Fig. 3: Graph theoretical metrics derived from brain connectomes, empirical SCs and FCs.
a–f Top row presents the SC properties in two age groups (n = 37 young and n = 32 older adults). a Structural modularity is increased, and b transitivity shows a decreasing trend. It can be interpreted as declined structural segregation. Due to loss in white-matter tracts in the aging brain, the connections across modules become more sparse. Thus, segregated SC resulted in a decreased inter-regional exchange of excitation. Though c global efficiency remains invariant, d significantly decreased average characteristic path length indicates a decline in network integration, which has a direct impact on the network resilience, confirmed by e assortativity, and f node betweenness centrality comparing the two age groups. g–l Functional network properties are shown in the second row (n = 37 young and n = 32 older adults). g Functional modularity remains unaltered with age, implying an average number of functional modules remains intact. However, specific brain regions could vary within a module in the two age groups. A significant increase (p < 0.001) is observed in i global efficiency and j average characteristic path length. Increased global efficiency and average characteristic path length in the elderly group signify an increased functional network integration. No significant changes are seen in k assortativity and l node betweenness centrality between the two groups, which describe unaltered functional resilience in aging brain. To visualize alteration patterns between the age groups, we join the two means by a black line, where the standard deviations from the mean are shown in blue lines. The independent t-test analysis determines significant changes (no changes). Network properties are derived using Brain Connectivity Toolbox26.
