Motivation: The Human Connectome Project Aging (HCP-Aging) dataset presents a unique opportunity to study the aging brain. However, comprehensive analyses of structural connectivity in the dataset are still lacking. Goal(s): To examine age-related structural connectivity changes in HCP-Aging and explore the potential mechanisms underlying these changes. Approach: Macroscopic structural networks were reconstructed using anatomically constrained tractography and examined using graph theory-based tools and generative models. Results: We found significant alterations in the structural network topology as the brain aged, including reduced efficiency and connections to hubs, which could be attributed to increasing costs associated with preserving long-range connections. Impact: We have established a robust pipeline for reconstructing structural connectivity in the HCP-Aging dataset, and our findings suggest that aging increases the vulnerability of brain networks, potentially due to the high metabolic cost of maintaining an extensive network.
Liang et al. (Tue,) studied this question.
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