LAUSR

Abstract We study the firing behavior of bistable neurons that are coupled by both electrical and chemical synapses, constituting a hybrid coupled population. We use stochastic Hodgkin–Huxley model neurons for the dynamics of individual bistable units within the population and the connectivity is implemented with a scale-free network topology which is a widely used network paradigm in theoretical studies of neural circuits. By analyzing the electrical activity of both whole population and individual neurons, it is shown that population mean firing rate exhibits a non-monotonic behavior in the space of electrical and chemical coupling strengths. We identify dynamical mechanisms that shape such non-monotonic spiking behavior and show that different types of population spiking patterns can emerge by fine-tuning the coupling strengths of electrical and chemical synapses. Furthermore, we map the transitions between observed dynamical states in the parameter space of interest depending on the level of individual neuron bistability, existence probability of a synapse type and intrinsic ion channel noise.