PDF(Pubmed)
Abstract：
Understanding the relationship between functional connectivity (FC) of higher-order neurocognitive networks and age-related cognitive decline is a complex and evolving field of research. Decreases in FC have been associated with cognitive decline in persons with Alzheimer\'s disease and related dementias (ADRD). However, the contributions of FC have been less straightforward in typical cognitive aging. Some investigations suggest relatively robust FC within neurocognitive networks differentiates unusually successful cognitive aging from average aging, while others do not. Methodologic limitations in data processing and varying definitions of \'successful aging\' may have contributed to the inconsistent results to date. The current study seeks to address previous limitations by optimized MRI methods to examine FC in the well-established SuperAging phenotype, defined by age and cognitive performance as individuals 80 and older with episodic memory performance equal to or better than 50-to-60-year-olds. Within- and between-network FC of large-scale neurocognitive networks were compared between 24 SuperAgers and 16 cognitively average older-aged control (OACs) with stable cognitive profiles using resting-state functional MRI (rs-fMRI) from a single visit. Group classification was determined based on measures of episodic memory, executive functioning, verbal fluency and picture naming. Inclusion criteria required stable cognitive status across two visits. First, we investigated the FC within and between seven resting-state networks from a common atlas parcellation. A separate index of network segregation was also compared between groups. Second, we investigated the FC between six subcomponents of the default mode network (DMN), the neurocognitive network commonly associated with memory performance and disrupted in persons with ADRD. For each analysis, FCs were compared across groups using two-sample independent t-tests and corrected for multiple comparisons. There were no significant between-group differences in demographic characteristics including age, sex and education. At the group-level, within-network FC, between-network FC, and segregation measurements of seven large-scale networks, including subcomponents of the DMN, were not a primary differentiator between cognitively average aging and SuperAging phenotypes. Thus, FC within or between large-scale networks does not appear to be a primary driver of the exceptional memory performance observed in SuperAgers. These results have relevance for differentiating the role of FC changes associated with cognitive aging from those associated with ADRD.
摘要：
了解高阶神经认知网络的功能连通性（FC）与年龄相关的认知能力下降之间的关系是一个复杂且不断发展的研究领域。FC的减少与阿尔茨海默病和相关痴呆（ADRD）患者的认知能力下降有关。然而,在典型的认知衰老中,FC的贡献并不那么简单.一些研究表明，神经认知网络中相对稳健的FC将异常成功的认知衰老与平均衰老区分开来，而其他人没有。数据处理的方法学局限性和“成功老化”定义的不同可能是迄今为止结果不一致的原因。本研究旨在通过优化的MRI方法来解决以前的局限性，以检查已建立的SuperAging表型中的FC，根据年龄和认知表现定义为80岁及以上的个体，其情景记忆表现等于或优于50至60岁。使用静息状态功能MRI（rs-fMRI）从一次访问中比较了24个SuperAgers和16个认知平均老年对照（OAC）的大规模神经认知网络的网络内和网络间FC。群体分类是根据情景记忆的度量确定的，执行功能，口头流畅性和图片命名。纳入标准要求两次访问的认知状态稳定。首先,我们从一个常见的地图集分组中调查了七个静息态网络内部和之间的FC。还比较了组间网络隔离的单独指数。第二,我们研究了默认模式网络(DMN)的六个子组件之间的FC，ADRD患者的神经认知网络通常与记忆表现相关，并被破坏。对于每个分析，使用双样本独立t检验对各组进行比较，并对多重比较进行校正。在包括年龄在内的人口统计学特征上没有显著的组间差异，性和教育。在集团层面,网络内FC，网络间FC，和七个大规模网络的隔离测量，包括DMN的子组件，不是认知平均衰老和超衰老表型之间的主要区别。因此，大型网络内部或之间的FC似乎不是SuperAgers中观察到的出色内存性能的主要驱动因素。这些结果对于区分与认知衰老相关的FC变化与与ADRD相关的FC变化的作用具有相关性。
