Hub structure in functional network of EEG signals supporting high cognitive functions in older individuals

Introduction: Maintaining high cognitive functions is desirable for “wellbeing” in old age and is particularly relevant to a super-aging society. According to their individual cognitive functions, optimal intervention for older individuals facilitates the maintenance of cognitive functions. Cognitive function is a result of whole-brain interactions. These interactions are reflected in several measures in graph theory analysis for the topological characteristics of functional connectivity. Betweenness centrality (BC), which can identify the “hub” node, i.e., the most important node affecting whole-brain network activity, may be appropriate for capturing whole-brain interactions. During the past decade, BC has been applied to capture changes in brain networks related to cognitive deficits arising from pathological conditions. In this study, we hypothesized that the hub structure of functional networks would reflect cognitive function, even in healthy elderly individuals.

Method: To test this hypothesis, based on the BC value of the functional connectivity obtained using the phase lag index from the electroencephalogram under the eyes closed resting state, we examined the relationship between the BC value and cognitive function measured using the Five Cognitive Functions test total score.

Results: We found a significant positive correlation of BC with cognitive functioning and a significant enhancement in the BC value of individuals with high cognitive functioning, particularly in the frontal theta network.

Discussion: The hub structure may reflect the sophisticated integration and transmission of information in whole-brain networks to support high-level cognitive function. Our findings may contribute to the development of biomarkers for assessing cognitive function, enabling optimal interventions for maintaining cognitive function in older individuals.