Identifying a task-invariant cognitive reserve network using task potency

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Abstract

Cognitive reserve (CR) is thought to protect against the consequence of age- or disease-related structural brain changes across multiple cognitive domains. The neural basis of CR may therefore comprise a functional network that is actively involved in many different cognitive processes. To investigate the existence of such a “task-invariant” CR network, we measured functional connectivity in a cognitively normal sample between 20 and 80 years old (N ​= ​265), both at rest and during the performance of 11 separate tasks that aim to capture four latent cognitive abilities (i.e. vocabulary, episodic memory, processing speed, and fluid reasoning). For each individual, we determined the change in functional connectivity from the resting state to each task state, which is referred to as “task potency” (Chauvin et al., 2018, 2019). Task potency was calculated for each pair among 264 nodes (Power et al., 2012) and then summarized across tasks reflecting the same cognitive ability. Subsequently, we established the correlation between task potency and IQ or education (i.e. CR factors). We identified a set of 57 pairs in which task potency showed significant correlations with IQ, but not education, across all four cognitive abilities. These pairs were included in a principal component analysis, from which we extracted the first component to obtain a latent variable reflecting task potency in this task-invariant CR network. This task potency variable was associated with better episodic memory (β ​= ​0.19, p ​< ​.01) and fluid reasoning performance (β ​= ​0.17, p ​< ​.01) above and beyond the effects of cortical thickness (range [absolute] β ​= ​0.28-0.32, p ​< ​.001). Our identification of this task-invariant network contributes to a better understanding of the mechanism underlying CR, which may facilitate the development of CR-enhancing treatments. Our work also offers a useful alternative operational measure of CR for future studies.

Original languageEnglish
Article number116593
JournalNEUROIMAGE
Volume210
DOIs
Publication statusPublished - 15 Apr 2020

Keywords

  • Cognitive aging
  • Cognitive reserve
  • Cortical thickness
  • IQ
  • fMRI

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