Abstract
Short-term dynamical synapses increase the computational power of neuronal networks. These synapses act as additional filters to the inputs of a neuron before the subsequent integration of these signals at its cell body. In this work, we describe a model of depressing and facilitating synapses derived from a hardware circuit implementation. This model is equivalent to theoretical models of short-term synaptic dynamics in network simulations. These circuits have been added to a network of leaky integrate-and-fire neurons. A cortical model of direction-selectivity that uses short-term dynamic synapses has been implemented with this network.