Characterizing and modulating motor cortical dynamics underlying rapid sequence learning in primates

表征和调节灵长类动物快速序列学习背后的运动皮层动力学

• 批准号: 10677450
• 负责人: Sandon Montgomery Griffin
• 金额: $ 3.96万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10677450
• 关键词: Area; Behavior; Behavior Therapy; Behavior assessment; Behavior monitoring; Behavioral; Bradykinesia; Brain; Brain Injuries; Chronic; Computer Models; Data; Development; Disease; Electrical Stimulation of the Brain; Event; Exhibits; Foundations; Functional Magnetic Resonance Imaging; Hand; Human; Implant; Intervention; Learning; Link; Magnetoencephalography; Mental Depression; Mental disorders; Motor; Motor Cortex; Motor Skills; Nervous System; Neurons; Obsessive-Compulsive Disorder; Parkinson Disease; Pathologic; Pattern; Performance; Population; Primates; Process; Research; Resolution; Rest; Role; Signal Transduction; Sleep; Speed; Techniques; Testing; Work; arm; awake; cognitive rigidity; compulsion; experimental study; flexibility; gaze; improved; interdisciplinary approach; kinematics; motor learning; motor skill learning; multimodality; nervous system disorder; neural; neural correlate; neuromechanism; nonhuman primate; novel; rumination; sequence learning

PROJECT SUMMARY A fundamentally important question is how the nervous system converges on optimal solutions during the process of motor learning. A growing body of evidence in humans has remarkably demonstrated the presence of micro-offline gains (MOGs), or significant “offline” performance gains after a brief rest period (~10 second), during motor sequence learning, which diminish as a fast and reliable performance is consolidated. Magnetoencephalography (MEG) recordings have linked this rapid form of consolidation to 13-30 Hz oscillations in field potentials (β, beta) and replay of broad-band field potential patterns across the motor cortex, particularly the primary motor cortex (M1) – an area essential to the execution and learning of motor skills. However, it remains unclear how high-resolution spiking signals in M1 are reflected in reactivations of spatially broad MEG signals and how offline β may support consolidation. Moreover, it is unclear if such micro-offline processing is causal to rapid behavioral modifications. Here, we use a novel sequential reach task for non-human primates (NHPs) that reliably elicits MOGs, combined with LFP and neuronal spiking recordings in motor cortex, to probe how the primate motor cortex enables rapid sequence learning. Our preliminary data shows that task-active neuronal ensembles in M1 are reactivated during short breaks, particularly in early learning when MOGs are highest. In contrast, offline β is highest during later breaks and is inversely correlated with MOGs. Together, these results motivate our overall hypothesis that micro-offline reactivation of task-active spiking patterns promotes rapid learning, and as behavior is optimized, offline β increases to promote stability of learned neural activity patterns. To test this hypothesis, we use an interdisciplinary approach of high-speed reach and gaze tracking, precise neural recordings, computational modeling, and causal manipulations. In Aim 1, we will assess whether reactivations of task-active ensembles during brief rest periods correlate with rapid behavioral modifications. In Aim 2, we will quantify the relationship between offline β-coherent spiking patterns and changes in online spiking dynamics. Finally, in Aim 3, we will use 20 Hz alternating current stimulation (ACS) to causally determine the role of offline β in regulating rapid consolidation and behavioral stability. Together, these experiments will further our understanding of how the primate cortex enables adaptive behavioral modifications on short timescales and lay a strong foundation for stimulation-based interventions for pathological conditions of behavioral and cognitive rigidity, such as Parkinson’s disease, obsessive-compulsive disorder, and depression.

项目摘要 一个根本重要的问题是神经系统如何在最佳解决方案上融合 运动学习过程。人类越来越多的证据表明了存在 在短暂的休息时间（〜10秒）之后，微型官能线增益（MOG）或显着的“离线”性能增长， 在运动序列学习中，作为快速可靠的性能减少的运动序列学习。 磁脑电图（MEG）录音已将这种快速的合并形式与13-30 Hz振荡联系起来 在田间电势（β，β）和整个运动皮层的宽带电势模式的重播，特别是 主要运动皮层（M1） - 这是执行和学习运动技能必不可少的领域。但是，它 尚不清楚M1中的高分辨率尖峰信号反映在空间宽MEG的重新激活中 信号以及离线β如何支持合并。此外，目前尚不清楚这种微型官能线处理是否是 因果关系快速行为修改。 在这里，我们为非人类素数（NHP）使用新颖的顺序触及任务，可可靠地引起MOGS，合并 在运动皮层中的LFP和神经元尖峰录音中，以探测主电机皮层如何快速启用 序列学习。我们的初步数据表明，M1中的任务活性神经元合奏在 短暂的休息时间，尤其是在MOGS最高的早期学习中。相比之下，离线β在以后的期间最高 断裂，与MOGS成反比。这些结果共同促进了我们的总体假设 任务活性峰值模式的微校线重新激活促进了快速学习，并且行为是 优化的，离线β增加了以促进学习神经活动模式的稳定性。 为了检验这一假设，我们使用高速覆盖范围和凝视跟踪的跨学科方法，精确 神经记录，计算建模和因果关系。在AIM 1中，我们将评估是否 短暂休息期间任务活性合奏的重新激活与快速行为修改相关。在 AIM 2，我们将量化离线β-加速器尖峰模式与在线尖峰的变化之间的关系 动力学。最后，在AIM 3中，我们将使用20 Hz替代电流刺激（AC）来确定 离线β在调节快速巩固和行为稳定性中的作用。这些实验将进一步 我们对灵长类动物皮质如何实现短时标准的适应性行为修改的理解 为基于刺激的干预措施为行为和认知的病理状况奠定了坚实的基础 刚性，例如帕金森氏病，强迫症和抑郁症。