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The small-world property in the context of complex networks impliesstructural benefits to the processes taking place within a network, such asoptimal information transmission and robustness. In this paper, we study amodel network of integrate-and-fire neurons that are subject toactivity-dependent synaptic plasticity. We find the learning rule that givesrise to a small-world structure when the collective dynamics of the systemreaches a critical state which is characterised by power-law distributions ofactivity clusters. Moreover, by analysing the motif profile of the networks, weobserve that bidirectional connectivity is impaired by the effects of this typeof plasticity.

Small-world structure induced by spike-timing-dependent plasticity in networks with critical dynamics