ArticleGeroScience2026
Cognitive network plasticity across divergent aging trajectories: an exploratory graph-theoretic study.
Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
3 authors.
Funding
Abstract
Interindividual variability in response to cognitive training remains a key barrier to developing precision approaches for maintaining neurocognitive health across the lifespan. Characterizing changes in system-level cognitive reorganization may provide insight into mechanisms of cognitive reserve, resilience, and plasticity that shape divergent aging trajectories and vulnerability to age-related cognitive decline. This exploratory study applies a cognitive network framework to examine how relationships among cognitive functions change and reorganize following training. We conducted a secondary analysis of open-access data from a randomized controlled trial comparing computerized cognitive training (Lumosity) with an active control (crossword puzzles), including 4471 participants (mean age 38.7 ± 15.1 years; range 18-80) from the retained analytic sample. Participants were stratified into low- and high-performing groups based on baseline cognitive performance. Cognitive networks were estimated using partial Spearman correlations among seven cognitive tasks, controlling for age, education, estimated training exposure, and self-reported psychological variables indexing affect and cognitive failures. Permutation-based thresholding ensured robust network estimation, and graph-theoretical metrics quantified training-related changes in network integration and segregation. Both interventions were associated with improvements in overall cognitive performance, with larger gains observed among low-performing individuals undergoing computerized training. Network-level changes were modest but systematic: low-performing participants in the computerized training group showed increases in global integration, whereas high-performing participants exhibited reductions in clustering and local efficiency. These findings demonstrate that cognitive network metrics capture subtle, performance-dependent patterns of plasticity expressed as changes in system-level organization, beyond mean cognitive gains and demographic age. Such system-level markers may help elucidate heterogeneity in neurocognitive aging and inform strategies to promote cognitive health.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.