dorsal/arxiv
View SchemaIntensity Coding in Two-Dimensional Excitable Neural Networks
| Authors | Mauro Copelli, Osame Kinouchi |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0409032 |
| URL | https://arxiv.org/abs/q-bio/0409032 |
| DOI | 10.1016/j.physa.2004.10.043 |
| Journal | Physica A 349 (2005) 431-442 |
Abstract
In the light of recent experimental findings that gap junctions are essential for low level intensity detection in the sensory periphery, the Greenberg-Hastings cellular automaton is employed to model the response of a two-dimensional sensory network to external stimuli. We show that excitable elements (sensory neurons) that have a small dynamical range are shown to give rise to a collective large dynamical range. Therefore the network transfer (gain) function (which is Hill or Stevens law-like) is an emergent property generated from a pool of small dynamical range cells, providing a basis for a "neural psychophysics". The growth of the dynamical range with the system size is approximately logarithmic, suggesting a functional role for electrical coupling. For a fixed number of neurons, the dynamical range displays a maximum as a function of the refractory period, which suggests experimental tests for the model. A biological application to ephaptic interactions in olfactory nerve fascicles is proposed.
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"abstract": "In the light of recent experimental findings that gap junctions are essential\nfor low level intensity detection in the sensory periphery, the\nGreenberg-Hastings cellular automaton is employed to model the response of a\ntwo-dimensional sensory network to external stimuli. We show that excitable\nelements (sensory neurons) that have a small dynamical range are shown to give\nrise to a collective large dynamical range. Therefore the network transfer\n(gain) function (which is Hill or Stevens law-like) is an emergent property\ngenerated from a pool of small dynamical range cells, providing a basis for a\n\"neural psychophysics\". The growth of the dynamical range with the system size\nis approximately logarithmic, suggesting a functional role for electrical\ncoupling. For a fixed number of neurons, the dynamical range displays a maximum\nas a function of the refractory period, which suggests experimental tests for\nthe model. A biological application to ephaptic interactions in olfactory nerve\nfascicles is proposed.",
"arxiv_id": "q-bio/0409032",
"authors": [
"Mauro Copelli",
"Osame Kinouchi"
],
"categories": [
"q-bio.NC",
"cond-mat.dis-nn",
"cond-mat.stat-mech",
"nlin.CG",
"nlin.PS",
"physics.bio-ph",
"q-bio.TO"
],
"doi": "10.1016/j.physa.2004.10.043",
"journal_ref": "Physica A 349 (2005) 431-442",
"title": "Intensity Coding in Two-Dimensional Excitable Neural Networks",
"url": "https://arxiv.org/abs/q-bio/0409032"
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