Nested-spectral analysis reveals a disruption of behavioral-related dynamic functional balance in the aging brain

NONLINEAR DYNAMICS(2023)

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摘要
The relationship between the age-related reorganization of brain networks and individual behavior has attracted much attention. However, how age induces changes in neural activity at different frequencies in the brain to balance the demands of network integration and segregation, and how age-induced changes in network integration and segregation relate to behavior remain enigmatic. Here, a nested-spectral partition method was used to analyze behavioral-related dynamic functional balance in the aging brain with electroencephalogram signals collected from 56 healthy participants (age: 20–80 years) at rest. The nested-spectral partition approach measures hierarchical segregation and integration across multiple levels by detecting hierarchical modules in brain functional networks. Declines in general personality and general cognitive ability in older adults were captured by exploratory factor analysis. We showed that the brain network of elderly individuals contains more hierarchical modules to generate higher segregation, and it is closer to the functional balance state in the theta and alpha bands but away from this state in the gamma band. Meanwhile, the abnormal variability of functional balance in the elderly brain supports more flexible transitions between segregated and integrated states in the alpha band but reduces the transitions in the beta and gamma bands. Crucially, the degeneration of general personality and general cognitive ability is significantly associated with higher segregation and abnormal flexibility of the brain, especially in the theta, beta, and gamma bands. Our results provide deep insights from a spectral partitioning perspective into the brain dynamic mechanisms that are associated with age-related personality and cognitive degeneration.
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关键词
Aging,EEG,Spectral analysis,Functional dynamic balance,Cognitive ability,Personality traits
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