Neurons compute and communicate by transforming synaptic input patterns into output
spike trains. The nature of this transformation depends crucially on the properties of voltage …

Transmission of information is an important function of cortical neurons, so it is conceivable
that they have evolved to transmit information efficiently, with low noise and high temporal …

While spike timing has been shown to carry detailed stimulus information at the sensory
periphery, its possible role in network computation is less clear. Most models of computation …

Neuronal action potentials or spikes provide a long-range, noise-resistant means of
communication between neurons. As point processes single spikes contain little information …

The concept that neural information is encoded in the firing rate of neurons has been the
dominant paradigm in neurobiology for many years. This paradigm has also been adopted …

In the present overview, our wish is to demystify some aspects of coding with spike-timing,
through a simple review of well-understood technical facts regarding spike coding. Our goal …

Networks based on coordinated spike coding can encode information with high efficiency in
the spike trains of individual neurons. These networks exhibit single-neuron variability and …

Recent experimental reports have suggested that cortical networks can operate in regimes
were sensory information is encoded by relatively small populations of spikes and their …

How do neural networks learn to represent information? Here, we address this question by
assuming that neural networks seek to generate an optimal population representation for a …

Networks of spiking neurons are very powerful and versatile models for biological and
artificial information processing systems. Especially for modelling pattern analysis tasks in a …