Stochastic oscillations produce dragon king avalanches in self-organized quasi-critical systems

Understand

In the last decade, several models with network adaptive mechanisms (link deletion-creation, dynamic synapses, dynamic gains) have been proposed as examples of self-organized criticality (SOC) to explain neuronal avalanches.

• However, all these systems present stochastic oscillations hovering around the critical region that are incompatible with standard SOC.
• This phenomenology has been called self-organized quasi-criticality (SOqC).
• Here we make a linear stability analysis of the mean field fixed points of two SOqC systems: a fully connected network of discrete time stochastic spiking neurons with firing rate adaptation produced by dynamic neuronal gains and an excitable cellular automata with depressing synapses.