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Oscillatory network coding of a global stimulus

The pyramidal cells of weakly electric fish respond to environmental broadband electrical stimuli. They have recently been shown to exhibit oscillations in mean firing rate in response to global stimuli that affect the whole body simultaneously similar to communication stimuli for these animals. In contrast, for spatially localized stimuli such as those produced by prey, the firing rate simply fluctuates around a constant mean. This switch in coding strategy relies on delayed negative (inhibitory) feedback connections in the neural network. We first summarize these experimental findings, as well as our mathematical modeling of this effect using a globally-coupled delayed inhibitory network of leaky integrate-and-fire neurons (LIF's). Here we study the mechanism of the transition from oscillatory to non-oscillatory firing states in such networks. This is done using simulations of a simpler network of LIF's with current based Gaussian white noise stimuli, rather than conductance based bandlimited Gaussian stimuli. We focus on the effect of feedback gain, current bias, and stimulus intensity on the oscillation under global conditions, and see how the decrease of these parameters brings on a response characteristic of the local case. These simulations are performed for a fixed amount of individual synaptic noise to each cell. We also show how insights into these results can be obtained from the analysis of stimulus-induced oscillations in a simpler rate model description of this spatially-extended excitable system.