We investigated the effect of the subnetwork topology on the synchronization of interconnected networks, or NoNs. Although random connection was favorable for synchronizing individual networks, the SF and super-hub topology with high-degree hub nodes exhibited highest synchrony in NoNs. This variation in the optimal topology in single and interconnected networks is the major finding of our study. The use of a phase oscillator model as local node dynamics allowed us to analytically investigate the structure-function relationships in NoNs via the synchrony alignment function. The results provide a first-order approximation to the study of dynamics within complex networks of biologically more plausible neural oscillators, such as the neural mass models (Zhao et al., 2010, 2011; Zamora-López et al., 2016). Indeed, the collective dynamics of a Kuramoto oscillator system has been shown to resemble that of neural mass models (Hoppensteadt and Izhikevich, 1997; Zamora-López et al., 2016), which highlights the neuroscientific relevance of the phase reduction approach (Breakspear et al., 2010; Rodrigues et al., 2016). The directionality of the connections and interaction delays are the factors that we also simplified or neglected
