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

描述（由申请人提供）：本职业发展计划旨在为研究者Truccolo博士提供感觉运动神经生理学独立研究职业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相结合，以研究相互作用的皮层网络的功能。训练计划的目的是进一步了解额顶叶感觉运动回路在自愿运动的在线控制中的作用。具体而言，拟议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）基于顶叶皮层（5d）中计算的运动误差校正到达运动的视觉和机械扰动;以及2）当关于手臂的视觉反馈不可用时，5d使用手位置的前向模型预测，从本体感受反馈和从M1接收的运动命令导出，以便计算运动误差。使用两个10 X10电极阵列的独特皮质内记录技术将记录M1和5d中的细胞群和局部场电位（LFP）的活动，因为猴子纠正了短暂的视觉和机械扰动。一个2连杆机械臂将被用来提供机械扰动。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，以及预测的M1和5d之间的相互作用，在纠正运动。培训计划将在布朗大学神经科学系Donoghue博士的指导下进行。导师和环境非常适合：布朗是一个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的领先专家。除了在实验神经生理学的培训，活动将包括在翻译神经科学的培训，涉及正在进行的临床试验皮层神经假体装置。该计划将形成一个研究生涯的基础，其长期目标包括：1）阐明额顶叶网络病理引起的运动障碍的潜在机制，2）设计皮层神经网络。 神经假体设备，将感觉反馈纳入机器人肢体的在线闭环控制。

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.