Modulating Low-Frequency Cortical Population Dynamics to Augment Motor Function After Stroke

调节低频皮质群动态以增强中风后的运动功能

• 批准号: 10602448
• 负责人: Karunesh Ganguly
• 金额: $ 62.98万
• 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: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10602448
• 关键词: Affect; Animals; Area; Brain; Chronic; Data; Dimensions; Distant; Electric Stimulation; Electrophysiology (science); Engineering; Fingers; Frequencies; Generations; Goals; Hand; Human; Injury; Lesion; Link; Medicine; Methods; Motor; Motor Cortex; Motor Skills; Movement; Nature; Neurons; Neurosciences; Performance; Phase; Physiological; Population Dynamics; Primates; Process; Randomized; Rattus; Recovery; Research; Residual state; Sensory; Somatosensory Cortex; Speed; Stroke; Survivors; System; Techniques; Testing; Therapeutic; Training; United States; Upper Extremity; Work; design; disability; grasp; hand dysfunction; improved; in vivo; innovation; motor function recovery; motor impairment; motor recovery; network models; neural; neural network; neurophysiology; neuroregulation; nonhuman primate; novel; post stroke; sensory cortex; skills; stereotypy; stroke model; stroke patient; stroke survivor; therapeutic target

PROJECT SUMMARY Stroke is the leading cause of motor disability in the United States, with approximately 700,000 new cases per year. Impaired hand and finger control are a leading cause of such disability. Despite advances in task- specific training for the upper limb, a large number of stroke patients do not regain full function of their hand; novel treatment methods are urgently required. We propose to use a systems neuroscience and `neural engineering' framework that captures the dynamic interactions between neurons and the distributed motor network to both characterize and develop novel neurophysiological based neuromodulation approaches to enhance motor function. Studies in healthy animals support a framework for dynamic interactions between local and distant areas through transient oscillations. Oscillations are defined by a frequency bandwidth, e.g. motor areas are known to have task-related low-frequency oscillations (0.5-4 Hz). How the recovery process affects neural activity and oscillatory dynamics in primates preforming dexterous tasks remains unknown? 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, track spontaneous recovery 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. Essential translational steps involve testing whether this approach also works for gyrated brains during the performance of dexterous tasks. This proposal aims to use in vivo electrophysiological methods to model the network dynamics of recovery. The underlying hypothesis is that synchronous LFO spike-field interactions in the perilesional cortex are important for recovery and its modulation can augment dexterous motor function. Importantly, our preliminary data provides strong support for our proposed research goals; we have found that low-frequency oscillatory dynamics drive coordination of sensory and motor areas during recovery and that artificial low-frequency electrical stimulation can boost dexterous function during recovery. Completion of these aims will provide critical information for designing therapeutic approaches that specifically target perilesional oscillatory activity with low frequency electrical stimulation. Focusing on targeted neuromodulation of such dynamic network interactions represents a new direction that could transform our ability to augment upper extremity function following stroke.

项目总结 在美国，中风是导致运动障碍的主要原因，每年约有70万新病例 年。手和手指控制受损是导致这种残疾的主要原因。尽管任务取得了进展- 针对上肢的专项训练，大量中风患者手部功能不能完全恢复； 迫切需要新的治疗方法。我们建议使用系统神经科学和‘神经学’ 工程学框架，捕捉神经元和分布式马达之间的动态相互作用 网络来表征和开发基于神经生理学的新的神经调节方法 增强运动功能。对健康动物的研究支持了一个动态相互作用的框架 通过瞬变振荡的局部和远程地区。振荡由频率带宽定义，例如 众所周知，运动区有与任务相关的低频振荡(0.5-4赫兹)。恢复过程如何 灵长类灵长类灵巧任务对神经活动和振荡动力学的影响尚不清楚？ 我们最近对大鼠的研究(Ramanathan等人，《自然医学》2018；Lemke等人，《自然神经科学》， 2019年)表明与低频振荡活动(0.5-4赫兹“LFO”)有关的种群动态是 对运动控制至关重要，跟踪自发恢复，并可作为调制使用的目标 电刺激。更具体地说，大脑皮层刺激被发现既能增强LFO的力量，又能增强 运动功能。基本的转换步骤包括测试这种方法是否也适用于回转 大脑在执行灵巧任务的过程中。 这项建议旨在使用体内电生理方法来模拟恢复的网络动力学。 潜在的假设是，损毁周围皮质中的同步LFO棘波-场相互作用是 对于恢复很重要，它的调节可以增强灵巧的运动功能。重要的是，我们的初选 数据为我们提出的研究目标提供了强有力的支持；我们发现低频振荡 在恢复过程中，动力驱动感觉和运动区的协调，以及人工低频 电刺激可以促进恢复过程中的灵巧功能。 这些目标的完成将为设计具体的治疗方法提供关键信息 以低频电刺激为靶点的周边振荡活动。专注于目标明确 这种动态网络相互作用的神经调节代表了一个新的方向，可能会改变我们的 中风后增强上肢功能的能力。