Sensorimotor Computations in M1 & 5d During Online Control of Reaching Movement

描述（由申请人提供）：本职业发展建议旨在为研究者Truccolo博士提供在感觉运动神经生理学方面的独立研究所需的实验专业知识。Truccolo博士的目标是将他在统计和计算建模方面的背景与神经生理学方面的积极实验工作结合起来，研究相互作用的皮层网络的功能。该训练计划旨在进一步了解额顶叶感觉运动回路在自主运动在线控制中的作用。具体来说，提出的研究将测试计算模型的几个实验预测，其假设是：1)初级运动皮层（M1）根据顶叶皮层计算的运动误差（5d）纠正到达运动的视觉和机械扰动；2)当没有关于手臂的视觉反馈时，5d使用基于本体感觉反馈和从M1接收到的运动命令的手部位置前向模型预测来计算运动误差。使用两个10X10电极阵列的独特皮质内记录技术将记录M1和5d的细胞群活动和局部场电位（LFPs），因为猴子纠正了到达运动的短暂视觉和机械扰动。一个双连杆机械臂将被用来传递机械扰动。研究者最近开发的统计方法将用于测试预测的感觉、运动和错误信号的存在，以及在纠正运动期间预测的M1和5d之间的相互作用。该培训项目将在布朗大学神经科学系的Donoghue博士的指导下进行。导师和环境非常适合：布朗大学是著名的神经技术和系统神经科学中心，多诺霍博士是感觉运动系统、多电极神经生理学和神经假体方面的权威专家。除了实验神经生理学方面的培训外，活动还包括正在进行的皮质神经假体装置临床试验的转化神经科学方面的培训。该计划将形成一个研究生涯的基础，其长期目标包括：1)揭示由额顶叶网络病理引起的运动障碍的潜在机制，以及2)皮层的设计

DESCRIPTION (provided by applicant): This career development proposal aims at providing the investigator, Dr. Truccolo, with the required experimental expertise for an independent research career in sensorimotor neurophysiology. Dr. Truccolo's goal is to integrate his background in statistical and computational modeling with active experimental work in neurophysiology to investigate the function of interacting cortical networks. The training program is designed to further the understanding of the role of fronto-parietal sensorimotor loops in the online control of voluntary movements. Specifically, the proposed research will test several experimental predictions of a computational model whose hypotheses are: 1) that primary motor cortex (M1) corrects for visual and mechanical perturbations of reaching movements, based on a motor error computed in parietal cortex (5d); and 2) that when visual feedback about the arm is unavailable, 5d uses a forward model prediction of the hand position, derived from proprioceptive feedback and motor commands received from M1, in order to compute the motor error. Unique intracortical recording technology using two 10X10 electrode-arrays will record the activities of cell ensembles and local field potentials (LFPs) in M1 and 5d as monkeys correct for transient visual and mechanical perturbations of reaching movements. A 2-link robot arm will be employed to deliver mechanical perturbations. Statistical methods recently developed by the investigator will be used to test for the existence of predicted sensory, motor and error signals as well as for predicted interactions between M1 and 5d during corrective movements. The training program will be conducted under the mentorship of Dr. Donoghue in the Department of Neuroscience at Brown University. The mentor and the environment are ideally suited: Brown is a well-known center for neuro-technology and systems neuroscience, and Dr. Donoghue is a leading expert in sensorimotor systems, multielectrode neurophysiology, and neural prostheses. In addition to training in experimental neurophysiology, activities will include training in translational neuroscience involving an ongoing clinical trial of cortical neuroprosthetic devices. The proposed program will form the basis for a research career whose long term goals include: 1) shedding new light on the mechanisms underlying movement disorders arising from pathologies of fronto-parietal networks, and 2) the design of cortical neuroprosthetic devices that incorporate sensory feedback in the online closed-loop control of robotic limbs.