Characterizing and modulating motor cortical dynamics underlying rapid sequence learning in primates
Characterizing and modulating motor cortical dynamics underlying rapid sequence learning in primates
批准号:
10677450
负责人:
Sandon Montgomery Griffin
金额:
$3.96万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-05-01 至 2026-04-30
关键词:
AreaBehaviorBehavior TherapyBehavior assessmentBehavior monitoringBehavioralBradykinesiaBrainBrain InjuriesChronicComputer ModelsDataDevelopmentDiseaseElectrical Stimulation of the BrainEventExhibitsFoundationsFunctional Magnetic Resonance ImagingHandHumanImplantInterventionLearningLinkMagnetoencephalographyMental DepressionMental disordersMotorMotor CortexMotor SkillsNervous SystemNeuronsObsessive-Compulsive DisorderParkinson DiseasePathologicPatternPerformancePopulationPrimatesProcessResearchResolutionRestRoleSignal TransductionSleepSpeedTechniquesTestingWorkarmawakecognitive rigiditycompulsionexperimental studyflexibilitygazeimprovedinterdisciplinary approachkinematicsmotor learningmotor skill learningmultimodalitynervous system disorderneuralneural correlateneuromechanismnonhuman primatenovelruminationsequence learning
中文摘要
项目概要
一个根本性的重要问题是神经系统如何在
运动学习的过程。越来越多的人类证据显着证明了这种现象的存在
微离线增益 (MOG),或短暂休息时间(约 10 秒)后显着的“离线”性能增益,
在运动序列学习期间,随着快速可靠的性能得到巩固,这种能力会减弱。
脑磁图 (MEG) 记录将这种快速巩固形式与 13-30 Hz 振荡联系起来
场电位(β、β)和运动皮层宽带场电位模式的重放,特别是
初级运动皮层 (M1) – 对于执行和学习运动技能至关重要的区域。然而,它
目前尚不清楚 M1 中的高分辨率尖峰信号如何反映在空间广泛的 MEG 的重新激活中
信号以及离线β如何支持整合。此外,尚不清楚这种微离线处理是否有效。
快速行为改变的原因。
在这里,我们对非人类灵长类动物 (NHP) 使用了一种新颖的顺序到达任务,该任务可靠地引发 MOG,结合
通过运动皮层中的 LFP 和神经元尖峰记录,探索灵长类运动皮层如何实现快速
序列学习。我们的初步数据表明,M1 中的任务活跃神经元群在
短暂的休息,尤其是在 MOG 最高时的早期学习中。相反,离线β在后期最高
断裂并与 MOG 呈负相关。总之,这些结果激发了我们的总体假设:
任务主动尖峰模式的微离线重新激活促进快速学习,并且随着行为
优化的离线 β 增加可促进学习神经活动模式的稳定性。
为了检验这一假设,我们使用了高速到达和注视跟踪的跨学科方法,精确
神经记录、计算模型和因果操作。在目标 1 中,我们将评估是否
在短暂的休息期间任务活跃整体的重新激活与快速的行为改变相关。在
目标 2,我们将量化离线 β 相干尖峰模式与在线尖峰变化之间的关系
动态。最后,在目标 3 中,我们将使用 20 Hz 交流电刺激 (ACS) 来因果确定
离线β在调节快速巩固和行为稳定性中的作用。总之,这些实验将进一步
我们对灵长类动物皮层如何在短时间内实现适应性行为修改的理解以及
为基于刺激的行为和认知病理状况干预措施奠定坚实的基础
僵化,如帕金森病、强迫症和抑郁症。
英文摘要
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.
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国内基金
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