Collaborative Research: NCS-FO: Intelligent Closed-Loop Neural Interface System for Studying Mechanisms of Somatosensory Feedback in Control of Functional and Stable Locomotion

来自运动腿的感觉反馈对于功能性和动态稳定的运动至关重要。虽然很明显，运动相关的感觉反馈影响腿间协调和步态选择（步行、小跑、疾驰等），但尚不清楚哪种感觉模式（例如，肌肉长度或力相关信号）和反馈来源（例如，髋关节或膝关节肌肉）介导这些运动变化。因此，本项目旨在了解提供臀部肌肉长度信息的感觉神经元如何调节肢间协调和步态选择。这一目标将通过以智能、闭环和良好控制的方式有选择地和可逆地刺激这些感觉神经元来实现。该项目将开发新的神经植入工具和相关的计算算法，用于大型动物模型猫的运动相关感觉信号的体内操作。本项目的新发现和开发的方法将大大提高我们对感觉运动控制机制的理解，并有助于开发新的治疗干预措施。提出的多学科研究方法也将显著扩大快速发展的光遗传学领域的效用和能力，使变革性研究成为可能，并为神经科学提供前所未有的新实验工具。这项工作对社会最显著的长期效益将是改善大量受各种运动缺陷（从肢体丧失到感觉神经病变）影响的人群的生活质量。这些人将受益于由机器学习算法控制的神经系统和工程系统之间的神经接口的发展。在整个项目中，将努力从代表性不足的群体中招收和培训研究生和本科生。还将组织外展活动，与教师、学生和代表性不足的群体分享资源、工具和知识。拟议的研究和教育活动的结果将通过科学展览、出版物、研讨会、会议和互联网与学生、科学界和公众分享。本研究的总体目标是通过在体内开发和利用智能闭环光电神经接口系统，表征猫模型中臀部肌肉纺轴传入神经对肢体间协调和步态选择的体感控制机制。特别是，在本提案中，将开发高密度，高效，无线供电的植入式光电（WIOE）神经接口设备。每个WIOE均采用64个透明微电极和16个微尺度发光二极管（µled）组成的光电阵列，一个片上系统（SoC）和一个功率接收器（Rx）线圈，封装尺寸为3毫米，能够进行光遗传刺激和神经活动的电记录。无线遥测链路将在外部数据采集/控制单元和分布式WIOE植入物阵列之间实现有效的经皮功率和宽带数据传输。将多个WIOE装置植入猫的背根神经节（DRG）。记录DRG神经元的神经活动、四肢选定肌肉的肌电图活动和全身运动运动学，并通过光遗传刺激控制猫在无约束运动中选定DRG的纺锤体传入活动。机器学习（ML）模型利用信号中的时空结构，并将DRGs中的传入活动映射到肢体运动学，将用于实现光遗传神经调节的闭环控制。拟议的研究活动将由一个在生物医学、无线微电子、机器学习、人工智能和行为神经科学领域具有互补研究专长的合作者团队进行。所提出的智能闭环光电神经接口的成功开发将为一套全面的微创神经接口提供强大的构建模块，用于研究运动的体感控制，以及监测或治疗体感病理状况。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。

Sensory feedback from moving legs is critical for functional and dynamically stable locomotion. Although it is clear that motion-related sensory feedback influences inter-leg coordination and selection of gaits (walking, trotting, galloping, etc.), it is not known which sensory modalities (e.g., muscle length- or force-related signals) and sources of feedback (e.g., hip or knee muscles) mediate these locomotor changes. Therefore, this project aims to understand how sensory neurons providing information about the length of hip muscles regulate interlimb coordination and gait selection. This goal will be accomplished by selectively and reversibly stimulating these sensory neurons in an intelligent, closed-loop, and well-controlled manner. This project will lead to the development of new neural implant tools and associated computational algorithms for an in-vivo manipulation of motion-related sensory signals in a large animal model, the cat. The new findings of this project and the developed methods will substantially enhance our understanding of the mechanisms of sensory locomotor control and contribute to developing novel therapeutic interventions. The proposed multidisciplinary research approaches will also significantly expand the utility and capabilities of the rapidly growing field of optogenetics, enabling transformative research and providing unprecedented new experimental tools for neuroscience. The most noticeable long-term benefits of this work to society will be an improvement in the quality of life for a sizable population of people affected by a wide range of movement deficits, from limb loss to sensory neuropathy. These individuals will benefit from the development of neural interfaces between the nervous and engineering systems controlled by machine learning algorithms. Throughout this project, efforts will be made to recruit and train graduate and undergraduate students from underrepresented groups. Outreach activities will also be organized to share resources, tools, and knowledge with teachers, students, and underrepresented groups. The results of the proposed research and educational activities will be shared with students, scientific communities, and the public through science fairs, publications, workshops, conferences, and the Internet.The overall goal of this proposal is to characterize the mechanisms of somatosensory control of interlimb coordination and gait selection by spindle afferents of hip muscles in the cat model by developing and utilizing in-vivo an intelligent and closed-loop optoelectronic neural interface system. In particular, in this proposal high-density, efficient, and wirelessly-powered implantable opto-electro (WIOE) neural interface devices will be developed. Each WIOE heterogeneously incorporates an optoelectronic array of 64 transparent microelectrodes and 16 microscale light-emitting-diodes (µLEDs), a system-on-a-chip (SoC), and a power receiver (Rx) coil in an mm3-size package, capable of optogenetic stimulation and electrical recording of neural activities. Wireless telemetry links will be implemented for efficient transcutaneous power and wideband data transmission between an external data-acquisition/control unit and the distributed array of WIOE implants. Multiple WIOE devices will be implanted in selected dorsal root ganglia (DRG) of the cat. Neural activities of DRG neurons, EMG activities of selected muscles of the four limbs, and full-body locomotor kinematics will be recorded, and spindle afferent activities will be manipulated via optogenetic stimulation in selected DRGs during unconstrained cat locomotion. Machine learning (ML) models leveraging the spatiotemporal structures in the signals and mapping afferent activities in DRGs to limb kinematics will be applied for achieving closed-loop control of the optogenetic neuromodulation. The proposed research activities will be conducted by a team of collaborators with complementary research expertise in the areas of bioMEMS, wireless microelectronics, machine learning, artificial intelligence, and behavioral neuroscience. The successful development of the proposed intelligent and closed-loop optoelectronic neural interface will yield a robust building block for a comprehensive set of minimally invasive neural interfaces to study somatosensory control of movement, as well as monitor or treat somatosensory pathological conditions.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.