Abstract
Age and sex associated with changes in the functional brain network topology and cognition in large population of older adults have been poorly understood. We explored this question further by examining differences in 11 resting-state graph theory measures with respect to age, sex, and their relationships with cognitive performance in 17,127 United Kingdom Biobank participants (mean = 62.83 ± 7.41 years). Age was associated with an overall decrease in the effectiveness of network communication (i.e., integration) and loss of functional specialization (i.e., segregation) of specific brain regions. Sex differences were also observed, with women showing more efficient networks, which were less segregated than in men (FDR adjusted p < 0.05). The age-related changes were also more apparent in men than in women, which suggests that men may be more vulnerable to cognitive decline with age. Interestingly, while network segregation and strength of limbic network were only nominally associated with cognitive performance, the network measures collectively were significantly associated with cognition (FDR adjusted p ≤ 0.002). This may imply that individual measures may be inadequate to capture much of the variance in the neural activity or its output and need further refinement. The complexity of the organization of the functional brain may be shaped by the age and sex of an individual, which ultimately may influence the cognitive performance of older adults. Age and sex stratification may be used to inform clinical neuroscience research to identify older adults at risk of cognitive dysfunction.
Highlights
The brain is topographically organized into distinct networks
Significant differences were observed for the demographics, graph theory measures, and memory scores between men and women (Table 2)
The only exceptions were that strength of default and salience networks were not significantly associated with age
Summary
The brain is topographically organized into distinct networks. In the recent years, neuroscientists have examined networks to understand the brain function in preference to the classic study of specific brain regions. In network models of rs-fMRI data, functional brain networks are summarized into a collection of nodes (i.e., brain regions) and edges (i.e., magnitude of temporal correlation in fMRI activity between regions) (Rubinov and Sporns, 2010; Bertolero et al, 2018). This network model can be used to study the global and local properties of the functional brain networks (Table 1). There is evidence that adult human brains are organized into groups of specialized functional networks that are able to respond to various cognitive demands (Wang J. et al, 2010). Studying the organization of functional networks in the aging brain may allow us to understand age-associated cognitive changes, even in the absence of a brain disease (Burke and Barnes, 2006; Otte et al, 2015)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
