Eliminating synchronization of coupled neurons adaptively by using feedback coupling with heterogeneous delays

In this paper, we present an adaptive scheme involving heterogeneous delay interactions to suppress synchronization in a large population of oscillators. We analytically investigate the incoherent state stability regions for several specific kinds of distributions for delays. Interestingly, we find that, among the distributions that we discuss, the exponential distribution may offer great convenience to the performance of our adaptive scheme because this distribution renders an unbounded stability region. Moreover, we demonstrate our scheme in the realization of synchronization elimination in some representative, realistic neuronal networks, which makes it possible to deepen the understanding and even refine the existing techniques of deep brain stimulation in the treatment of some synchronization-induced mental disorders.

Automated summary

The paper introduces an adaptive scheme with heterogeneous delay interactions to suppress synchronization in a large population of oscillators, highlighting the potential advantages of using an exponential distribution. The scheme successfully demonstrates synchronization elimination in realistic neuronal networks, providing insights for deepening the understanding and refining existing techniques of deep brain stimulation in treating synchronization-induced mental disorders.