LIN Xiang-hong, ZHANG Tian-wen. An Integrate-and-Fire Neuron Model with Exponential Synaptic Conductances for Event-Driven Simulation Strategy[J]. Acta Electronica Sinica, 2008, 36(8): 1495-1501.
DOI:
LIN Xiang-hong, ZHANG Tian-wen. An Integrate-and-Fire Neuron Model with Exponential Synaptic Conductances for Event-Driven Simulation Strategy[J]. Acta Electronica Sinica, 2008, 36(8): 1495-1501.DOI:
An Integrate-and-Fire Neuron Model with Exponential Synaptic Conductances for Event-Driven Simulation Strategy
In this paper we propose a novel integrate-and-fire(IF)neuron model with exponential synaptic conductances that can be simulated exactly.The postsynaptic potentials and spontaneous discharge statistics of the new model are compared with those of commonly used models
such as the leaky IF model with instantaneous synaptic interactions or the passive membrane equation(PME)model with exponential synaptic conductances in which conductances are explicitly integrated.The proposed model is much closer to the PME model with respect to the spiking response dynamics
while still being nearly as computationally efficient as simple leaky IF model.Then we present an event-driven simulation strategy for the new model.Using event-driven and clock-driven simulation strategies we simulate random network with dynamic synapses
the results indicate that(1)the simulation time scales linearly with the total number of spiking events in the event-driven simulation strategies and(2)the temporal precision of spiking events impacts on neuronal dynamics of network in the different simulation strategies.