Complete and partial synchronization in empirical brain networks

Abstract

The chimera state, characterized by the coexistence of synchronization and asynchronization in a network, associates with special brain functions and disorders. This paper studies the chimera state in empirical networks reconstructed from the human, macaque, marmoset, and mouse brain data and also a constructed random network. The structural properties, such as clustering coefficient, efficiency, and modularity index of the networks, are computed and compared. The degree distributions of networks are also represented, yielding a more different degree distributon for the mouse network with the others. To determine the collective behavior of the network, the global and local order parameters and the master stability function are applied. Under increasing coupling strength, all the networks generically display the sequence of transitions from asynchronous state, over chimeras to the synchronous regime. There are also multistable regions during the transitions. The results represent that based on the coupling strength required to reach a fully synchronized state, human, marmoset, and macaque networks have relatively similar dynamical regions of synchronization. Mouse and random networks, however, require considerably stronger and weaker couplings, respectively. Changing the dynamics of the individual neurons shows that the asynchronous and chimera regions extend as the dynamics of the neurons become more complex.