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Berlin 2015 – scientific programme

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BP: Fachverband Biologische Physik

BP 8: Neurophysics II

BP 8.9: Talk

Monday, March 16, 2015, 16:45–17:00, H 1058

Self-consistent spectra in recurrent spiking networks — •Stefan Wieland1,2 and Benjamin Lindner1,21Bernstein Center for Computational Neuroscience Berlin, Germany — 2Humboldt University Berlin, Germany

Firing patterns in cortical networks are often modeled with Poissonian spike trains. Demanding self-consistency at the level of firing rates, i.e. that spike trains driving a neuron possess the same firing rate as the spike train they evoke, then yields a tractable analytic description of network dynamics. However, output spike trains are usually observed to be non-Poissonian, something a more coherent framework should account for. Here we present iterative schemes that yield self-consistent statistics in recurrent neural networks at the level of spike-train correlations.

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