Neurobiological mechanisms of sleep and exercise effects on memory in older adults at risk for Alzheimer's disease
睡眠和运动对有阿尔茨海默病风险的老年人记忆力影响的神经生物学机制
基本信息
- 批准号:10672951
- 负责人:
- 金额:$ 2.64万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-01 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAgingAlzheimer&aposs DiseaseAlzheimer&aposs disease pathologyAlzheimer&aposs disease riskBehavioralBiological MarkersBrainCognitionDataData CollectionData SetDementiaDevelopmentDiscriminationElderlyElectroencephalographyEpisodic memoryExerciseExhibitsFrequenciesFunctional Magnetic Resonance ImagingFunctional disorderGenetic Predisposition to DiseaseGoalsGraphHumanImpaired cognitionIndividualInterventionIntervention StudiesKnowledgeLife StyleLinkMeasuresMedialMemoryMemory impairmentMentorshipMethodsNeurobehavioral ManifestationsNeurodegenerative DisordersParticipantPatternPublic HealthQuestionnairesRecommendationResearchResearch PersonnelResolutionResourcesRestSleepSleep StagesSlow-Wave SleepStatistical ModelsTemporal LobeTestingTimeTrainingVisitanalytical methodcareercohortdata integrationdensityeffective therapyimprovedinnovationinsightmemory consolidationmemory retentionmodifiable lifestyle factorsnetwork architectureneurobiological mechanismneuroimagingnon rapid eye movementnormal agingnoveloperationpoor sleeppreventprospectivesleep qualitysleep quantitysleep spindletemporal measurementtheoriesyoung adult
项目摘要
PROJECT SUMMARY
Alzheimer’s disease is a progressive form of dementia with no effective treatments. Episodic memory deficits
are a defining cognitive symptom of Alzheimer’s disease, which may be related to changes in the medial temporal
lobes (MTL). The MTL facilitates episodic memory function and is particularly vulnerable to Alzheimer’s disease
pathology. Both sleep and exercise are linked to episodic memory function, including pattern separation
operations reliant on the MTL. Evidence in young adults suggests that sleep and exercise are each independently
linked to mnemonic discrimination (behavioral correlate of pattern separation), but it is unclear whether they
interact to do so, and through what mechanisms. Whether these relationships are altered in older adults at-risk
for Alzheimer’s disease is also unknown. To fill this knowledge gap, the proposed study will record high-density
electroencephalography (hdEEG) during overnight sleep to measure the topographically specific (i.e., local)
expression of non-rapid eye movement sleep slow-wave activity (SWA) and fast sleep spindle activity, administer
a memory task assessing mnemonic discrimination prior to and following sleep to measure sleep-dependent
memory consolidation, and collect questionnaire data assessing exercise frequency and duration from 56 older
adults with heightened Alzheimer’s disease risk. High-resolution resting-state functional magnetic resonance
imaging (hr-rsfMRI) data previously collected from this same participant cohort will be analyzed to measure
resting-state network modularity. The project will address three specific aims: (1) determine whether local
expression of SWA and fast spindle activity are associated with sleep-dependent memory consolidation in older
adults, (2) determine whether network modularity is associated with sleep-dependent memory consolidation and
local sleep expression in older adults, and (3) determine whether exercise is associated with local expression of
SWA and fast spindle activity and network modularity. This project will provide the applicant with comprehensive
training in memory theory, advanced statistical modelling, and cutting-edge analytical methods for hr-rsfMRI and
hdEEG data. This research and training plan will prepare the applicant for an independent academic research
career and will provide novel insights into the neurobiological mechanisms supporting the relationships among
sleep, exercise, and memory consolidation in older adults at-risk for Alzheimer’s disease. Findings from this
project could guide prospective exercise and sleep-based interventional studies to improve memory function and
inform public health recommendations to reduce Alzheimer’s disease risk by underscoring the importance of
sleep.
项目摘要
阿尔茨海默氏病是一种进行性痴呆,没有有效的治疗方法。情景记忆缺陷
是阿尔茨海默病的一个明确的认知症状,这可能与内侧颞叶的变化有关。
叶(MTL)。MTL促进情景记忆功能,并且特别容易患阿尔茨海默病
病理睡眠和运动都与情景记忆功能有关,包括模式分离
依赖MTL的业务。年轻人的证据表明,睡眠和锻炼是独立的,
与记忆辨别(模式分离的行为相关)有关,但尚不清楚它们是否
互动,以及通过什么机制。这些关系是否在老年人中发生改变
阿尔茨海默病的病因也是未知的。为了填补这一知识空白,拟议的研究将记录高密度的
脑电图(hdEEG)以测量地形特异性(即,当地)
非快速眼动睡眠慢波活动(SWA)和快速睡眠纺锤波活动的表达,给予
一项记忆任务,评估睡眠前后的记忆辨别力,以测量睡眠依赖性
记忆巩固,并收集问卷数据评估运动频率和持续时间从56岁以上
老年痴呆症风险增高的成年人。高分辨率静息态功能磁共振
将分析先前从同一参与者队列收集的成像(hr-rsfMRI)数据,以测量
静态网络模块化。该项目将解决三个具体目标:(1)确定当地是否
老年人SWA表达和快纺锤体活动与睡眠依赖性记忆巩固相关
成年人,(2)确定网络模块化是否与睡眠依赖性记忆巩固有关,
老年人的局部睡眠表达,以及(3)确定运动是否与局部睡眠表达相关。
SWA和快速纺锤体活性和网络模块化。该项目将为申请人提供全面的
记忆理论培训,先进的统计建模,以及hr-rsfMRI的尖端分析方法,
hdEEG数据。这项研究和培训计划将为申请人进行独立的学术研究做好准备
职业生涯,并将提供新的见解神经生物学机制支持之间的关系
睡眠、锻炼和记忆巩固在老年人中的作用时发现的问题
该项目可以指导前瞻性的运动和基于睡眠的干预研究,以改善记忆功能,
告知公共卫生建议,通过强调以下方面的重要性来降低阿尔茨海默病的风险:
睡吧
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Functional network structure supports resilience to memory deficits in cognitively normal older adults with amyloid-β pathology.
- DOI:10.1038/s41598-023-40092-x
- 发表时间:2023-08-25
- 期刊:
- 影响因子:4.6
- 作者:
- 通讯作者:
Examining the diagnostic value of the mnemonic discrimination task for classification of cognitive status and amyloid-beta burden.
- DOI:10.1016/j.neuropsychologia.2023.108727
- 发表时间:2023-12-15
- 期刊:
- 影响因子:2.6
- 作者:Kim, Soyun;Adams, Jenna N.;Chappel-Farley, Miranda G.;Keator, David;Janecek, John;Taylor, Lisa;Mikhail, Abanoub;Hollearn, Martina;Mcmillan, Liv;Rapp, Paul;Yassa, Michael A.
- 通讯作者:Yassa, Michael A.
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Miranda Chappel-Farley其他文献
Miranda Chappel-Farley的其他文献
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{{ truncateString('Miranda Chappel-Farley', 18)}}的其他基金
Neurobiological mechanisms of sleep and exercise effects on memory in older adults at risk for Alzheimer's disease
睡眠和运动对有阿尔茨海默病风险的老年人记忆力影响的神经生物学机制
- 批准号:
10314868 - 财政年份:2021
- 资助金额:
$ 2.64万 - 项目类别:
Neurobiological mechanisms of sleep and exercise effects on memory in older adults at risk for Alzheimer's disease
睡眠和运动对有阿尔茨海默病风险的老年人记忆力影响的神经生物学机制
- 批准号:
10474324 - 财政年份:2021
- 资助金额:
$ 2.64万 - 项目类别:
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