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We consider the Watts-Strogatz small-world network consisting of subthresholdneurons which exhibit noise-induced spikings. This neuronal network hasadaptive dynamic synaptic strengths governed by the spike-timing-dependentplasticity (STDP). In previous works without STDP, stochastic spikesynchronization (SSS) between noise-induced spikings of subthreshold neuronswas found to occur in a range of intermediate noise intensities throughcompetition between the constructive and the destructive roles of noise. Here,we investigate the effect of additive STDP on the SSS by varying the noiseintensity. Occurrence of a "Matthew" effect in synaptic plasticity is found dueto a positive feedback process. As a result, good synchronization gets bettervia long-term potentiation (LTP) of synaptic strengths, while badsynchronization gets worse via long-term depression (LTD). Emergence of LTP andLTD of synaptic strengths are intensively investigated via microscopic studiesbased on the pair-correlations between the pre- and the post-synaptic IISRs(instantaneous individual spike rates) as well as the distributions of timedelays between the pre- and the post-synaptic spike times. Furthermore, theeffects of multiplicative STDP (which depends on the states) on the SSS arealso studied and discussed in comparison with the case of additive STDP.

Stochastic Spike Synchronization in A Small-World Neural Network with Spike-Timing-Dependent Plasticity