  The synchronization of human networks is essential for our civilization, and
understanding the motivations, behavior, and basic parameters that govern the
dynamics of human networks is important in many aspects of our lives. Human
ensembles have been investigated in recent years, but with very limited control
over the network parameters and in noisy environments. In particular, research
has focused predominantly on all-to-all coupling, whereas current social
networks and human interactions are often based on complex coupling
configurations, such as nearest-neighbor coupling and small-world networks.
Because the synchronization of any ensemble is governed by its network
parameters, studying different types of human networks while controlling the
coupling and the delay is essential for understanding the dynamics of different
types of human networks. We studied the synchronization between professional
violin players in complex networks with full control over the network
connectivity, coupling strength of each connection, and delay. We found that
the usual models for coupled networks, such as the Kuramoto model, cannot be
applied to human networks. We found that the players can change their
periodicity by a factor of three to find a stable solution to the coupled
network, or they can delete connections by ignoring frustrating signals. These
additional degrees of freedom enable new strategies and yield better solutions
than are possible within current models. Our results may influence numerous
fields, including traffic management, epidemic control, and stock market
dynamics.
