Biomarkers.

Background: Investigating age-related changes in MEG brain networks offers significant potential for comprehending aging trajectories and unveiling anomalous patterns associated with neurodegenerative disorders, such as Alzheimer's disease. In this study, we extended a deep learning model called Fully Hyperbolic Neural Network (FHNN) to embed MEG brain connectivity graphs into a Lorentz Hyperboloid model for hyperbolic space. Through these embeddings, we then explored the impact of aging on brain functional connectivity across multiple decades.

Method: We analyzed data from 587 participants enrolled in the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) longitudinal study. Notably, we introduced a unique metric-the radius of the node embeddings-which effectively proxies the hierarchical organization of the brain. We leveraged this metric to (i) assess whether we can decode age-related information, and (ii) characterize subtle hierarchical organization changes of various brain subnetworks attributed to the aging process.

Result: Our decoding results revealed that the hyperbolic radius carries substantially more age-related information compared to all other conventional graph-theoretic measures examined, underscoring the effectiveness of employing hyperbolic embeddings to characterize the aging process. An examination of hyperbolic radius alteration patterns across decades exposed numerous subnetworks showcasing a decline in hierarchy during aging, with some displaying gradual changes and others undergoing rapid transformations in the aging brain (illustrated in Figure 1cde).

Conclusion: Overall, our study presented the first evaluation of hyperbolic embeddings in MEG brain networks, introduced a novel measure of brain hierarchy, and used this measure to highlight aging trajectories in the large cohort of the Cam-CAN dataset. A prominent finding was the reduction of hierarchy across a substantial number of subnetworks throughout the aging brain. This hierarchy reduction could imply a shift in the brain network configuration impairing cognitive processes.