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Journal Articles Neural Computation Year : 2005

Categorization of neural excitability using threshold models

Arnaud Tonnelier

Abstract

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 afterpotential following a spike. The crucial characteristic is the existence for type II model of a positive overshoot, i.e. a delayed afterdepolarization, 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 et al. model and the Hodgkin-Huxley model.
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Dates and versions

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

Identifiers

  • HAL Id : inria-00000581 , version 2

Cite

Arnaud Tonnelier. Categorization of neural excitability using threshold models. Neural Computation, 2005, 17 (7), pp.1447-1455. ⟨inria-00000581v2⟩
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