Impact of Sleep and Corticostriatal Functional Connectivity on Behavioral Flexibility
Impact of Sleep and Corticostriatal Functional Connectivity on Behavioral Flexibility
批准号:
10463506
负责人:
David Darevsky
金额:
$4.0万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-05-01 至 2023-03-31
关键词:
AnimalsAreaBehaviorBehavioralBrainChronicComputer ModelsCorpus striatum structureCoupledCouplingDataData AnalysesDropsEquilibriumEvolutionExploratory BehaviorFoundationsFrequenciesInjuryInterventionLaboratory FindingLearningLearning SkillLinkLocationMediatingMemoryMental disordersModelingModificationMotorMotor CortexMotor SkillsMotor outputMovementNeuronsObsessive-Compulsive DisorderOutputPerformancePlayPopulationPositioning AttributeProcessRattusRehabilitation therapyResearchRewardsRoleSleepSlow-Wave SleepStrokeSynapsesSystemTestingTrainingVariantWorkaddictionawakebaseenvironmental changeexperienceexperimental studyflexibilitygraspinsightinterdisciplinary approachmemory consolidationmotor disordernon rapid eye movementnoveloptogeneticspreventrelating to nervous systemresponseskillssleep physiologysleep spindle
中文摘要
项目总结
一大堆工作揭示了运动皮质(M1)如何推动新兴运动技能的精细化
精确的、自动的动作。此外,我们实验室的发现暗示了皮质纹状体(CS)功能的出现
M1和背外侧纹状体(DLS)之间的连接对于提高涉及两者的技能至关重要
粗略和精细的运动,如熟练的伸手抓握(RTG)任务,其中大鼠精确执行
伸手去取回赏金弹丸。然而,尽管人们对M1/DLS活动的演变知道得很多
对于可预测的行为输出,对于运动系统如何响应大的
错误,允许通过行为探索灵活地适应学习到的技能。
在这里,我们使用了RTG任务的一个新变体(在这个任务中,大鼠首先学习到达颗粒之前的一个位置
持有者被移动到不重叠的位置,在下文中称为重新对准任务),以探测CS网络如何
实现了应对环境变化的行为灵活性。我们的初步数据显示,虽然老鼠
最终“重新瞄准”到新的颗粒位置,这个过程只在几天内发生,而不是在一天内发生,并且
涉及运动变异性增强的一过性状态。这表明睡眠期间的“离线”巩固
在调节行为稳定性与探索性之间的平衡以及中心假说方面起着关键作用
非快速眼动(NREM)睡眠对CS连接的双向调节作用
以实现行为探索。
在这里,我们使用探索性数据分析、计算建模和因果关系的跨学科方法
操纵来回答上面的问题。在目标1中,我们将评估睡眠的临时嵌套是如何
通过慢振荡和增量波调制行为切换和theta频率LFP相干性
在到达过程中(它的出现已被证明与成功的到达行为有关)。在目标2中,
我们将用跨区域计算模型来拟合尖峰数据,以分离M1与DLS活动的动力学
通过重新定位范式,深入了解每个区域对行为的各自贡献
稳定性与灵活性。最后,在目标3中,我们将使用闭环光遗传学来因果确定
睡眠纺锤体对行为稳定性和CS功能连接性的贡献。加在一起,这些
实验将进一步加深我们对睡眠生理学的理解,因为它与行为灵活性有关,并为
为基于睡眠的运动障碍干预奠定了坚实的基础,这些障碍包括受伤、中风,甚至可能
精神健康障碍(如成瘾或强迫症)
皮质纹状体连接。
英文摘要
PROJECT SUMMARY
A large body of work has revealed how motor cortex (M1) drives the refinement of emergent motor skills towards
precise, automatic actions. Moreover, our lab’s findings implicate the emergence of corticostriatal (CS) functional
connectivity between M1 and dorsolateral striatum (DLS) as essential to refinement of skills that involve both
gross and fine motor movements, such as a skilled reach-to-grasp (RTG) task where rats execute precise
reaches to retrieve reward pellets. However, while much is known about the evolution of M1/DLS activity
towards predictable behavior output, little is known about how the motor system responds to large
errors by allowing flexible adaptation of learnt skill through behavioral exploration.
Here we use a new variant of the RTG task (where rats first learn reaching to one location before the pellet
holder is moved to a non-overlapping position, termed ‘re-aiming’ task hereafter) to probe how the CS network
enables behavioral flexibility in response to environmental changes. Our preliminary data shows that while rats
eventually “re-aim” to the new pellet location, the process occurs only across days, rather than within day, and
involves a transitory state of heightened motor variability. This suggests that “offline” consolidation during sleep
plays a key role in mediating the balance between behavioral stability vs exploration, and the central hypothesis
of this proposal is that non-rapid eye movement (NREM) sleep bidirectionally modulates CS connectivity
to enable behavioral exploration.
Here we use an interdisciplinary approach of exploratory data analysis, computational modeling, and causal
manipulations to answer the above question. In Aim 1, we will assess how the temporal nesting of sleep spindles
with slow oscillations and delta-waves modulates both behavioral switchover and theta frequency LFP coherence
during reaching (the emergence of which has been shown to track with successful reaching behavior). In Aim 2,
we will fit spiking data with a cross-area computational model to dissociate the dynamics of M1 vs DLS activity
across the re-aiming paradigm to gain deeper insight into each region’s respective contributions to behavioral
stability vs flexibility. And lastly in Aim 3, we will use closed-loop optogenetics to causally determine the
contributions of sleep spindles to both behavioral stability and CS functional connectivity. Together, these
experiments will further our understanding of sleep physiology as it relates to behavioral flexibility and lay a
strong foundation towards sleep-based interventions for motor disorders after injury, stroke, and perhaps even
mental health disorders (such as addiction or obsessive-compulsive disorder) that prominently implicate
corticostriatal connectivity.
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