In these multiscale neural activities, the network dynamics, which is captured by the degree of synchronization and information flow between pair-wise brain regional neural activities called dynamic functional connectivity (dFC), play an important role in coordinating the mutual interactions of neural activities (reviewed in Cohen, 2018; Luppi et al., 2022). ...besides the pair-wise neural interactions, the temporal itinerancy of the global topology of the whole-brain functional network is present (Guan et al., 2022). Subsequently, a more rigid method for determining the length of a window based on the temporal transition of a quasistable spatial power distribution, called a microstate, was proposed (Guan et al., 2022; Yan et al., 2023). ...instead of focusing on synchronization within the time-window, a technique of utilizing the instantaneous temporal patterns produced by neural interaction was also developed, which is required for achieving high temporal resolution to capture the characteristics of moment-to-moment dynamical functional connectivity (Nobukawa et al., 2019). Recent mathematical modeling of brain networks focuses on large hierarchical neural characteristics from the molecular/cellular and local neural circuit levels to the global whole brain level. ...embedding disease-specific impairments into the modeled-brain network studies could reveal the mechanisms by which these individual impairments affect the alternations of brain network dynamics (Matsumoto et al., 2023; Park et al.; Zhu et al.). Network dynamics in the physiological-data approach Studies in this decade have revealed that functional connectivity exhibits large temporal variability, even in the resting state, which is called dFC (Betzel et al., 2012; Hutchison et al., 2013; Allen et al., 2014; Calhoun et al., 2014; Hansen et al., 2015) (reviewed in Cohen, 2018).