Tracking the dynamic functional connectivity structure of the human brain across the adult lifespan

The transition from early adulthood to older is marked by pronounced functional and structural brain transformations that impact cognition and behaviour. Here, we use dynamic functional network connectivity method to examine resting state functional network changes over aging process. In general, the features of dynamic functional states are generally varying across ages, such as the frequency of expression and the amount of time spent in the certain state. Increasing age is associated with less variability of functional state across time at rest period. From age point of view, examining the age-related difference of topology index revealed 19-30 age range has the significant largest global efficiency, largest local efficiency of default-mode network (DMN), cognitive control network (CCN) and salience network (SN). As for functional states, one state displayed the whole positive connectivity, in the meantime, it has the largest global efficiency and local efficiency of three subnetworks. Besides, the frequency of another state was negatively correlated to the box block (The Wechsler Adult Intelligence Scale subset, which is thought to evaluate fine motor skills, processing speed, and visuospatial ability), while positively correlated with age, and the box block was inversely correlated to age. The results suggested that cognitive aging may be characterized by the dynamic functional network connectivity. Taken together, these findings suggested the importance of a dynamic approach to understanding cognitive aging in lifespan.