The effects of inhibitory neuron fraction on the dynamics of an avalanching neural network

The statistical analysis of the collective neural activity known as avalanches provides insight into the proper behavior of brains across many species. In this talk we present a neural network model based on the work of Lombardi, Herrmann, de Arcangelis et al. that captures the relevant dynamics of neural avalanches, and we show how the active neuron fraction can be used as a control mechanism to introduce exponential cut-offs in the distributions of avalanche strength and duration, transition the power spectral density of the network out of an epileptic regime, and drive the evolution of the network structure over time.