A robust balancing mechanism for spiking neural networks

Abstract

Dynamical balance of excitation and inhibition is usually invoked to explain the irregular low firing activity observed in the cortex. We propose a robust nonlinear balancing mechanism for a random network of spiking neurons, in absence of strong external currents. The mechanism exploits the plasticity of excitatory-excitatory synapses induced by short-term depression. A simple self-consistent analysis accompanied by direct simulations shows the emergence and stability of a balanced asynchronous state in the thermodynamic limit. This regime is essentially fluctuation driven and characterized by highly irregular spiking dynamics of all neurons.