Minimally Invasive Ultrasonic Brain-Machine Interface

微创超声脑机接口

• 批准号: 10294005
• 负责人: RICHARD A ANDERSEN
• 金额: $ 329.08万
• 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: 2021-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10294005
• 关键词: 3-Dimensional; 3D ultrasound; Acute; Algorithms; Animals; BRAIN initiative; Blood flow; Brain; Brain region; Chronic; Computer software; Computers; Data; Development; Devices; Dura Mater; Electroencephalography; Eye; Functional Magnetic Resonance Imaging; Future; Hand; Human; Image; Imaging Techniques; Imaging technology; Implant; Intention; Left; Macaca; Methodology; Methods; Molecular; Monitor; Monkeys; Motor; Movement; Myristica fragrans; Neurosciences; Neurosciences Research; Operative Surgical Procedures; Parietal Lobe; Patients; Performance; Procedures; Process; Research; Research Personnel; Resolution; Rodent; Signal Transduction; Speed; System; Techniques; Technology; Testing; Three-Dimensional Imaging; Time; Tissues; Ultrasonics; Ultrasonography; Work; base; brain machine interface; brain tissue; brain volume; computerized data processing; cost; cranium; data acquisition; design; experimental study; hemodynamics; image processing; implantable device; implantation; infection risk; innovation; innovative technologies; invention; minimally invasive; multidisciplinary; neuroimaging; neuroprosthesis; neurosurgery; neurotransmission; nonhuman primate; novel; real-time images; relating to nervous system; spatiotemporal; temporal measurement

Abstract Brain-machine interfaces (BMIs) are one of the key motivating applications for the BRAIN Initiative’s drive to develop innovative technologies for large-scale recording of neural activity, benefiting not only BMI, but many other neuroscience studies. The most advanced techniques for neural recording and BMIs are currently invasive, causing local damage to living brain tissue, limiting their applications in human neuroscience research and BMI. On the other hand, noninvasive techniques typically offer relatively low spatial resolution and sensitivity. A minimally invasive BMI would bridge the gap between these extremes, opening a new avenue for neuroscience research and neuroprosthetics. Recently, functional ultrasound (fUS) imaging was introduced as a breakthrough technology for large-scale recording of neural activity – providing highly sensitive imaging of activity-dependent changes in blood flow with a spatiotemporal resolution of ~100 µm and 100 ms at several-cm depth. Importantly, fUS can record from outside the brain and protective dura mater tissue, vastly expanding its potential use in neuroscience applications and BMIs alike. While fUS is a hemodynamic technique, its excellent spatiotemporal performance and single-trial sensitivity offer a substantially closer connection to the underlying neuronal signals than achievable with other hemodynamic methods such as fMRI. In this project, we will push the boundaries of fUS as a technology for large-scale recording of neural activity by developing a fUS-based minimally invasive BMI. This proposal is based on preliminary data acquired by the collaborating investigators showing that ultrafast fUS imaging of the posterior parietal cortex in non-human primates (NHP) provides sufficient information to predict planned movements from single trial fUS recordings. These remarkable findings suggest that it may be possible to use fUS as the basis for a minimally invasive BMI that is implanted in the skull and does not penetrate the dura or brain tissue. Turning this potential into reality requires several fundamental advances in fUS neural imaging technology, which will greatly enhance the utility of this large-scale neural imaging technique across neuroscience applications. These advances include (1) maximizing the speed, data processing and information content extracted from fUS to enable a high- performance, real-time acute BMI; (2) developing a surgically implantable fUS technology for chronic, longitudinal minimally invasive recording of neural activity from a specific brain region; and (3) extending the fUS technology from 2D to 3D to facilitate applications requiring real-time imaging of large brain volumes. This proposal is enabled by two key innovations made by the co-PIs: the invention of fUS by Tanter, and the discovery by the collaborative team of Andersen, Shapiro and Tanter that fUS signals contain information that can be used for BMI. In addition, several new innovations are introduced through the proposed work including techniques to acquire and process fUS data in real time, advances in fUS hardware and surgical techniques for chronic implantation, and advances to enable wide-field and sparse real-time 3D imaging. If successful, this project will significantly advance the capabilities of fUS as a widely useful technology for rapid, sensitive, large-scale neural imaging and enable minimally invasive BMI.

摘要 脑机接口（BMI）是BRAIN Initiative推动开发的关键激励应用程序之一 用于大规模记录神经活动的创新技术，不仅有利于BMI，而且有利于许多其他神经科学 问题研究目前最先进的神经记录和BMI技术都是侵入性的，对生活造成局部损害。 脑组织，限制了它们在人类神经科学研究和BMI中的应用。另一方面，非侵入性技术 通常提供相对低的空间分辨率和灵敏度。微创BMI将弥合以下两种情况之间的差距 这些极端，为神经科学研究和神经修复开辟了一条新的途径。最近，功能超声（fUS） 成像作为一种突破性的技术被引入，用于大规模记录神经活动-提供高度的 血流中活性依赖性变化的灵敏成像，时空分辨率约为100 µm和100 ms， 几厘米深重要的是，fUS可以从大脑和保护性硬脑膜组织外部记录，极大地扩展了其功能。 在神经科学应用和BMI等方面的潜在用途。虽然fUS是一种血流动力学技术， 时空性能和单次试验灵敏度提供了与潜在神经元更紧密的联系， 信号比其他血液动力学方法，如功能磁共振成像。 在这个项目中，我们将推动fUS作为一种大规模记录神经活动的技术的界限， 基于fUS的微创BMI。这一建议是基于合作调查人员获得的初步数据 显示非人类灵长类动物（NHP）后顶叶皮质的超快fUS成像提供了足够的 根据单次试验fUS记录预测计划运动的信息。这些惊人的发现表明， 可以使用fUS作为植入颅骨且不穿透颅骨的微创BMI的基础。 硬脑膜或脑组织。 将这种潜力变为现实需要fUS神经成像技术的几个根本性进展，这将 大大增强了这种大规模神经成像技术在神经科学应用中的实用性。这些进步 包括（1）最大化速度、数据处理和从fUS提取的信息内容，以实现高 性能，实时急性BMI;（2）开发手术植入式fUS技术，用于慢性，纵向 微创记录特定脑区的神经活动;以及（3）将fUS技术从2D 到3D，以促进需要对大脑容量进行实时成像的应用。这一建议是由两个关键 co-PI的创新：Tanter发明了fUS，Andersen的合作团队发现了fUS， Shapiro和Tanter认为，fUS信号包含可用于BMI的信息。此外，一些新的创新是 介绍了通过拟议的工作，包括技术，以获取和处理fUS数据在真实的时间，进展fUS 长期植入的硬件和手术技术，以及实现宽视野和稀疏实时3D的进展 显像如果成功，该项目将大大提高fUS作为一种广泛有用的技术的能力， 灵敏的大规模神经成像，并实现微创BMI。

项目成果

Decoding motor plans using a closed-loop ultrasonic brain-machine interface.

• DOI: 10.1038/s41593-023-01500-7
• 发表时间: 2024-01
• 期刊: NATURE NEUROSCIENCE
• 影响因子: 25
• 作者: Griggs, Whitney S.;Norman, Sumner L.;Deffieux, Thomas;Segura, Florian;Osmanski, Bruno-Felix;Chau, Geeling;Christopoulos, Vasileios;Liu, Charles;Tanter, Mickael;Shapiro, Mikhail G.;Andersen, Richard A.
• 通讯作者: Andersen, Richard A.