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Age-related changes of the time-varying features in the brain functional connectivity and cognitive ageing

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Brain functional modular organization changes with age. Considering the brain as a dynamic system, recent studies have suggested that time-varying connectivity provides more information on brain functions. However, the spontaneous reconfiguration of modular brain structures over time during ageing remains poorly understood. In this study, we investigated the age-related dynamic modular reconfiguration using resting-state functional MRI data (615 participants, aged 18-88 years) from Cam-CAN. We employed a graph-based modularity analysis to investigate modular variability and the transition of nodes from one module to another in modular brain networks across the adult lifespan. Results showed that modular structure exhibits both linear and nonlinear age-related trends. The modular variability is higher in early and late adulthood, with higher modular variability in the association networks and lower modular variability in the primary networks. In addition, the whole brain transition matrix showed that the times of transition from other networks to the dorsal attention network were the largest. Furthermore, the modular structure was closely related to the number of cognitive components and memory-related cognitive performance, suggesting a potential contribution to flexibility cognitive function. Our findings highlighted the notable dynamic characteristics in large-scale brain networks across the adult lifespan, which enhanced our understanding of the neural substrate in various cognition during ageing. These findings also provided further evidence that dedifferentiation and compensation are the outcomes of functional brain interactions.
Title: Age-related changes of the time-varying features in the brain functional connectivity and cognitive ageing
Description:
Brain functional modular organization changes with age.
Considering the brain as a dynamic system, recent studies have suggested that time-varying connectivity provides more information on brain functions.
However, the spontaneous reconfiguration of modular brain structures over time during ageing remains poorly understood.
In this study, we investigated the age-related dynamic modular reconfiguration using resting-state functional MRI data (615 participants, aged 18-88 years) from Cam-CAN.
We employed a graph-based modularity analysis to investigate modular variability and the transition of nodes from one module to another in modular brain networks across the adult lifespan.
Results showed that modular structure exhibits both linear and nonlinear age-related trends.
The modular variability is higher in early and late adulthood, with higher modular variability in the association networks and lower modular variability in the primary networks.
In addition, the whole brain transition matrix showed that the times of transition from other networks to the dorsal attention network were the largest.
Furthermore, the modular structure was closely related to the number of cognitive components and memory-related cognitive performance, suggesting a potential contribution to flexibility cognitive function.
Our findings highlighted the notable dynamic characteristics in large-scale brain networks across the adult lifespan, which enhanced our understanding of the neural substrate in various cognition during ageing.
These findings also provided further evidence that dedifferentiation and compensation are the outcomes of functional brain interactions.

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