Stochastic Resonance in a Small-World Network of Rulkov Neurons with Electrical and Chemical Synapses Under an Alternating Electric Field and Synaptic Transmission Delay

Biological neural systems can use moderate noise to enhance their responses to weak stimuli, and this process is affected by synaptic transmission, network structure, transmission timing, and external electric fields. We constructed a Watts–Strogatz network of Rulkov neurons with electrical and chemical synapses, Gaussian noise, an alternating electric field, and synaptic transmission delay to examine stochastic resonance in response to a periodic signal that produced a weak noise-free population response at its fundamental frequency. All tested network configurations showed a maximum response at an intermediate noise intensity. Increasing the chemical-synapse probability increased the peak response in the initial synaptic-composition scan, whereas the effect of network rewiring varied with synaptic composition. After transmission delay was introduced, the field setting associated with a stronger response varied with synaptic composition and delay. Several delay-dependent response maxima shifted when the input period changed. These results characterize how synaptic composition, transmission delay, and external-field settings shaped the input-frequency response within the modeled neuronal network.