Optimizing oscillatory epidural electrical stimulation to selectively increase task-related population dynamics in motor areas

优化振荡硬膜外电刺激以选择性地增加运动区域中与任务相关的群体动态

• 批准号: 10468122
• 负责人: Karunesh Ganguly
• 金额: $ 70.9万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10468122
• 关键词: Affect; Area; Basal Ganglia; Behavior; Brain; Cells; Cephalic; Complex; Computer Analysis; Consensus; Custom; Data; Deep Brain Stimulation; Dimensions; Disease; Dorsal; Electric Stimulation; Electrodes; Frequencies; Goals; Impairment; Joints; Lead; Link; Measures; Medicine; Methods; Modeling; Motor; Motor Cortex; Motor Skills; Movement; Nature; Neurons; Neurosciences; Parkinson Disease; Performance; Physiological; Play; Population Dynamics; Preparation; Rattus; Recovery; Recovery of Function; Role; Sensory; Sleep; Somatosensory Cortex; Stroke; Survivors; Synaptic Transmission; Target Populations; Techniques; Testing; Therapeutic; Time; Uncertainty; United States; Work; design; disability; grasp; improved; innovation; motor behavior; motor function recovery; motor recovery; neural model; neural patterning; neuropsychiatric disorder; neuroregulation; non rapid eye movement; nonhuman primate; noninvasive brain stimulation; orientation selectivity; post stroke; prevent; relating to nervous system; response; sensory feedback; simulation; stroke recovery; stroke trials

PROJECT SUMMARY Stroke is the leading cause of motor disability in the United States. While brain stimulation to enhance motor function after stroke has shown promise in small studies, two recent large stroke trials did not find evidence for significant benefits. A key uncertainty is about how to exactly tailor brain stimulation to effectively modulate neural dynamics associated with movement preparation and control. Our recent studies in rats (Ramanathan et al., Nature Medicine 2018; Lemke et al., Nature Neuroscience, 2019) demonstrated that population dynamics linked to low-frequency oscillatory activity (0.5-4Hz “LFO”) are essential for movement control and can serve as a target for modulation using electrical stimulation. More specifically, cortical stimulation was found to both boost LFO power and augment motor function. We now also have substantial evidence in a non-human primate model that such an approach can be effective in more complex brains. However, it is essential to further optimize the delivery of such stimulation to specifically target cortical dynamics. We thus propose to optimize parameters for epidural stimulation to selectively modulate population dynamics in the intact motor network. Our approach entails simultaneous recording of single neurons in the non-human primate motor network along with electrical stimulation using a customized “ring” of epidural cranial screw electrodes. Moreover, we will use computational analysis to determine how task-related neural dynamics in a reach-to-grasp task are modulated by electrical stimulation. More specifically, we will optimize and develop principles for large-scale electrical stimulation to selectively enhance “neural modes” isolated to M1 or PMd or joint across both areas. This approach is built on the growing consensus that motor networks perform computations through coordinated ensemble activity or “neural modes”, i.e. patterns of neural covariation measured with dimensionality reduction methods. Activation of neural modes (i.e. Neural Model Activation or NMA) appear to constitute building blocks for computations underlying movement control. Our specific aims are: 1) Determine optimal ACS parameters that increases both local and cross-area NMA between M1 and PMd during a reach-grasp task; 2) Determine optimal ACS parameters that increases both local and cross-area NMA between M1 and S1 during a reach-grasp task; 3) Determine parameters for ACS to enhance task NMA during time periods away from the task. Completion of these aims will provide critical information for designing therapeutic stimulation that selectively targets population dynamics in the distributed motor network. The information gained may also help improve methods for non- invasive brain stimulation.

项目概要 在美国，中风是导致运动障碍的主要原因，而大脑刺激可以增强运动能力。 中风后的功能在小型研究中显示出希望，但最近的两项大型中风试验没有找到证据 一个关键的不确定性是如何精确调整大脑刺激以有效调节神经。 我们最近对大鼠的研究（Ramanathan 等人， Nature Medicine 2018；Lemke 等人，Nature Neuroscience，2019）证明种群动态相关 低频振荡活动（0.5-4Hz“LFO”）对于运动控制至关重要，并且可以作为目标 更具体地说，发现皮质刺激可以增强 LFO。 我们现在在非人类灵长类动物模型中也有大量证据。 这种方法可以在更复杂的大脑中有效，但是，有必要进一步优化。 因此，我们建议优化参数以专门针对皮层动力学。 硬膜外刺激选择性调节完整运动网络中的群体动态。 需要同时记录非人类灵长类动物运动网络中的单个神经元以及电 使用定制的硬膜外颅螺钉电极“环”进行刺激此外，我们将使用计算。 分析以确定伸手可及的任务中与任务相关的神经动力学如何通过电调节 更具体地说，我们将优化和开发大规模电刺激的原理。 有选择地增强与 M1 或 PMd 隔离的“神经模式”或跨这两个区域的联合。 越来越多的共识认为运动网络通过协调的整体活动或 “神经模式”，即用降维激活方法测量的神经协变模式。 神经模式（即神经模型激活或 NMA）似乎构成了计算的构建块 我们的具体目标是： 1) 确定可同时提高两者的最佳 ACS 参数。 到达抓取任务期间 M1 和 PMd 之间的本地和跨区域 NMA； 2) 确定最佳 ACS； 在触及抓取任务期间增加 M1 和 S1 之间的本地和跨区域 NMA 的参数； 确定 ACS 的参数，以在远离任务完成的时间段内增强任务 NMA。 这些目标将为设计选择性针对人群的治疗刺激提供关键信息 分布式运动网络中的动态变化也可能有助于改进非运动方法。 侵入性脑刺激。