Department of Neuroscience, University of Kentucky, Lexington, KY, 40536, USA.
Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, 40536, USA; Department of Neurology, University of Kentucky, Lexington, KY, 40536, USA; Department of Psychiatry, University of Kentucky, Lexington, KY, 40536, USA.
Neuroimage. 2019 Jul 15;195:320-332. doi: 10.1016/j.neuroimage.2019.03.073. Epub 2019 Apr 4.
Executive function (EF) performance in older adults has been linked with functional and structural profiles within the executive control network (ECN) and default mode network (DMN), white matter hyperintensities (WMH) burden and levels of Alzheimer's disease (AD) pathology. Here, we simultaneously explored the unique contributions of these factors to baseline and longitudinal EF performance in older adults. Thirty-two cognitively normal (CN) older adults underwent neuropsychological testing at baseline and annually for three years. Neuroimaging and AD pathology measures were collected at baseline. Separate linear regression models were used to determine which of these variables predicted composite EF scores at baseline and/or average annual change in composite ΔEF scores over the three-year follow-up period. Results demonstrated that low DMN deactivation, high ECN activation and WMH burden were the main predictors of EF scores at baseline. In contrast, poor DMN and ECN WM microstructure and higher AD pathology predicted greater annual decline in EF scores. Subsequent mediation analysis demonstrated that DMN WM microstructure uniquely mediated the relationship between AD pathology and ΔEF. These results suggest that functional activation patterns within the DMN and ECN and WMHs contribute to baseline EF while structural connectivity within these networks impact longitudinal EF performance in older adults.
执行功能(EF)在老年人中的表现与执行控制网络(ECN)和默认模式网络(DMN)内的功能和结构特征、脑白质高信号(WMH)负担以及阿尔茨海默病(AD)病理水平有关。在这里,我们同时探讨了这些因素对老年人基线和纵向 EF 表现的独特贡献。32 名认知正常(CN)的老年人在基线时接受了神经心理学测试,并在三年内每年进行一次测试。在基线时收集了神经影像学和 AD 病理测量数据。使用单独的线性回归模型来确定这些变量中的哪些可以预测基线时的综合 EF 评分,以及在三年随访期间综合 ΔEF 评分的平均年度变化。结果表明,DMN 去激活程度低、ECN 激活程度高和 WMH 负担是基线 EF 评分的主要预测因素。相比之下,DMN 和 ECN 的 WM 微观结构较差以及 AD 病理水平较高预测了 EF 评分的更大年度下降。随后的中介分析表明,DMN WM 微观结构独特地介导了 AD 病理与 ΔEF 之间的关系。这些结果表明,DMN 和 ECN 内的功能激活模式以及 WMH 有助于老年人的基线 EF,而这些网络内的结构连通性则影响老年人的纵向 EF 表现。