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The dynamic range measures the capacity of a system to discriminate theintensity of an external stimulus. Such an ability is fundamental for livingbeings to survive: to leverage resources and to avoid danger. Consequently, thelarger is the dynamic range, the greater is the probability of survival. Weinvestigate how the integration of different input signals affects the dynamicrange, and in general the collective behavior of a network of excitable units.By means of numerical simulations and a mean-field approach, we explore thenonequilibrium phase transition in the presence of integration. We show thatthe firing rate in random and scale-free networks undergoes a discontinuousphase transition depending on both the integration time and the density ofintegrator units. Moreover, in the presence of external stimuli, we find that asystem of excitable integrator units operating in a bistable regime largelyenhances its dynamic range.

Signal integration enhances the dynamic range in neuronal systems