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Brain Resilience to Targeted Attack of Resting BOLD Networks as a Measure of Cognitive Reserve. | LitMetric

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Article Abstract

Recent advancements in connectome analyses have enabled more precise measurements of brain network integrity. Identifying neural measures that can operate as mechanisms of cognitive reserve (CR) is integral for the study of individual variability in age-related cognitive changes. In the present study, we tested the hypothesis that network resilience, or the network's ability to maintain functionality when facing internal or external perturbations that cause damage or error, can function as a CR candidate, modifying the relationship between cognitive and brain changes in a lifespan cohort of cognitively healthy adults. One hundred cognitively healthy older adults from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (50-80 years) underwent resting-state fMRI and neuropsychological testing at baseline and five-year follow-up. Using undirected weighted adjacency matrices created from the Schaefer et al. (2018) 400-parcellation atlas and 19 additional subcortical regions (419 nodes in total), whole-brain network resilience was assessed through a targeted attack approach, where nodes were sequentially removed by nodal strength and resilience defined as the iteration of the steepest slope in the largest connected component (LCC) decay. We observed that brain resilience (BR) moderated the effect of cortical thickness (CT) changes on longitudinal changes in Fluid Reasoning performance, even after adjusting for baseline differences, demographic factors, and the initial LCC of the unlesioned matrix, indicating that individuals with greater resilience were less sensitive to the effect of cortical thickness changes on changes in cognition. These findings support the use of targeted attack as a measure of cognitive reserve, suggesting that higher brain network resilience may allow individuals with reduced brain integrity to better cope with structural loss and maintain cognitive function.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11643323PMC
http://dx.doi.org/10.21203/rs.3.rs-5356022/v1DOI Listing

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