Vibrational resonance in feedforward neuronal network with unreliable synapses

In this paper, we investigate vibrational resonance in feedforward neuronal network coupled in an all-to-all fashion. In contrast to earlier most work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on signal propagation in this work. It is shown that the neurotransmitter release probability and excitatory synaptic strength largely influence the signal propagation, and better tuning of these synaptic parameters makes the feedforward neuronal network support stable signal propagation. Furthermore, it is found that high-frequency driving plays important roles in causing the response of the feedforward neuronal network to subthreshold low-frequency signal and strengthening the ability of the signal propagation between layers. In particular, the optimal amplitude of high-frequency driving is largely influenced by the stochastic effect of neurotransmitter release and the coupling strength. Finally, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. It is demonstrated that unreliable synaptic coupling is more efficient than the random coupling for the transmission of local input signal. Considering that unreliable synapses are inevitable in neuronal communication, the presented results could have important implications for the weak signal detection and information propagation in neural systems.