Mean field methods for cortical network dynamics

J. Hertz, Alexander Lerchner, M. Ahmadi

Research output: Contribution to journalJournal articleResearchpeer-review


We review the use of mean field theory for describing the dynamics of dense, randomly connected cortical circuits. For a simple network of excitatory and inhibitory leaky integrate- and-fire neurons, we can show how the firing irregularity, as measured by the Fano factor, increases with the strength of the synapses in the network and with the value to which the membrane potential is reset after a spike. Generalizing the model to include conductance-based synapses gives insight into the connection between the firing statistics and the high- conductance state observed experimentally in visual cortex. Finally, an extension of the model to describe an orientation hypercolumn provides understanding of how cortical interactions sharpen orientation tuning, in a way that is consistent with observed firing statistics
Original languageEnglish
Book seriesComputational Neoroscience: Cortical Dynamics Lecture Notes in Computer Science
Pages (from-to)71-89
Publication statusPublished - 2004

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