CONICET | Buscador de Institutos y Recursos Humanos

There are phenomena in the nature in which some elements of a system present the same rhythmic behaviour. When this occurs, we say that there is a synchronization between the elements or parts of the system. An example of this phenomenon is the synchronization of the neuronal activity in the brain, in particular in the visual cortex of mammals, where it is possible to observe diﬀerent patterns of activity. In order to understand the emergence of these patterns we model each neuron as a simple phase oscillator, and, as a result of the coupling between neurons, a synchronization of the phases arises under some circumstances. In this work we analyse the formation of patterns using a scale-free topology of connections. With the purpose of making a more realistic model, this network is embedded in a low-dimensional Euclidean space and the interaction function is modelled with a mexican hat function that depends on the distance and also on the location of the site in the network. We analyze the parameters that allow us to obtain diﬀerent sets of patterns, such as bubbles, oriented stripes or labyrinths. Subsequently, we characterize quantitatively the patterns obtained. We compare our results with real data obtained in ferret visual cortex.