The human brain is a complex structural and functional network organ in the human body. Graph theory was introduced to study the complex network organization of the brain. The structural and functional systems of the brain have the characteristics of a complex network, such as network modularity, highly connected hubs, and small world topology [1,2]. Electroencephalography (EEG) studies have shown reduced connectivity in adults to be influenced by aging in a resting state through a difficult mathematical calculation [3]. In other EEG studies, network connectivity was reduced in an elderly group compared to a younger group [4,5]. In order to study the network properties of brain networks, several network matrices were used to investigate brain aging, such as characteristic path length, node strength, edge and node betweenness centrality, clustering coefficient, global efficiency, and local efficiency [6]. The study of brain networks in healthy aging, especially age-related changes in memory, plays a vital role in understanding the deficits created by Alzheimer’s disease (AD). Graph theory is applied to model the human brain as a complex network represented by nodes or vertices (i.e., brain regions) connected by edges (i.e., functional connections) [1,7].
