Electrical and chemical synapses shape the dynamics of neural networks, and their functional roles in information processing have been a longstanding question in neurobiology. In this paper, we investigate the role of synapses on the optimization of the phenomenon of self-induced stochastic resonance in a delayed multiplex neural network by using analytical and numerical methods. We consider a two-layer multiplex network in which, at the intra-layer level, neurons are coupled either by electrical synapses or by inhibitory chemical synapses. For each isolated layer, computations indicate that weaker electrical and chemical synaptic couplings are better optimizers of self-induced stochastic resonance. In addition, regardless of the synaptic strengths, shorter electrical synaptic delays are found to be better optimizers of the phenomenon than shorter chemical synaptic delays, while longer chemical synaptic delays are better optimizers than longer electrical synaptic delays; in both cases, the poorer optimizers are, in fact, worst. It is found that electrical, inhibitory, or excitatory chemical multiplexing of the two layers having only electrical synapses at the intra-layer levels can each optimize the phenomenon. Additionally, only excitatory chemical multiplexing of the two layers having only inhibitory chemical synapses at the intra-layer levels can optimize the phenomenon. These results may guide experiments aimed at establishing or confirming to the mechanism of self-induced stochastic resonance in networks of artificial neural circuits as well as in real biological neural networks.

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多重神经网络中的最佳自感应随机共振：电突触与化学突触

电和化学突触塑造了神经网络的动力学，它们在信息处理中的功能作用一直是神经生物学中长期存在的问题。在本文中，我们通过分析和数值方法研究了突触在延迟多重神经网络中自诱导随机共振现象优化中的作用。我们考虑一个两层多路网络，其中在层内水平上，神经元通过电突触或抑制性化学突触耦合。对于每个隔离层，计算表明较弱的电和化学突触耦合是自感应随机共振的更好优化器。此外，无论突触强度如何，较短的电突触延迟被发现比较短的化学突触延迟更好地优化该现象，而较长的化学突触延迟比较长的电突触延迟是更好的优化器；在这两种情况下，较差的优化器实际上是最差的。研究发现，在层内水平仅具有电突触的两层的电、抑制或兴奋性化学复用可以各自优化该现象。此外，只有层内水平仅具有抑制性化学突触的两层的兴奋性化学复用才能优化该现象。这些结果可以指导旨在建立或确认人工神经回路网络以及真实生物神经网络中自诱导随机共振机制的实验。