Parabolic bursting in an excitable system coupled with a slow oscillation
SIAM Journal on Applied Mathematics
On numerical simulations of integrate-and-fire neural networks
Neural Computation
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Firing rate of the noisy quadratic integrate-and-fire neuron
Neural Computation
Exact simulation of integrate-and-fire models with synaptic conductances
Neural Computation
Type i membranes, phase resetting curves, and synchrony
Neural Computation
Simple model of spiking neurons
IEEE Transactions on Neural Networks
Spike-timing error backpropagation in theta neuron networks
Neural Computation
Simplicity and efficiency of integrate-and-fire neuron models
Neural Computation
A Markovian event-based framework for stochastic spiking neural networks
Journal of Computational Neuroscience
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Event-driven strategies have been used to simulate spiking neural networks exactly. Previous work is limited to linear integrate-and-fire neurons. In this note, we extend event-driven schemes to a class of nonlinear integrate-and-fire models. Results are presented for the quadratic integrate-and-fire model with instantaneous or exponential synaptic currents. Extensions to conductance-based currents and exponential integrate-and-fire neurons are discussed.