Exploring Cognitive Aging Using Refernce Ability Neural Networks
Exploring Cognitive Aging Using Refernce Ability Neural Networks
批准号:
9177188
负责人:
Christian Georg Habeck
金额:
$718.04万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-01 至 2021-08-31
关键词:
AccountingAdultAgeAge-associated memory impairmentAgingAlzheimer&aposs DiseaseAlzheimer&aposs disease riskAmyloidAmyloid depositionBehavioralBiological Neural NetworksBrainCerebrovascular CirculationCognitionCognitiveCognitive agingCore-Binding FactorCross-Sectional StudiesDataData SetDementiaDerivation procedureElderlyEpisodic memoryFunctional ImagingFunctional Magnetic Resonance ImagingGoalsGrantHandHealthImageImpaired cognitionIndividualLeadLiquid substanceLocationLongevityMeasuresMediator of activation proteinMethodsModelingMultimodal ImagingNatureParticipantPatternPerformancePhasePositron-Emission TomographyProceduresProcessProductivityQuality of lifeResearchResearch PersonnelRestRisk FactorsSeriesSocietiesSpeedStagingStructureTestingThickTimeVocabularyWhite Matter Hyperintensityage differenceage effectage relatedagedbasebehavior changebrain behaviorbrain volumecognitive changecognitive performancecognitive taskcognitive testingcohortfollow-upinsightlongitudinal analysismild cognitive impairmentneurobehavioralneuroimagingpre-clinicalprogramsrelating to nervous systemwhite matter
中文摘要
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英文摘要
PROJECT SUMMARY:
This study focus on the optimal functional and structural imaging characterization of the cognitive aging and
preclinical Alzheimer's disease (AD). It has been repeatedly demonstrated that performance across the age
span on large batteries of diverse cognitive tests can be parsimoniously represented by a set of four reference
abilities: episodic memory, perceptual speed, fluid ability, and vocabulary. Based on these findings, it has been
argued that cognitive aging research should try to understand how aging impacts performance of this small set
of reference abilities than focus on specific tasks. In contrast, neuroimaging researchers typically evaluate age
differences in neural activation associated with the performance of a single specific task that may or may not
be fully representative of these reference abilities. We have begun to identify the latent brain networks
associated with each of the four reference abilities across adulthood. While undergoing functional imaging, we
tested large group of healthy adults aged 20 to 80 with a series of 12 cognitive tasks that represent the four
reference abilities (3 per construct). Using unique expertise in spatial covariance and other analyses of the
fMRI imaging data, we have derived preliminary versions of the latent spatial, brain-wide fMRI networks that
are associated with the latent cognitive structure of the reference abilities across adulthood. Successful
identification of these "reference ability neural networks" may lead to a paradigm shift in research on the neural
bases of age differences in cognition by focusing on the broad and replicable aspects common to several tasks
rather than the possibly idiosyncratic features of individual tasks. We now propose to follow up this group at 5
years in order to begin to delineate how expression of these networks changes with aging and with the onset of
mild cognitive impairment and AD. We will use multimodal imaging to evaluate potential mediators of age and
dementia-related differences in the utilization of the networks. These include change in brain volume and
cortical thickness; white matter hyperintensity burden; integrity of white matter tracts; resting CBF; and the
default network. Importantly, we will use PET to assess amyloid burden. The proposed study will develop a
completely new and more focused imaging approach to the study of cognitive aging and preclinical AD. It has
the potential to provide key insights into the nature and causes of the neural changes that underlie cognitive
aging and to more accurately describe the preclinical phase of AD.
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Exploring Cognitive Aging Using Reference Ability Neural Networks
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批准号:10645084
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项目类别:
-
资助金额:$243.43万
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财政年份:2011
-
负责人:Christian Georg Habeck
-
依托单位:
Exploring Cognitive Aging Using Reference Ability Neural Networks
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批准号:10470092
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项目类别:
-
资助金额:$245.19万
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财政年份:2011
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负责人:Christian Georg Habeck
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依托单位:
Early AD Detection with ASL MRI & Covariance Analysis
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批准号:7491027
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项目类别:
-
资助金额:$32.34万
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财政年份:2007
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负责人:Christian Georg Habeck
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依托单位:
Early AD Detection with ASL MRI & Covariance Analysis
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批准号:7144095
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项目类别:
-
资助金额:$32.65万
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财政年份:2007
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负责人:Christian Georg Habeck
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依托单位:
Multivariate approaches to neuroimaging analysis
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批准号:7197143
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项目类别:
-
资助金额:$29.02万
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财政年份:2007
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负责人:Christian Georg Habeck
-
依托单位:
Multivariate approaches to neuroimaging analysis
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批准号:7564716
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项目类别:
-
资助金额:$28.4万
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财政年份:2007
-
负责人:Christian Georg Habeck
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依托单位:
Multivariate approaches to neuroimaging analysis
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批准号:7383849
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项目类别:
-
资助金额:$28.4万
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财政年份:2007
-
负责人:Christian Georg Habeck
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依托单位:
Early AD Detection with ASL MRI & Covariance Analysis
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批准号:8092768
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项目类别:
-
资助金额:$30.78万
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财政年份:2007
-
负责人:Christian Georg Habeck
-
依托单位:
Early AD Detection with ASL MRI & Covariance Analysis
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批准号:7632173
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项目类别:
-
资助金额:$31.9万
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财政年份:2007
-
负责人:Christian Georg Habeck
-
依托单位:
Early AD Detection with ASL MRI & Covariance Analysis
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批准号:7874469
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项目类别:
-
资助金额:$32.02万
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财政年份:2007
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负责人:Christian Georg Habeck
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依托单位:
海外基金