Theory of complex networks has proved as a powerful tool for the study of a large number of natural, social and technological systems. In last years, the complex networks methods have been successfully applied to the research of the structure and function of neural system, both in the large scale, to improve the understanding of the integration-segregation function balance of different brain areas, and in the microscale, as the study of the feedback between structure and dynamics in living neural tissue. For this last purpose, in vitro primary cultures neurons are used to experimentally investigate the morphological evolution of self-organized ensembles of cells into networks. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro and mesoscale properties emerge. By means of numerical models we can identify the physical processes ruling the structure transformations as well as the evolution of the dynamics of the whole system.