Izhikevich neuron model in networks with topographical obstacles

Abstract

The aim of this study is to examine the behaviour of a simulated neuronal network in which neurons are located in topographical obstacles shaped as parallel tracks that reduce the capacity of neurons to interconnect. The simulations show that three different scenarios of collective activity are observed, depending on the connectivity between neurons, from few isolated groups of neurons to the entire synchronous activation of the network. We also observed that, when neurons strongly follow the topographical pattern, the activity of the system is highly tied to the structure of the network, indicating that dynamics (functional connectivity) is highly linked to structural one.