Dynamics of a large system of spiking neurons with synaptic delay
Federico Devalle, Ernest Montbri\'o, Diego Paz\'o

TL;DR
This paper studies the dynamics of large networks of spiking neurons with synaptic delays, revealing complex synchronization patterns, bifurcations, and novel states, with analytical and numerical approaches comparing excitatory and inhibitory couplings.
Contribution
It provides an exact reduction of a heterogeneous QIF neuron network to firing rate equations and uncovers new partially synchronized states not seen in classical models.
Findings
Identification of various partially synchronized states including collective chaos and QPS.
Analytical phase diagrams for homogeneous and heterogeneous populations.
Comparison showing qualitative agreement with traditional firing rate models only under specific conditions.
Abstract
We analyze a large system of heterogeneous quadratic integrate-and-fire (QIF) neurons with time delayed, all-to-all synaptic coupling. The model is exactly reduced to a system of firing rate equations that is exploited to investigate the existence, stability and bifurcations of fully synchronous, partially synchronous, and incoherent states. In conjunction with this analysis we perform extensive numerical simulations of the original network of QIF neurons, and determine the relation between the macroscopic and microscopic states for partially synchronous states. The results are summarized in two phase diagrams, for homogeneous and heterogeneous populations, which are obtained analytically to a large extent. For excitatory coupling, the phase diagram is remarkably similar to that of the Kuramoto model with time delays, although here the stability boundaries extend to regions in parameter…
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