Role of coordinated multi-area reactivations during transitions between automatic and flexible behaviors.
Role of coordinated multi-area reactivations during transitions between automatic and flexible behaviors.
批准号:
10721280
负责人:
MAKSIM V BAZHENOV
金额:
$296.51万
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:
2023-09-01 至 2026-08-31
关键词:
AreaBackBehaviorBehavioralBrainBrain regionCellsComputer ModelsCorpus striatum structureCoupledCouplingDataDystoniaElectrophysiology (science)EventFailureFire - disastersGoalsInvestigationKnowledgeLeadLearningLinkMaintenanceMedialMemoryMental disordersModelingMotor CortexMotor SkillsMovementNeurologicNeuronsObsessive-Compulsive DisorderParkinson DiseasePathway interactionsPatternPerformancePopulation DynamicsPrefrontal CortexProcessProductionRattusRoleSiteSleepSlow-Wave SleepTask PerformancesTestingThalamic structureTimeTrainingWorkaddictionawakecell typeexperienceflexibilityforgettinggraspinsightmemory consolidationmotor skill learningneuralnon rapid eye movementnovelnovel therapeuticsoptogeneticspreventsleep spindlestroke recovery
中文摘要
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英文摘要
Abstract
Sleep occupies a large part of our lives and is widely believed to perform essential functions. During
sleep, the neuronal rules of engagement and population dynamics are clearly different than waking.
There is extensive evidence that one primary function of sleep is to consolidate memories formed during
waking. Recent work, however, suggests that sleep may also actively alter neural connections to
achieve forgetting (‘unlearning’). How the brain balances learning and forgetting, exactly how sleep
contributes, and the ultimate effects on ensembles and behavior are unknown.
The goal of this proposal is to determine how neuronal population dynamics during non-rapid-eye-
movement sleep (NREMS) achieve learning vs forgetting. We specifically aim to examine how activity
during NREMS regulates coupling across the cortex and the striatum, trial-to-trial variability of neural
ensembles (“representational variance”) and thereby behavioral automaticity versus flexibility.
Automaticity – the consistent production of a contextually-driven, fast and accurate action – is
associated with increased cortico-striatal coupling and reliable ensemble activity (low variance). In
contrast, weaker cortico-striatal coupling is associated with flexible, exploratory states and increased
representational variance.
We will use a rat model of motor skill learning (reach-to-grasp), together with multi-site
electrophysiology, identification of specific neuronal subtypes, closed-loop perturbations, and detailed
computational modelling. We will determine how specific NREMS dynamics differentially regulate the
reactivation of neuronal ensembles, to enable distinct forms of activity-dependent plasticity. Based on
extensive preliminary data, we hypothesize that global slow oscillations coupled to spindles trigger
globally coordinated reactivations that are broadly coordinated between cortical and striatal subregions.
These coordinated reactivations strengthen functional connections and produce earlier firing of ‘direct
pathway’ striatal neurons, promoting automaticity. By contrast, local up-states occurring during delta
waves produce uncoordinated reactivations, leading to functional decoupling of corticostriatal
connections and earlier firing of ‘indirect pathway’ striatal neurons to promote exploration and flexibility.
Our closely integrated electrophysiological, optogenetic and computational investigations will provide
novel mechanistic insights into precisely how brain dynamics during sleep achieve both consolidation
and unlearning of specific behavioral patterns. This knowledge has great potential to help us better
understand and treat the wide range of neurological and psychiatric illnesses associated with
alterations in cortico-striatal processing.
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会议论文
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