Model framework for emergence of synchronized oscillations

Autonomy is an important concept when investigating the mechanism whereby biological systems exhibit flexibility against unpredictable environmental changes. Herein we propose a parameter-tuning algorithm, based on a selection principle, that allows the emergence of synchronization between populations of oscillators through autonomous changes of the intrinsic parameters. With the algorithm, the populations exhibit self-recovery of the synchronized state after the existing synchronized state is broken suddenly; that is, the system chooses appropriate values of the intrinsic parameters to recover the synchronized state. We also propose a continuous model in which the selection is described by the replicator model and the parameter values are determined by the density profile of the oscillators in parameter space.