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Article Dans Une Revue Neural computation. Année : 2005

Categorization of neural excitability using threshold models

Arnaud Tonnelier

Résumé

A classification of spiking neurons according to the transition from quiescence to periodic firing of action potentials is commonly used. Nonbursting neurons are classified into two types, type I and type II excitability. We use simple phenomenological spiking neuron models to derive a criterion for the determination of the neural excitability based on the after potential following a spike. The crucial characteristic is the existence for type II model of a positive overshoot, that is, a delayed after depolarization, during the recovery process of the membrane potential. Our prediction is numerically tested using well-known type I and type II models including the Connor, Walter, & McKown (1977) model and the Hodgkin-Huxley (1952) model.
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Dates et versions

inria-00000581 , version 1 (04-11-2005)
inria-00000581 , version 2 (03-06-2009)

Identifiants

Citer

Arnaud Tonnelier. Categorization of neural excitability using threshold models. Neural computation., 2005, 17 (7), pp.1447--1455. ⟨10.1162/0899766053723087⟩. ⟨inria-00000581v1⟩
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