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Imaging of Cognition, Learning and Memory in Aging

Imaging of Cognition, Learning and Memory in Aging
衰老过程中认知、学习和记忆的成像
批准号:
9913429
负责人:
YAAKOV STERN
金额:
$97.74万
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:
2017-05-01 至 2022-03-31

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中文摘要
翻译
本研究旨在更好地理解认知储备(CR)的神经基础。 我们假设CR调节了与年龄或阿尔茨海默病(AD)相关的关系 脑部病理学及其临床影响。我们的研究结果表明,CR通过 大脑处理任务的方式存在个体差异,我们可以使用与任务相关的功能磁共振成像 激活以了解这些处理差异。我们也已经开始研究影响 大脑完整性,或大脑储备(BR)。更好地理解CR和BR的前景是,这些概念 对功能随时间的保存有影响,所以储备的神经机制是 在纵向背景下进行最佳研究。我们建议在5年内启动纵向随访, 特征良好,最初健康的年轻人(n=50)和老年人(n=150),以阐明 认知障碍背后的神经机制,有助于维持认知障碍和成功的认知表现 推进与年龄相关的脑变化和AD病理。这些参与者已经在 两项功能磁共振成像任务的基线,以及与年龄和AD相关的大脑变化和 病理学,包括脑体积、皮质厚度、脑白质高信号、静息状态的MR测量 脑血流和默认网络完整性,以及来自Florbetaben PET的淀粉样蛋白负荷量化。我们 已经确定了CR的候选神经机制。我们将确定是否存在差异 这些CR网络在健康老年人中的表达与降低重要临床风险相关 结果包括认知功能下降和发展为轻度认知障碍、MCI或AD。我们还将 探索测量的CR和CR网络如何维持BR,以及它们如何调节观察到的大脑的影响 改变和推进阿尔茨海默病的病理,以保持认知功能。
英文摘要
The proposed research is aimed at better understanding the neural underpinnings of cognitive reserve (CR). We have postulated that CR moderates the relationship between age- or Alzheimer’s disease (AD)-related brain pathology and the clinical impact of that pathology. Our findings suggest that CR operates through individual differences in how tasks are processed in the brain and that we can use fMRI-measured task-related activation to understand these processing differences. We have also begun to look at the factors influencing brain integrity, or brain reserve (BR). The promise of better understanding CR and BR is that these concepts have implications for preservation of function over time, so the neural mechanisms underlying reserve are optimally studied in a longitudinal context. We propose to initiate longitudinal follow-up at 5 years of a large, well characterized, initially healthy group of young (n=50) and older (N=150) adults, in order to elucidate the neural mechanism underlying CR that help maintain BR and successful cognitive performance in the face of advancing age-related brain changes and AD pathology. These participants have already been studied at baseline with two fMRI tasks, as well as quantified measures of age- and AD-related brain changes and pathology, including MR measures of brain volume, cortical thickness, white matter hyperintensities, resting cerebral blood flow and default network integrity, as well quantified amyloid burden from Florbetaben PET. We have already identified candidate neural mechanisms for CR. We will determine whether differential expression of these CR networks in healthy elders is associated with reduced risk of important clinical outcomes including cognitive decline and developing mild cognitive impairment MCI or AD. We will also explore how measured CR and CR networks maintain BR and how they moderate the effect of observed brain changes and advancing AD pathology in order to preserve cognitive functioning.
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Imaging of Cognition, Learning and Memory in Aging
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