Lifespan trajectories of the brain's functional complexity characterized by multiscale sample entropy.

Resting state functional magnetic resonance imaging (rs-fMRI) is a widely used imaging modality that can capture spontaneous neural activity of the brain. The human brain is a complex system, and emerging evidence suggests that the complexity of neural activity may serve as an index of its information processing capacity. In this study, we used multiscale sample entropy (MSE) to analyze the complexity of rs-fMRI time series from 504 healthy subjects aged 6 to 85 years. We constructed global and regional trajectories of the brain's functional complexity across the lifespan and examined its correlation with executive function. We observed a nonlinear trajectory of fMRI-complexity, with a peak occurring at 23 years of age (95% CI: 21.27,26.38 years). Males reached the peak complexity at 26 years (95% CI: 19.95, 33.14 years), whereas females peaked at 23 years (95% CI 20.16, 29.18 years). Significant correlations were found between complexity and Number-Letter Switching of the Trail Making Test in the parietal and medial temporal lobes, while Inhibition and Inhibition/Switching of the Color Word Interference Test showed significant negative correlations with rs-fMRI complexity in the lateral and medial frontal cortex. These results provide insight into the behavior of fMRI-complexity across lifespan stages and highlight its association with executive function. As a non-invasive biomarker, fMRI-complexity may offer a novel approach to understanding the brain's information processing capacity and its deficits in illness.