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

在日常生活中，人们经常灵巧地用手抓住和握住物体，如锤子或鸡蛋。这些任务需要不同水平的稳定握力，并在手指和手掌上施加不同的感觉。这就提出了一个问题，即大脑如何调节持续的抓取力，并处理来自手不同部位的感觉输入。该项目将使用高密度电极网研究人类受试者在执行持续的握手任务时的皮质振荡，并感受触觉刺激，如触摸和振动。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并区分手的触觉输入。该项目将提供有关感觉运动皮质活动与抓握力和触觉有关的组织的新知识。对触摸和振动做出独特反应的大脑区域将被电脉冲刺激，以产生人工感觉。从这个项目中获得的见解将在开发能够复制自然手功能的闭环神经假体方面发挥关键作用。尽管我们在理解感觉运动行为的神经基础方面取得了长足的进步，但关于在产生持续复杂的手功能(如抓握和触觉探索)过程中感觉和运动皮质回路的神经动力学知识非常有限，这是日常活动中必不可少的。更好地理解与持续复杂的手部运动和体感加工相关的时空神经动力学是构建更有效的闭环式神经假体的必要要求。利用先进的电极技术，该项目将利用高密度皮层脑电图仪(ECoG)栅格记录大脑皮质活动，然后利用计算智能对多通道数据进行解码，以识别在执行持续握手功能期间感觉运动皮质的振荡模式。高密度的ECoG栅格将以亚厘米的分辨率提供跨越大片皮质空间的大脑活动记录。同时，触觉感官输入--如振动和触摸--将被传递到不同的手指和手掌。该项目将检验皮层振荡在多大程度上可以用来预测产生的抓取力，并区分不同延长的手部躯体感觉输入。该项目还将开发一个实时系统，用于在线绘制皮质激活图，然后使用通道套件和使用环路计算机系统模拟ECoG调制的时间模式来刺激皮质区域。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，以揭示体感和运动皮质振荡的空间光谱动力学，并解码这些模式，以控制闭环式手神经假体。结果将使神经假体的设计和开发更接近于手的自然功能。该项目由了解神经和认知系统的综合策略(NCS)资助，NCS是一个多学科计划，由生物学(BIO)、计算机和信息科学与工程(CEISE)、教育和人力资源(EHR)、工程(ENG)和社会、行为和经济科学(SBE)的主管部门联合支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.