dorsal/arxiv
View SchemaMean field methods for cortical network dynamics
| Authors | John Hertz, Alexander Lerchner, Mandana Ahmadi |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0402023 |
| URL | https://arxiv.org/abs/q-bio/0402023 |
Abstract
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.
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"abstract": "We review the use of mean field theory for describing the dynamics of dense,\nrandomly connected cortical circuits. For a simple network of excitatory and\ninhibitory leaky integrate-and-fire neurons, we can show how the firing\nirregularity, as measured by the Fano factor, increases with the strength of\nthe synapses in the network and with the value to which the membrane potential\nis reset after a spike. Generalizing the model to include conductance-based\nsynapses gives insight into the connection between the firing statistics and\nthe high-conductance state observed experimentally in visual cortex. Finally,\nan extension of the model to describe an orientation hypercolumn provides\nunderstanding of how cortical interactions sharpen orientation tuning, in a way\nthat is consistent with observed firing statistics.",
"arxiv_id": "q-bio/0402023",
"authors": [
"John Hertz",
"Alexander Lerchner",
"Mandana Ahmadi"
],
"categories": [
"q-bio.NC"
],
"title": "Mean field methods for cortical network dynamics",
"url": "https://arxiv.org/abs/q-bio/0402023"
},
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"type": "Model",
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