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

项目摘要 中风是美国运动残疾的主要原因。虽然大脑刺激可以增强运动 虽然在小型研究中显示出了中风后功能的希望，但最近的两项大型中风试验没有发现中风后功能恢复的证据。 重大利益。一个关键的不确定性是关于如何准确地调整大脑刺激以有效地调节神经元的功能。 与运动准备和控制相关的动力学。我们最近在大鼠中的研究（Ramanathan等人， Nature Medicine 2018; Lemke等人，Nature Neuroscience，2019）表明，人口动态与 低频振荡活动（0.5- 4 Hz“LFO”）对于运动控制至关重要，可以作为目标 用于使用电刺激进行调制。更具体地说，皮层刺激被发现既提高LFO 增强运动功能我们现在在非人类灵长类动物模型中也有大量证据 这种方法在更复杂的大脑中也是有效的。然而，必须进一步优化 将这种刺激递送到特定目标皮质动力学。因此，我们建议优化参数， 硬膜外刺激以选择性地调节完整运动网络中的群体动力学。我们的方法 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沿着电 使用定制的硬膜外颅骨螺旋电极“环”进行刺激。此外，我们将使用计算 分析，以确定如何在一个达到掌握任务的任务相关的神经动力学调制的电 刺激.更具体地说，我们将优化和开发大规模电刺激的原理， 选择性地增强与M1或PMd隔离的“神经模式”或跨两个区域的联合。这种方法建立在 越来越多的共识认为，运动网络通过协调的整体活动进行计算， “神经模式”，即用降维方法测量的神经协变的模式。激活 神经模式（即神经模型激活或NMA）似乎构成了计算的构建块 潜在的移动控制我们的具体目标是：1）确定最佳的ACS参数， 在伸手抓取任务期间M1和PMd之间的局部和跨区域NMA; 2）确定最佳ACS 在伸手抓握任务期间增加M1和S1之间的局部和跨区域NMA的参数; 3） 确定ACS的参数，以在任务之外的时间段内增强任务NMA。完成 这些目标将为设计选择性靶向人群的治疗刺激提供关键信息 分布式运动网络中的动力学。所获得的信息也可能有助于改进非- 侵入性脑刺激

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.