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Cross-correlations in sparsely connected recurrent networks of spiking neurons

  • Nicolas Brunel
Part I: Coding and Learning in Biology
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1327)

Abstract

We study the dynamics of sparsely connected recurrent networks composed of excitatory and inhibitory integrate-and-fire (IF) neurons firing at low rates, and in particular cross-Correlations (CC) between spike times of pairs of neurons using both numerical simulations and a recent theory. CCs exhibit damped oscillations with a frequency which depends on synaptic time constants. Individual CCs are shown to depend weakly on synaptic connectivity. They depend more strongly on the firing rates of individual neurons.

Keywords

Global Activity Recurrent Network Oscillatory Limit Cycle Connection Probability Synaptic Delay 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Nicolas Brunel
    • 1
  1. 1.LPS, Ecole Normale SupérieureParis Cedex 05France

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