Networks of integrate-and-fire neuron using rank order coding A: How to implement spike time dependent Hebbian plasticity

Based on neurophysiological observations on the behavior of synapses, spike time dependent Hebbian plasticity is a novel extension to the modeling of the Hebb rule. This rule has enormous importance in the learning of spiking neural networks (SNN) but its mechanisms and computational properties are still to be explored. In this article, we present a generative model for spike time dependent pla sticity based on a simplified model of the synaptic kinetic. We then explor e the fitting of this model to experimental data and review some of its dyn amical properties. Finally, we extend this model to a simplified model of i ntegrate-and-fire (IF) neurons network using rank order coding. (C) 2001 El sevier Science B.V. All rights reserved.