Hydrodynamic Limits for Spatially Structured Interacting Neurons
Aline Duarte, Guilherme Ost, Andr\'es Rodr\'iguez

TL;DR
This paper derives a hydrodynamic limit for a spatially structured stochastic neuron model, showing that the empirical distribution converges to a PDE describing the evolution of membrane potentials.
Contribution
It introduces a novel spatially dependent neuron model without mean-field assumptions and proves convergence to a nonlinear hyperbolic PDE.
Findings
Empirical distribution converges to a PDE as 0.
The limiting PDE is of hyperbolic type, capturing neuron interactions.
Electrical synapses induce synchronization effects in the model.
Abstract
In this paper we study the hydrodynamic limit for a stochastic process describing the time evolution of the membrane potentials of a system of neurons with spatial dependency. We do not impose on the neurons mean-field type interactions. The values of the membrane potentials evolve under the effect of chemical and electrical synapses and leak currents. The system consists of neurons embedded in , each spiking randomly according to a point process with rate depending on both its membrane potential and position. When neuron spikes, its membrane potential is reset to a resting value while the membrane potential of is increased by a positive value , if influences . Furthermore, between consecutive spikes, the system follows a deterministic motion due both to electrical synapses and leak currents. The electrical synapses are involved…
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