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Cognitive reserve and network efficiency as compensatory mechanisms of the effect of aging on phonemic fluency

机译:认知储备和网络效率作为老化对音素流畅性效果的补偿机制

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摘要

Compensation in cognitive aging is a topic of recent interest. However, factors contributing to cognitive compensation in functions such as phonemic fluency (PF) are not completely understood. Using cross-sectional data, we investigated cognitive reserve (CR) and network efficiency in young (32-58 years) versus old (59-84 years) individuals with high versus low performance in PF. ANCOVA was used to investigate the interaction between CR, age, and performance in PF. Random forest and graph theory analyses were conducted to study the contribution of cognition to PF and efficiency measures, respectively. Higher CR increased performance in PF and reduced age-related differences in PF. A slightly higher number of cognitive functions contributed to performance in high CR groups. The networks were more integrated in high CR individuals, both in the older age and high-performance groups. The strength and segregation of the networks were decreased in high-performance groups with high CR. We conclude that PF decreases less with age in individuals with higher CR, possibly due to a greater capacity to recruit non-linguistic cognitive networks, and efficient use of language networks, thereby integrating information in a rapid way across less fragmented networks. High CR and network efficiency seem to be important factors for cognitive compensation.
机译:认知老龄化的补偿是近期兴趣的主题。然而,没有完全理解有助于诸如音素流畅(PF)等功能中的认知补偿的因素。使用横断面数据,我们调查了年轻人(32-58岁)的认知储备(CR)和网络效率,而不是PF中具有高性能的旧(59-84岁)。 ANCOVA用于研究PF中CR,年龄和性能之间的相互作用。进行随机森林和图形理论分析,以分别研究认知对PF和效率措施的贡献。较高的CR增加了PF的性能,并降低了PF的年龄相关差异。略高数量的认知功能有助于高CR组的性能。在较旧的年龄和高性能群体中,该网络更集成在高CR个体中。网络的高性能群体的强度和分离在具有高CR的高性能组中降低。我们得出结论,PF随着较高CR的个体年龄而减少,可能是由于招募非语言认知网络的能力和高效使用语言网络,从而以快速的方式整合在较少分段的网络上的信息。高CR和网络效率似乎是认知补偿的重要因素。

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