Garcia-Cabello Eloy, Gonzalez-Burgos Lissett, Pereira Joana B, Hernández-Cabrera Juan Andres, Westman Eric, Volpe Giovanni, Barroso José, Ferreira Daniel
Department of Clinical Psychology, Psychobiology and Methodology, Faculty of Psychology, University of La Laguna, La Laguna, Spain.
Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden.
Front Aging Neurosci. 2021 Aug 18;13:694254. doi: 10.3389/fnagi.2021.694254. eCollection 2021.
: Cognitive aging has been extensively investigated using both univariate and multivariate analyses. Sophisticated multivariate approaches such as graph theory could potentially capture unknown complex associations between multiple cognitive variables. The aim of this study was to assess whether cognition is organized into a structure that could be called the "cognitive connectome," and whether such connectome differs between age groups. : A total of 334 cognitively unimpaired individuals were stratified into early-middle-age (37-50 years, = 110), late-middle-age (51-64 years, = 106), and elderly (65-78 years, = 118) groups. We built cognitive networks from 47 cognitive variables for each age group using graph theory and compared the groups using different global and nodal graph measures. : We identified a cognitive connectome characterized by five modules: verbal memory, visual memory-visuospatial abilities, procedural memory, executive-premotor functions, and processing speed. The elderly group showed reduced transitivity and average strength as well as increased global efficiency compared with the early-middle-age group. The late-middle-age group showed reduced global and local efficiency and modularity compared with the early-middle-age group. Nodal analyses showed the important role of executive functions and processing speed in explaining the differences between age groups. : We identified a cognitive connectome that is rather stable during aging in cognitively healthy individuals, with the observed differences highlighting the important role of executive functions and processing speed. We translated the connectome concept from the neuroimaging field to cognitive data, demonstrating its potential to advance our understanding of the complexity of cognitive aging.
认知衰老已通过单变量和多变量分析进行了广泛研究。复杂的多变量方法,如图论,可能潜在地捕捉多个认知变量之间未知的复杂关联。本研究的目的是评估认知是否组织成一种可称为“认知连接组”的结构,以及这种连接组在不同年龄组之间是否存在差异。
总共334名认知未受损个体被分为早中年组(37 - 50岁,n = 110)、中老年组(51 - 64岁,n = 106)和老年组(65 - 78岁,n = 118)。我们使用图论为每个年龄组从47个认知变量构建认知网络,并使用不同的全局和节点图指标对各组进行比较。
言语记忆、视觉记忆 - 视觉空间能力、程序记忆、执行 - 运动前功能和处理速度。与早中年组相比,老年组的传递性和平均强度降低,全局效率增加。与早中年组相比,中老年组的全局和局部效率以及模块化降低。节点分析表明执行功能和处理速度在解释年龄组之间差异方面的重要作用。
我们确定了一个在认知健康个体衰老过程中相当稳定的认知连接组,观察到的差异突出了执行功能和处理速度的重要作用。我们将连接组概念从神经影像学领域应用到认知数据,证明了其在推进我们对认知衰老复杂性理解方面的潜力。