Montemurro Sonia, Filippini Nicola, Ferrazzi Giulio, Mantini Dante, Arcara Giorgio, Marino Marco
IRCCS San Camillo Hospital, Venice, Italy.
Philips Healthcare, Milan, Italy.
Front Aging Neurosci. 2023 May 24;15:1168576. doi: 10.3389/fnagi.2023.1168576. eCollection 2023.
In healthy aging, the way people cope differently with cognitive and neural decline is influenced by exposure to cognitively enriching life-experiences. Education is one of them, so that in general, the higher the education, the better the expected cognitive performance in aging. At the neural level, it is not clear yet how education can differentiate resting state functional connectivity profiles and their cognitive underpinnings. Thus, with this study, we aimed to investigate whether the variable education allowed for a finer description of age-related differences in cognition and resting state FC.
We analyzed in 197 healthy individuals (137 young adults aged 20-35 and 60 older adults aged 55-80 from the publicly available LEMON database), a pool of cognitive and neural variables, derived from magnetic resonance imaging, in relation to education. Firstly, we assessed age-related differences, by comparing young and older adults. Then, we investigated the possible role of education in outlining such differences, by splitting the group of older adults based on their education.
In terms of cognitive performance, older adults with higher education and young adults were comparable in language and executive functions. Interestingly, they had a wider vocabulary compared to young adults and older adults with lower education. Concerning functional connectivity, the results showed significant age- and education-related differences within three networks: the Visual-Medial, the Dorsal Attentional, and the Default Mode network (DMN). For the DMN, we also found a relationship with memory performance, which strengthen the evidence that this network has a specific role in linking cognitive maintenance and FC at rest in healthy aging.
Our study revealed that education contributes to differentiating cognitive and neural profiles in healthy older adults. Also, the DMN could be a key network in this context, as it may reflect some compensatory mechanisms relative to memory capacities in older adults with higher education.
在健康衰老过程中,人们应对认知和神经衰退的不同方式会受到丰富认知生活经历的影响。教育就是其中之一,因此一般来说,教育程度越高,衰老过程中的认知表现预期就越好。在神经层面,目前尚不清楚教育如何区分静息态功能连接模式及其认知基础。因此,通过本研究,我们旨在调查教育变量是否能更精细地描述认知和静息态功能连接中与年龄相关的差异。
我们分析了197名健康个体(来自公开可用的LEMON数据库的137名20 - 35岁的年轻人和60名55 - 80岁的老年人)与教育相关的一系列认知和神经变量,这些变量源自磁共振成像。首先,我们通过比较年轻人和老年人来评估与年龄相关的差异。然后,我们通过根据老年人的教育程度对其进行分组,研究教育在勾勒这些差异方面可能发挥的作用。
在认知表现方面,受过高等教育的老年人和年轻人在语言和执行功能方面相当。有趣的是,与年轻人和受教育程度较低的老年人相比,他们的词汇量更大。关于功能连接,结果显示在三个网络中存在显著的与年龄和教育相关的差异:视觉 - 内侧网络、背侧注意网络和默认模式网络(DMN)。对于DMN,我们还发现了它与记忆表现的关系,这进一步证明了该网络在健康衰老过程中连接认知维持和静息态功能连接方面具有特定作用。
我们的研究表明,教育有助于区分健康老年人的认知和神经特征。此外,在这种情况下,DMN可能是一个关键网络,因为它可能反映了与受过高等教育的老年人记忆能力相关的一些补偿机制。