Synchronization of complex human networks

Abstract

The synchronization of human networks is essential for our civilization and understanding its dynamics is important to many aspects of our lives. Human ensembles were investigated, but in noisy environments and with limited control over the network parameters which govern the network dynamics. Specifically, research has focused predominantly on all-to-all coupling, whereas current social networks and human interactions are often based on complex coupling configurations. Here, we study the synchronization between violin players in complex networks with full and accurate control over the network connectivity, coupling strength, and delay. We show that the players can tune their playing period and delete connections by ignoring frustrating signals, to find a stable solution. These additional degrees of freedom enable new strategies and yield better solutions than are possible within current models such as the Kuramoto model. Our results may influence numerous fields, including traffic management, epidemic control, and stock market dynamics.

Synchronization Stability Model of Complex Brain Networks: An EEG Study

“…. , N and then complex dynamics network (1) can reach an identity synchronous steady state, and C × C × • • • × C is called the synchronous area of the complex dynamic network (1).…”

“…A common criterion to judge the synchronous stability of a system is to require that the Lyapunov exponents for (2) are all negative (1,18). But this does not mean that this condition alone can determine whether a system realizes a steady state or not.…”

“…Synchronization of complex networks is a very important research direction in the study of complex network dynamics because the complexity of the structural characteristics of complex networks has a multifaceted impact on the dynamics of synchronization. This direction has been a focus of research in recent years (1)(2)(3)(4)(5). At present, most of the synchronization research on complex networks has been done to investigate the impact of topology on the synchronization capability, but the synchronization process per se has rarely been studied.…”

Lag synchronization of coupled time-delayed FitzHugh–Nagumo neural networks via feedback control

“…The synchronization of brain networks is essential for normal functioning, and understanding its dynamics is important to many aspects of our lives 27 . Research on synchronization is vital in revealing the role of communication cells in the neural network structure [28][29][30] .…”

Cellular Synchronisation through Unidirectional and Phase-Gated Signalling

“…The oscillators monitor constantly the phase difference between them and minimize it. A generic mathematical framework that captures these phenomena has been proposed by Kuramoto(Kuramoto, 2012; Strogatz, 2000) and is still widely applied to understand among others, the coordinated behaviour of cellular(Yoshioka-Kobayashi et al, 2020) and human networks(Saw et al, 2019; Shahal et al, 2020). Despite the mathematical elegance and broad applicability of this model, it makes specific assumptions about the symmetric behaviour of the oscillators, their continuous and bidirectional communication.…”