Dynamics of a network of quadratic integrate-and-fire neurons with bimodal heterogeneity

Abstract

An exact low-dimensional system of mean-field equations for an infinite-size network of pulse coupled integrate-and-fire neurons with a bimodal distribution of an excitability parameter is derived. Bifurcation analysis of these equations shows a rich variety of dynamic modes that do not exist with a unimodal distribution of this parameter. New modes include multistable equilibrium states with different levels of the spiking rate, collective oscillations and chaos. All oscillatory modes coexist with stable equilibrium states. The mean field equations are a good approximation to the solutions of a microscopic model consisting of several thousand neurons.

References in corpus (4)

• Macroscopic description for networks of spiking neurons
• Exact Results for the Kuramoto Model with a Bimodal Frequency Distribution
• Symmetry breaking in two interacting populations of quadratic integrate-and-fire neurons
• Suppression of synchronous spiking in two interacting populations of excitatory and inhibitory quadratic integrate-and-fire neurons

Cited by in corpus (3)

• Mean-field equations for neural populations with $q$-Gaussian heterogeneities
• Effect of Cauchy noise on a network of quadratic integrate-and-fire neurons with non-Cauchy heterogeneities
• Low-dimensional model for adaptive networks of spiking neurons