NCS-FO: Characterization and Decoding of Cortical Oscillatory Dynamics of Complex Hand Function

在日常生活中，人们用手频繁而灵巧地抓住和握住一个物体，如锤子或鸡蛋。这些任务需要不同程度的稳定抓握力，并在手指和手掌上施加不同的感觉。这就提出了一个问题，即大脑是如何调节持续的抓握力并处理来自手部不同部位的感觉输入的。该项目将使用高密度电极网格研究人类受试者在执行持续的手抓任务和感觉触觉刺激（如触摸和振动）时的皮层振荡。新的计算算法将被开发并应用于神经数据，以预测产生的抓取力和区分手部的触觉输入。这个项目将提供关于感觉运动皮层活动组织与抓握力和触觉的新知识。大脑中对触摸和振动有独特反应的区域将受到电脉冲的刺激，从而产生人工感觉。从这个项目中获得的见解将在闭环神经假肢的发展中发挥关键作用，可以复制自然手的功能。尽管我们对感觉运动行为的神经基础的理解取得了相当大的进展，但在持续复杂手功能（如抓握和触觉探索）产生过程中，对感觉和运动皮层回路的神经动力学的了解非常有限，这些功能对日常活动至关重要。更好地了解持续复杂手部运动和体感处理相关的时空神经动力学是构建更高效的闭环神经假肢的必要条件。利用先进的电极技术，该项目将用高密度皮质电图（ECoG）网格记录皮层活动，然后用计算智能解码多通道数据，以识别持续手抓功能执行过程中感觉运动皮层的振荡模式。高密度ECoG网格将提供跨大皮质空间的大脑活动记录，分辨率为亚厘米。同时，触觉感官输入——比如振动和触摸——将被传递到不同的手指和手掌。该项目将研究皮质振荡在多大程度上可以用来预测产生的抓握力，并区分不同的长时间体感输入到手。该项目还将开发一个实时系统，用于在线绘制皮层激活，然后使用通道套件和模拟ECoG调制的时间模式，使用计算机在环系统刺激皮层区域。该项目将整合神经科学、神经外科和生物医学工程专业知识，揭示体感和运动皮层振荡的空间光谱动力学，并解码这些模式以控制闭环手部神经假肢。结果将使神经义肢的设计和开发更接近手部的自然功能。该项目由理解神经和认知系统的综合策略（NCS）资助，这是一个由生物学（BIO）、计算机与信息科学与工程（CISE）、教育与人力资源（EHR）、工程学（ENG）和社会、行为和经济科学（SBE）联合支持的多学科项目。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。

In daily life, people grasp and hold an object with their hands, such as a hammer or an egg, frequently and dexterously. These tasks require different levels of steady grasp force and exert different sensations on the fingers and palm. This raises questions of how the brain regulates sustained grasp force and processes sensory input from different parts of the hand. This project will investigate cortical oscillations using high-density electrode grids while human subjects perform sustained hand grasp tasks and feel tactile stimuli such as touch and vibration. Novel computational algorithms will be developed and applied to the neural data to predict the produced grasp force and differentiate tactile inputs to the hand. This project will provide novel knowledge regarding the organization of sensorimotor cortex activity in relation to grasp force and tactile sensations. Brain regions that show unique activity in response to touch and vibration will then be stimulated with electrical pulses to elicit artificial sensations. Insights gained from this project will play a critical role in the development of closed-loop neuroprosthetics that can replicate natural hand function.Despite considerable progress regarding our understanding of the neural bases of sensorimotor behavior, there is very limited knowledge about the neural dynamics of sensory and motor cortical circuits during the generation of sustained complex hand function, such as grasping and tactile exploration, which are essential for common daily activities. A better understanding of the spatio-temporal neural dynamics associated with sustained complex hand movements and somatosensory processing is a necessary requirement for the construction of more efficient closed-loop neuroprosthetics. Utilizing advanced electrode technology, this project will record cortical activity with high-density electrocorticography (ECoG) grids, then decode multichannel data with computational intelligence for the identification of oscillatory patterns of the sensorimotor cortex during the execution of sustained hand grasp function. The high-density ECoG grids will provide recordings of brain activity across a large cortical space and with sub-centimeter resolution. Simultaneously, tactile sensory inputs--such as vibration and touch--will be delivered to different fingers and palm. The project will examine to what extent the cortical oscillations can be used to predict the produced grasp force and distinguish between different prolonged somatosensory inputs to the hand. The project will also develop a real-time system for the mapping cortical activations online, then stimulate cortical regions using channel suites and temporal patterns mimicking the ECoG modulations using a computer-in-the-loop system. The project will integrate neuroscience, neurosurgery and biomedical engineering expertise, to uncover spatio-spectral dynamics of somatosensory and motor cortical oscillations, and decode these patterns for the control of closed-loop hand neuroprosthetics. Outcomes will enable the design and development of neuroprosthetics more akin to the natural function of the hand.This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NCS), a multidisciplinary program jointly supported by the Directorates for Biology (BIO), Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).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.