For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-eq...
Richard Naud, Nicolas Marcille, Claudia Clopath, W...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Recent biological experimental findings have shown that the synaptic plasticity depends on the relative timing of the pre- and postsynaptic spikes which determines whether Long Te...
The ability of dynamic synapses with short-term depression to transmit the information present in the presynaptic spike train to the postsynaptic neuron is discussed. Both by mini...
— Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process s...