Trajectories of brain entropy across lifetime estimated by resting state functional magnetic resonance imaging

The human brain is a complex system of interconnected brain regions that form functional networks with differing roles in cognition and behavior. However, the trajectories of these functional networks across development are unclear and designing a metric to track the complex trajectory of these characteristics throughout the lifespan is challenging. Here, permutation entropy (PE) was used to examine age-related variations in functional magnetic resonance imaging (fMRI) in healthy subjects aged 6-85 from global, network, and nodal perspectives. The global PE followed an inverted U-shaped trajectory that peaked at approximately age 40. The trajectory of the motor and somatosensory functional network was more consistent with a linear model and increased with age; other functional networks showed inverted U-shaped trajectories that peaked between 25 and 52 years of age. All nodes showed inverted U-shaped trajectories. Using cluster analysis, the peak ages of nodes were grouped into three clusters (at 24, 38, and 51 years). Overall, we characterized four aging trajectories: networks with a linear increase, early peak age, intermediate peak age, and older peak age. These findings suggest possible complexity in trajectories at critical age points regarding changes in related functional brain networks.