Synchrony and antiphase state in coupled stochastic neural oscillators

Abstract

Synchrony and antiphase phase locking in synaptically coupled neurons have been studied by employing numerical simulations. By using a Morris-Leicar (ML) model of two coupled stochastic neural oscillators, the effect of noise on the phase dynamics is extensively investigated in two different synaptic-coupling schemes; reciprocal excitatory and excitatoryinhibitory synapses. All possible dynamical features are presented in the parameter space of two important branching parameters, the coupling strength g(syn) and the synaptic time delay tau(d). In this work, antiphase states are observed and analyzed as the breaking dynamics of synchrony. As a transition state from synchrony to antiphase phase locking in the stochastic. system, intermittent antiphase states are also reported.