Neocortex's small world of fractal coupling

Biological neocortical neurons are arranged in a columnar clustered architecture. Using a mathematical model in which the clustering properties can be monitored by means of a connectivity probability function, we investigate the information propagation in the associated networks, by means of simulations and a semi-analytical approach. Our analysis demonstrates that for systems with n-nearest neighbor coupling, the information propagation increases linearly in the neighbor order n. For fractal coupling, shown to give rise to small-world network characteristics, in contrast, an enhanced dependence is found, that, in our model of the neocortex, quickly saturates at a high level, indicating the superiority of this network type