Age-related Changes in Structural Connectivity in the HCP-Aging Data

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.