In this paper, we first explain basic concepts of complex networks, which have attracted broad interests in the last decade. Then, we introduce a recent study on the relation between spike-timing-dependent plasticity and the emergent structure of neural networks. Synaptic plasticity facilitates formation of feedforward structure in neural networks with pacemakers, and it lessens the threshold for frequency synchrony in comparison to the case of networks with quenched synapses.
I describe the small-world effect and its relation to the notion of small-world networks. Small-world networks have been observed in structural and functional brain connectivity. Their origin remains a mystery to date. I review recent work that suggests that these structures originate from random initial conditions through adaptive rewiring and discuss the evidence for this proposal.
A system's structure constrains its function. The cerebral cortex is a network of multiple interconnected cortical areas, each of which can be defined as a spatially confined unit. Although patterns of cortical connectivity have been extensively studied, we are gaining further insight into cortical organizations by using computational approaches. In parallel, recent evidence indicates that the abundance of recurring elementary interaction patterns in complex networks, called network motifs, carry significant information about their overall organization. Here I review the structural organization of mammalian cortical networks from the viewpoint of network science; I then summarize recent advances in related fields.