dorsal/arxiv
View SchemaResponse variability in balanced cortical networks
| Authors | Alexander Lerchner, Cristina Ursta, John Hertz, Mandana Ahmadi, Pauline Ruffiot |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0402022 |
| URL | https://arxiv.org/abs/q-bio/0402022 |
Abstract
We study the spike statistics of neurons in a network with dynamically balanced excitation and inhibition. Our model, intended to represent a generic cortical column, comprises randomly connected excitatory and inhibitory leaky integrate-and-fire neurons, driven by excitatory input from an external population. The high connectivity permits a mean-field description in which synaptic currents can be treated as Gaussian noise, the mean and autocorrelation function of which are calculated self-consistently from the firing statistics of single model neurons. Within this description, we find that the irregularity of spike trains is controlled mainly by the strength of the synapses relative to the difference between the firing threshold and the post-firing reset level of the membrane potential. For moderately strong synapses we find spike statistics very similar to those observed in primary visual cortex.
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"abstract": "We study the spike statistics of neurons in a network with dynamically\nbalanced excitation and inhibition. Our model, intended to represent a generic\ncortical column, comprises randomly connected excitatory and inhibitory leaky\nintegrate-and-fire neurons, driven by excitatory input from an external\npopulation. The high connectivity permits a mean-field description in which\nsynaptic currents can be treated as Gaussian noise, the mean and\nautocorrelation function of which are calculated self-consistently from the\nfiring statistics of single model neurons. Within this description, we find\nthat the irregularity of spike trains is controlled mainly by the strength of\nthe synapses relative to the difference between the firing threshold and the\npost-firing reset level of the membrane potential. For moderately strong\nsynapses we find spike statistics very similar to those observed in primary\nvisual cortex.",
"arxiv_id": "q-bio/0402022",
"authors": [
"Alexander Lerchner",
"Cristina Ursta",
"John Hertz",
"Mandana Ahmadi",
"Pauline Ruffiot"
],
"categories": [
"q-bio.NC"
],
"title": "Response variability in balanced cortical networks",
"url": "https://arxiv.org/abs/q-bio/0402022"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "9e518051-01b6-4591-b504-7d0ca57d0c46",
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"type": "Model",
"variant": "snapshot-2026-03-01",
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