networks of conductance-based integrate-and-fire neurons

• Main Authors: Pierre Yger, Sami El, Boustani Alain Destexhe, Yves Frégnac
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: sami
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.300.1122; http://cns.iaf.cnrs-gif.fr/files/Topol2010.pdf

Abstract The relationship between the dynamics of neural networks and their patterns of connectivity is far from clear, despite its importance for understanding functional properties. Here, we have studied sparselyconnected networks of conductance-based integrateand-fire (IF) neurons with balanced excitatory and inhibitory connections and with finite axonal propagation speed. We focused on the genesis of states with highly irregular spiking activity and synchronous firing patterns at low rates, called slow Synchronous Irregular (SI) states. In such balanced networks, we examined the “macroscopic ” properties of the spiking activity, such as ensemble correlations and mean firing rates, for different intracortical connectivity profiles ranging from randomly connected networks to networks with Gaussian-distributed local connectivity. We systematically computed the distance-dependent correlations at the extracellular (spiking) and intracellular (membrane potential) levels between randomly assigned pairs of neurons. The main finding is that such properties, when they are averaged at a macroscopic scale, are invariant with respect to the different connectivity patterns, Action Editor: Mark van Rossum Pierre Yger and Sami El Boustani contributed equally. Electronic supplementary material The online version of this article (doi:10.1007/s10827-010-0310-z) contains supplementary material, which is available to authorized users.