High conductance states in a mean field cortical network model
Abstract
Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1 due to the tendency of spikes being clustered into bursts. We show that this behavior emerges naturally in a balanced cortical network model with random connectivity and conductance-based synapses. We employ mean field theory with correctly colored noise to describe temporal correlations in the neuronal activity. Our results illuminate the connection between two independent experimental findings: high conductance states of cortical neurons in their natural environment, and variable non-Poissonian spike statistics with Fano factors greater than 1.
Keywords
Cite
@article{arxiv.q-bio/0402026,
title = {High conductance states in a mean field cortical network model},
author = {Alexander Lerchner and Mandana Ahmadi and John Hertz},
journal= {arXiv preprint arXiv:q-bio/0402026},
year = {2007}
}
Comments
7 pages, 3 figures, presented at CNS 2003, to be published in Neurocomputing