Brain network mechanisms of aging-related cognitive decline
Brain network mechanisms of aging-related cognitive decline
批准号:
10543603
负责人:
Michael William Cole
金额:
$39.17万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-03-01 至 2023-02-28
关键词:
Administrative SupplementAffectAgeAgingAlzheimer&aposs DiseaseAmyloid beta-ProteinAwardBehaviorBrainBrain regionCOVID-19 pandemicCognitionCognitive deficitsDataData AnalysesData CollectionElderlyFunctional Magnetic Resonance ImagingFundingGoalsGrainGrantImpaired cognitionIndividual DifferencesInterruptionKnowledgeLearningLifeLinkLiquid substanceLiteratureMeasuresMediatingMemory impairmentMeta-AnalysisMethodsMovementNetwork-basedNeurodegenerative DisordersParticipantPathway interactionsPatient RecruitmentsPlayProcessPropertyPublic HealthRestRoleRouteSeriesTask PerformancesTestingTimeTrainingbasecognitive abilitycognitive controlcognitive processcognitive reservecognitive taskcognitive trainingexperiencehealthy agingimprovedimproved outcomeinnovationlong term memoryrecruitrelating to nervous systemtoolyoung adult
中文摘要
点击翻译按钮获取中文摘要
英文摘要
PROJECT SUMMARY/ABSTRACT
Aging-related cognitive decline has been independently linked to alterations in resting-state functional
connectivity (RSFC) and cognitive task activations using functional MRI (fMRI), yet it is now well established
that there is a strong statistical relationship between RSFC and task activations. This is despite these being
quite distinct measures: RSFC is calculated as correlations among distributed brain activity time series during
rest, while task activations are localized brain activity amplitude changes during active task performance. The
network mechanisms underlying the RSFC-activation relationship are unknown, yet understanding this
relationship would clarify how aging alters both RSFC and cognitive task activations. For RSFC, linking to
cognitive task activations may help explain why RSFC is associated with cognitive processes despite being
measured independently of tasks testing those processes. For cognitive task activations, linking to RSFC may
bring a unified network-based understanding to the varied aging-related activation changes identified across
many brain regions and tasks. Thus, there is a critical need to determine the network mechanisms underlying
the relationship between RSFC and cognitive task activations. Without such knowledge, obtaining a unified
understanding of the neural basis of aging-related cognitive decline is unlikely. The overall objective of this
proposal is to identify network mechanisms that can account for the alterations in both RSFC and cognitive
task activations that occur with aging-related decline (from ages 18-28 to 65-75) of cognitive control abilities
among healthy older adults. This focus on cognitive control reflects its importance to adaptive, goal-directed
behavior in daily life. Further, cognitive control network (CCN) regions have RSFC network “hub” properties
well suited to regulate general cognitive ability. Of particular relevance to aging, cognitive control is one of the
abilities most affected by both healthy aging and Alzheimer’s disease, and it plays a role in long-term memory
deficits (a key feature of Alzheimer’s disease). This proposal’s central hypothesis is that aging-related
alterations in RSFC reflect changes in intrinsic network pathways that influence brain activations during task
performance, and hence mediate disruption of cognitive control abilities. Three approaches will be utilized
across three aims to test our central hypothesis. Briefly, the first will utilize an innovative approach to predict
activation abnormalities based on RSFC abnormalities in healthy older adults. The second will utilize individual
differences to determine the contribution of CCN hub disruption to aging-related cognitive decline. The third will
utilize the established influence of cognitive training on RSFC to investigate the role of functional network
plasticity in aging-related cognitive decline. This project is expected to markedly improve understanding of the
brain network basis of cognitive decline from healthy aging, in addition to improving general understanding of
the large-scale network mechanisms underlying cognition.
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DOI:
10.1162/jocn_a_01580
发表时间:
2021-03
期刊:
Journal of cognitive neuroscience
影响因子:
3.2
作者:
[Sanchez-Romero R, Cole MW]
通讯作者:
Cole MW
DOI:
10.1038/s41467-022-28323-7
发表时间:
2022-02-03
期刊:
Nature communications
影响因子:
16.6
作者:
[Ito T, Yang GR, Laurent P, Schultz DH, Cole MW]
通讯作者:
Cole MW
DOI:
10.1162/netn_a_00234
发表时间:
2022-06
期刊:
NETWORK NEUROSCIENCE
影响因子:
4.7
作者:
[McCormick, Ethan M, Arnemann, Katelyn L, Ito, Takuya, Hanson, Stephen Jose, Cole, Michael W]
通讯作者:
Cole, Michael W
DOI:
10.1126/sciadv.abf2513
发表时间:
2021-07
期刊:
Science advances
影响因子:
13.6
作者:
[Hearne LJ, Mill RD, Keane BP, Repovš G, Anticevic A, Cole MW]
通讯作者:
Cole MW
Structural MRI and functional connectivity features predict current clinical status and persistence behavior in prescription opioid users.
结构 MRI 和功能连接特征可预测处方阿片类药物使用者当前的临床状态和持续行为。
DOI:
10.1016/j.nicl.2021.102663
发表时间:
2021
期刊:
NeuroImage. Clinical
影响因子:
--
作者:
[Mill RD, Winfield EC, Cole MW, Ray S]
通讯作者:
Ray S
共 11 条
Brain Network Mechanisms of Aging-Related Cognitive Decline
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批准号:10115559
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项目类别:
-
资助金额:$38.72万
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财政年份:2017
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负责人:Michael William Cole
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依托单位:
Brain Network Mechanisms of Aging-Related Cognitive Decline
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批准号:9882927
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项目类别:
-
资助金额:$38.72万
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财政年份:2017
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负责人:Michael William Cole
-
依托单位:
Brain Network Mechanisms of Instructed Learning
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批准号:9977801
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项目类别:
-
资助金额:$38.98万
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财政年份:2016
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负责人:Michael William Cole
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依托单位:
Brain Network Mechanisms of Instructed Learning
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批准号:9235846
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项目类别:
-
资助金额:$41.19万
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财政年份:2016
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负责人:Michael William Cole
-
依托单位:
Network Mechanisms of Flexible Cognitive Control
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批准号:8773729
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项目类别:
-
资助金额:$24.9万
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财政年份:2014
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负责人:Michael William Cole
-
依托单位:
Network Mechanisms of Flexible Cognitive Control
-
批准号:8280752
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项目类别:
-
资助金额:$8.27万
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财政年份:2012
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负责人:Michael William Cole
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依托单位:
Network Mechanisms of Flexible Cognitive Control
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批准号:8459387
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项目类别:
-
资助金额:$8.27万
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财政年份:2012
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负责人:Michael William Cole
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依托单位:
海外基金