Predicting spike-timing of a thalamic neuron using a stochastic synaptic model

A twofold spike-timing dependent stochastic synaptic model is used along with a leaky Integrate-and-Fire neuronal model to predict the spike timing of a single post-synaptic neuron in the lateral geniculate nucleus, knowing the spike train on the pre-synaptic side (i.e. in a retinal ganglion cell). In this synaptic model, spike-timing dependency is introduced for both the magnitude and relaxation of the dynamics representing the synaptic action. The results show that the used model is able to reliably predict the exact timing of spikes. These results and the model are the winner of a recent international competition.