Stochastic Actor-Oriented Models of Functional and Structural Human Brain Networks in Aging

The human brain is a complex and dynamical system that changes throughout the lifetime. Non-invasive imaging techniques, including magnetic resonance imaging (MRI), allow for the measurement of large-scale functional and structural connectivity networks in the brain. Beyond trends, the dynamics across long timescales are still poorly understood. Our research aims to address the question of these long-term dynamics by carefully adapting and applying the stochastic actor-oriented model to brain networks derived from MRI data in an aging population. The resulting models of network change suggest that the brain is promoting modularity, local efficiency, and short-range connectivity during aging with more adaptive functional networks compared to structural networks. Differences between individuals with and without cognitive impairment suggest a disruption in the maintenance of key brain topology in the progression of cognitive impairment with age. These results are modulated by subnetwork and sex differences that contribute further to the emerging picture of long-term dynamics in aging.