Volume 14 Supplement 1

Abstracts from the Twenty Second Annual Computational Neuroscience Meeting: CNS*2013

Open Access

Generalized synchronous output of neural populations - does it only encode fast stimulus components?

BMC Neuroscience201314(Suppl 1):P244


Published: 8 July 2013

Neurons are subject to intrinsic noise, which influences the information transmission of an incoming signal. Which information can we derive from a population of noisy neurons, that are uncoupled, but driven by a common broadband stimulus? Intuitively, one expects that the times where the action potentials of the different neurons coincide (synchronous spikes), contain different information about the common stimulus than the output of a single neuron does.

Indeed, experiments in a electro-sensory model system [1] revealed that synchronous spikes encode preferentially fast (high-frequency) components of the stimulus, i.e. synchrony acts as an information filter. A recent theoretical study [2] confirmed this finding and uncovered the stochastic mechanism of this filter.

To simplify the analytical approach, Ref. [2] used a rather strict measure of synchrony: all neurons in the population have to fire within a short time window. Here we generalize this to a measure of the synchronous output, for which only m out of n neurons in the population have to fire in synchrony. We inspect, how well this measure works for different ratios m/n and present an analytical approach to the spectral coherence function that characterizes the information transfer of the stimulus to the synchronous output. We discuss under which conditions this generalized synchrony acts as a band-pass filter.



This work was supported by Bundesministerium für Bildung und Forschung grant 01GQ1001A.

Authors’ Affiliations

Bernstein Center for Computational Neuroscience
Institute for Physics, Humboldt-Universität zu Berlin


  1. Middleton JW, Longtin A, Benda J, Maler L: Postsynaptic Receptive Field Size and Spike Threshold Determine Encoding of High-Frequency Information Via Sensitivity to Synchronous Presynaptic Activity. Journal of Neurophysiology. 2009Google Scholar
  2. Sharafi N, Benda J, Lindner B: Information filtering by synchronous spikes in a neural population. Journal of Computational Neuroscience. 2012Google Scholar


© Kruscha and Lindner; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.