Generic origins of irregular spiking in neocortical networks

We identify generic sources of complex and irregular spiking in biological neural networks. For the network description, we operate on a mathematicall y exact mesoscopic approach. Starting from experimental data, we determine exact properties of noise-driven, binary neuron interaction and extrapolate from there to properties of more complex types of interaction. Our approac h fills a gap between approaches that start from detailed biophysically mot ivated simulations but fail go make mathematically exact global predictions , and approaches that are able to make exact statements but only on levels of description that are remote from biology. As a consequence of the approa ch, a novel coding scheme emerges, shedding new light on local information processing in biological neural networks.