Lifespan Development of EEG Alpha and Aperiodic Component Sources is Shaped by the Connectome and Axonal Delays

We introduce ξ − α Net, a mesoscale generative model of cortical activity that models the EEG aperiodic ( ξ ) and α -rhythm ( α ) components via Hida-Matérn processes constrained by anatomical connectivity and interareal delays. This framework integrates fractional differential equations (modeling damping/resonance), decomposition of Spectral Granger Causality, and lifespan quantification. Bayesian inversion of the model, on cross-spectral rsEEG data from 1,965 participants aged 5-100 years (HarMNqEEG dataset), allows us to estimate cortical activity and effective connectivity patterns at 8,003-voxel resolution. ξ processes showed extended cortical networks, with occurrence probability increasing with age but amplitude peaking midlife (inverted-U trajectory). α processes exhibited a localization in the posterior areas of the cortex and two specialized networks (parieto-occipital, sensorimotor), with increasing localization probability and peak amplitude/frequency showing age-linked inverted-U trajectory. The model uniquely estimates global conduction delays, which are negatively correlated with α frequency and independent myelin concentration profiles, mechanistically linking neural propagation times to α regulation.