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.

抽象的 脑机界面（BMI）是大脑计划开发的主要动机应用程序之一 用于大规模记录神经元活动的创新技术，不仅使BMI受益，而且使许多其他神经科学受益 研究。神经记录和BMI的最先进的技术目前是侵入性的，造成了当地的生活损害 脑组织，限制其在人类神经科学研究和BMI中的应用。另一方面，无创技术 通常提供相对较低的空间分辨率和灵敏度。微创BMI会弥合 这些极端，为神经科学研究和神经假想开辟了新的途径。最近，功能性超声（FUS） 成像是作为用于大规模录制神经活动的突破性技术的引入 敏感的成像依赖活性的血流变化，时空分辨率约为100 µm和100 ms。 几厘米深度。重要的是，FUS可以从大脑外部记录并保护硬脑膜组织，从而大大扩展 在神经科学应用和BMIS上的潜在使用。虽然FUS是一种血液动力学技术，但它的出色 时空性能和单次试验灵敏度可提供与潜在神经元的更紧密联系 与其他血流动力学方法（例如fMRI）相比，信号。 在这个项目中，我们将通过开发FUS的界限作为一种大规模记录神经活动的技术 基于FUS的微创BMI。该提案基于合作调查人员获得的初步数据 表明非人类素数（NHP）的后顶叶皮层的超快FUS成像提供了足够的 信息以预测单个试验录制的计划运动。这些了不起的发现表明它可能 有可能使用FUS作为植入头骨且不会穿透的微创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基本进步，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）最大化从FU提取的速度，数据处理和信息内容以启用高级 性能，实时急性BMI； （2）为慢性，纵向开发手术植入的FUS技术 从特定大脑区域的神经活动的最小侵入性记录； （3）将FUS技术从2D扩展 到3D以促进需要实时大脑体积的实时成像的应用。该建议由两个密钥启用 Co-Pis的创新：Tanter的FUS发明，Andersen的合作团队的发现， shapiro和tanter fus信号包含可用于BMI的信息。此外，几项新的创新是 通过拟议的工作引入，包括实时获取和处理FUS数据的技术，FUS的进步 用于慢性植入的硬件和手术技术，并进步使宽场和稀疏实时3D 成像。如果成功的话，该项目将大大提高FUS的能力，以此作为快速，快速的技术 敏感的大规模神经成像，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.