Importance of Backbones in the Dynamics of Neuronal Networks

Abstract

This project investigates the collective dynamics of neuronal networks obtained from an experimental culture and several structural backbone models. The network dynamics are simulated using the Izhikevich model under different levels of noise and excitatory strength. The study compares the collective behavior of the real culture network and the synthetic topologies, namely: the random geometric graph, the minimum spanning tree, and the efficiency cost optimization. To characterize the emerging dynamics, measures of global synchronization and functional complexity are applied to the spiking activity. These metrics allow for a systematic comparison of the dynamical regimes associated with each topology. The results reveal significant differences in synchronization patterns and complexity across network structures, indicating that the observed phenomenology is strongly influenced by the underlying topology.