analog's best features-programmability and efficiency-while offering far greater robustness than either. Meanwhile recent advances in neuroscience techniques make it now possible to obtain the knowledge needed to design the right algorithms to run on our codec chip. Optogenetic stimulaton can now be used to drive neurons in macaque cortex and computer vision can now be used to track freely moving monkeys while recording wirelessly. We propose to leverage these recent advances to dramatically increase prosthetic performance through the principled design of: (1) An entirely new class of encoders that can spatio-temporally pattern neural activity via optogenetic techniques. (2) An entirely new class of decoders that can operate in the real world with animals moving freely around in far less constrained settings. (3) An entirely new class of implantable programmable electronics that achieves the level of energy- efficiency required to run these complex algorithms. We will demonstrate our success by having a freely moving primate, with a 96-microelectrode recording array and a 9-channel optogenetic stimulator implanted in its premotor and somatosensory cortex, respectively, control a human-like robotic arm. Our ultimate goal is to realize the neuromorphic engineer's dream: Helping untold millions with neurological injury by replacing damaged neural tissue with chips that work like the brain.