The past decades have seen an explosive growth in accumulation of experimental data in neuroscience research. The detailed anatomical and physiological data alone, however, are not enough to understand how the nervous system works. It is the recognition of this fact that makes modeling studies a significant part of mainstream research in neuroscience. The combination of theoretical methods, including mathematical analyses and computer simulations, together with modern experimental techniques has led to the emergence of a new discipline of computational neuroscience with the ultimate goal of explaining how neural signals represent and process information in the brain. Modeling of neuronal networks is a powerful tool that enables accomplishment of this goal by understanding how specific parts of the nervous system perform certain operations (for instance, learning specific motor skills, computing the direction of reaching movement, decoding spatial information, etc.) and is complementary to traditional techniques in neuroscience research.