Healthy Aging as Information Divergence in the Multiplex Brain

Understanding the co-evolution of the human brain’s structural scaffold and functional traffic across the adult lifespan remains a fundamental challenge in neuroscience. While age-related degradation in grey matter and functional activation is well-documented, the joint trajectory of the structural (SC) and functional (FC) connectomes is often overlooked due to the lack of an integrative framework. Here, we model the brain as a multiplex network to quantify the information-theoretic interdependencies between these two layers in a cross-sectional cohort of 589 healthy individuals (ages 18–88) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) dataset. Using Jensen-Shannon Divergence and relative entropy metrics, we identify a fundamental organizing principle of healthy aging characterized by: a progressive information divergence where functional dynamics increasingly "untether" from their underlying structural constraints. Our results reveal that this decoupling follows a robust linear trajectory, yet is highly spatially heterogeneous. Meso-scale community analysis using the Multiplex Map Equation identifies subcortical hubs—specifically the putamen, pallidum, caudate, and thalamus—as the primary epicenters of age-related SC-FC divergence. This topological shift toward functional independence in subcortical ''switchboards" provides a mechanistic connectomic signature for the well-documented decline in fluid intelligence and motor adaptation that accompanies aging. In striking contrast, the limbic core (hippocampus and entorhinal cortex) exhibits remarkable stability across the lifespan, suggesting a biological imperative to preserve high-fidelity memory circuits amidst global communicative rewiring. By framing healthy aging as a systematic subcortical untethering alongside limbic resilience, our work provides a powerful new multiplex baseline to distinguish normative cognitive decline from the early topological signals of neurodegenerative disease.