Enhancing weak signal transmission through a feedforward network

Phase-noise-induced resonance in arrays of coupled excitable neural models

Recently, it is observed that, in a single neural model, phase noise (time-varying signal phase) arising from an external stimulating signal can induce regular spiking activities even if the signal is subthreshold. In addition, it is also uncovered that there exists an optimal phase noise intensity at which the spiking rhythm coincides with the frequency of the subthreshold signal, resulting in a phase-noise-induced resonance phenomenon. However, neurons usually do not work alone, but are connected in the form of arrays or blocks. Therefore, we study the spiking activity induced by phase noise in arrays of globally and locally coupled excitable neural models. We find that there also exists an optimal phase noise intensity for generating large neural response and such an optimal value is significantly decreased compared to an isolated single neuron case, which means the detectability in response to the subthreshold signal of neurons is sharply improved because of the coupling. In addition, we reveal two new resonance behaviors in the neuron ensemble with the presence of phase noise: there exist optimal values of both coupling strength and system size, where the coupled neurons generate regular spikes under subthreshold stimulations, which are called as coupling strength and system size resonance, respectively. Finally, the dependence of phase-noise-induced resonance on signal frequency is also examined.