Categorization of neural excitability using threshold models
Identifieur interne : 001417 ( Hal/Curation ); précédent : 001416; suivant : 001418Categorization of neural excitability using threshold models
Auteurs : Arnaud Tonnelier [France]Source :
- Neural Computation [ 0899-7667 ] ; 2005.
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.
Url:
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: Pour aller vers cette notice dans l'étape Curation :001417
Links to Exploration step
Hal:hal-00390768Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Categorization of neural excitability using threshold models</title><author><name sortKey="Tonnelier, Arnaud" sort="Tonnelier, Arnaud" uniqKey="Tonnelier A" first="Arnaud" last="Tonnelier">Arnaud Tonnelier</name><affiliation wicri:level="1"><hal:affiliation type="researchteam" xml:id="struct-2348" status="OLD"><idno type="RNSR">200018289J</idno><orgName>Neuromimetic intelligence</orgName><orgName type="acronym">CORTEX</orgName><desc><address><country key="FR"></country></address><ref type="url">http://www.inria.fr/equipes/cortex</ref></desc><listRelation><relation active="#struct-160" type="direct"></relation><relation name="UMR7503" active="#struct-441569" type="indirect"></relation><relation active="#struct-300009" type="indirect"></relation><relation active="#struct-300291" type="indirect"></relation><relation active="#struct-300292" type="indirect"></relation><relation active="#struct-300293" type="indirect"></relation><relation active="#struct-2496" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-160" type="direct"><org type="laboratory" xml:id="struct-160" status="OLD"><orgName>Laboratoire Lorrain de Recherche en Informatique et ses Applications</orgName><orgName type="acronym">LORIA</orgName><desc><address><addrLine>Campus Scientifique BP 239 54506 Vandoeuvre-lès-Nancy Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.loria.fr</ref></desc><listRelation><relation name="UMR7503" active="#struct-441569" type="direct"></relation><relation active="#struct-300009" type="direct"></relation><relation active="#struct-300291" type="direct"></relation><relation active="#struct-300292" type="direct"></relation><relation active="#struct-300293" type="direct"></relation></listRelation></org></tutelle><tutelle name="UMR7503" active="#struct-441569" type="indirect"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="ISNI">0000000122597504</idno><idno type="IdRef">02636817X</idno><orgName>Centre National de la Recherche Scientifique</orgName><orgName type="acronym">CNRS</orgName><date type="start">1939-10-19</date><desc><address><country key="FR"></country></address><ref type="url">http://www.cnrs.fr/</ref></desc></org></tutelle><tutelle active="#struct-300009" type="indirect"><org type="institution" xml:id="struct-300009" status="VALID"><orgName>Institut National de Recherche en Informatique et en Automatique</orgName><orgName type="acronym">Inria</orgName><desc><address><addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/en/</ref></desc></org></tutelle><tutelle active="#struct-300291" type="indirect"><org type="institution" xml:id="struct-300291" status="OLD"><orgName>Université Henri Poincaré - Nancy 1</orgName><orgName type="acronym">UHP</orgName><date type="end">2011-12-31</date><desc><address><addrLine>24-30 rue Lionnois, BP 60120, 54 003 NANCY cedex, France</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300292" type="indirect"><org type="institution" xml:id="struct-300292" status="OLD"><orgName>Université Nancy 2</orgName><date type="end">2011-12-31</date><desc><address><addrLine>91 avenue de la Libération, BP 454, 54001 Nancy cedex</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300293" type="indirect"><org type="institution" xml:id="struct-300293" status="OLD"><orgName>Institut National Polytechnique de Lorraine</orgName><orgName type="acronym">INPL</orgName><date type="end">2011-12-31</date><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-2496" type="direct"><org type="laboratory" xml:id="struct-2496" status="OLD"><orgName>INRIA Lorraine</orgName><desc><address><addrLine>615 rue du Jardin Botanique 54600 Villers-lès-Nancy</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/centre-de-recherche-inria/nancy-grand-est</ref></desc><listRelation><relation active="#struct-300009" type="direct"></relation></listRelation></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université Nancy 2</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">HAL</idno><idno type="RBID">Hal:hal-00390768</idno><idno type="halId">hal-00390768</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00390768</idno><idno type="url">https://hal.archives-ouvertes.fr/hal-00390768</idno><date when="2005">2005</date><idno type="wicri:Area/Hal/Corpus">001417</idno><idno type="wicri:Area/Hal/Curation">001417</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Categorization of neural excitability using threshold models</title><author><name sortKey="Tonnelier, Arnaud" sort="Tonnelier, Arnaud" uniqKey="Tonnelier A" first="Arnaud" last="Tonnelier">Arnaud Tonnelier</name><affiliation wicri:level="1"><hal:affiliation type="researchteam" xml:id="struct-2348" status="OLD"><idno type="RNSR">200018289J</idno><orgName>Neuromimetic intelligence</orgName><orgName type="acronym">CORTEX</orgName><desc><address><country key="FR"></country></address><ref type="url">http://www.inria.fr/equipes/cortex</ref></desc><listRelation><relation active="#struct-160" type="direct"></relation><relation name="UMR7503" active="#struct-441569" type="indirect"></relation><relation active="#struct-300009" type="indirect"></relation><relation active="#struct-300291" type="indirect"></relation><relation active="#struct-300292" type="indirect"></relation><relation active="#struct-300293" type="indirect"></relation><relation active="#struct-2496" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-160" type="direct"><org type="laboratory" xml:id="struct-160" status="OLD"><orgName>Laboratoire Lorrain de Recherche en Informatique et ses Applications</orgName><orgName type="acronym">LORIA</orgName><desc><address><addrLine>Campus Scientifique BP 239 54506 Vandoeuvre-lès-Nancy Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.loria.fr</ref></desc><listRelation><relation name="UMR7503" active="#struct-441569" type="direct"></relation><relation active="#struct-300009" type="direct"></relation><relation active="#struct-300291" type="direct"></relation><relation active="#struct-300292" type="direct"></relation><relation active="#struct-300293" type="direct"></relation></listRelation></org></tutelle><tutelle name="UMR7503" active="#struct-441569" type="indirect"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="ISNI">0000000122597504</idno><idno type="IdRef">02636817X</idno><orgName>Centre National de la Recherche Scientifique</orgName><orgName type="acronym">CNRS</orgName><date type="start">1939-10-19</date><desc><address><country key="FR"></country></address><ref type="url">http://www.cnrs.fr/</ref></desc></org></tutelle><tutelle active="#struct-300009" type="indirect"><org type="institution" xml:id="struct-300009" status="VALID"><orgName>Institut National de Recherche en Informatique et en Automatique</orgName><orgName type="acronym">Inria</orgName><desc><address><addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/en/</ref></desc></org></tutelle><tutelle active="#struct-300291" type="indirect"><org type="institution" xml:id="struct-300291" status="OLD"><orgName>Université Henri Poincaré - Nancy 1</orgName><orgName type="acronym">UHP</orgName><date type="end">2011-12-31</date><desc><address><addrLine>24-30 rue Lionnois, BP 60120, 54 003 NANCY cedex, France</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300292" type="indirect"><org type="institution" xml:id="struct-300292" status="OLD"><orgName>Université Nancy 2</orgName><date type="end">2011-12-31</date><desc><address><addrLine>91 avenue de la Libération, BP 454, 54001 Nancy cedex</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300293" type="indirect"><org type="institution" xml:id="struct-300293" status="OLD"><orgName>Institut National Polytechnique de Lorraine</orgName><orgName type="acronym">INPL</orgName><date type="end">2011-12-31</date><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-2496" type="direct"><org type="laboratory" xml:id="struct-2496" status="OLD"><orgName>INRIA Lorraine</orgName><desc><address><addrLine>615 rue du Jardin Botanique 54600 Villers-lès-Nancy</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/centre-de-recherche-inria/nancy-grand-est</ref></desc><listRelation><relation active="#struct-300009" type="direct"></relation></listRelation></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université Nancy 2</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author></analytic><series><title level="j">Neural Computation</title><idno type="ISSN">0899-7667</idno><imprint><date type="datePub">2005</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="it"><term>Neural excitability</term><term>spike-response model</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Categorization of neural excitability using threshold models</title><author role="aut"><persName><forename type="first">Arnaud</forename><surname>Tonnelier</surname></persName><email>arnaud.tonnelier@inria.fr</email><idno type="halauthor">361323</idno><affiliation ref="#struct-2348"></affiliation></author><editor role="depositor"><persName><forename>Arnaud</forename><surname>Tonnelier</surname></persName><email>arnaud.tonnelier@inria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2009-06-03 08:56:37</date><date type="whenModified">2016-05-19 01:09:22</date><date type="whenReleased">2009-06-04 07:46:49</date><date type="whenProduced">2005</date><date type="whenEndEmbargoed">2009-06-03</date><ref type="file" target="https://hal.archives-ouvertes.fr/hal-00390768/document"><date notBefore="2009-06-03"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.archives-ouvertes.fr/hal-00390768/file/Tonnelier_NC_2005.pdf"><date notBefore="2009-06-03"></date></ref></edition><respStmt><resp>contributor</resp><name key="141182"><persName><forename>Arnaud</forename><surname>Tonnelier</surname></persName><email>arnaud.tonnelier@inria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00390768</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00390768</idno><idno type="halBibtex">tonnelier:hal-00390768</idno><idno type="halRefHtml">Neural Computation, Massachusetts Institute of Technology Press (MIT Press), 2005, 17 (7), pp.1447-1455</idno><idno type="halRef">Neural Computation, Massachusetts Institute of Technology Press (MIT Press), 2005, 17 (7), pp.1447-1455</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="INSMI">CNRS-INSMI - INstitut des Sciences Mathématiques et de leurs Interactions</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="LORIA-CSAI" p="LORIA">Systèmes complexes et intelligence artificielle</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="TDS-MACS">Réseau de recherche en Théorie des Systèmes Distribués, Modélisation, Analyse et Contrôle des Systèmes</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Categorization of neural excitability using threshold models</title><author role="aut"><persName><forename type="first">Arnaud</forename><surname>Tonnelier</surname></persName><email>arnaud.tonnelier@inria.fr</email><idno type="halAuthorId">361323</idno><affiliation ref="#struct-2348"></affiliation></author></analytic><monogr><idno type="halJournalId" status="VALID">17364</idno><idno type="issn">0899-7667</idno><idno type="eissn">1530-888X</idno><title level="j">Neural Computation</title><imprint><publisher>Massachusetts Institute of Technology Press (MIT Press)</publisher><biblScope unit="volume">17</biblScope><biblScope unit="issue">7</biblScope><biblScope unit="pp">1447-1455</biblScope><date type="datePub">2005</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="it">Neural excitability</term><term xml:lang="it">spike-response model</term></keywords><classCode scheme="halDomain" n="math.math-ds">Mathematics [math]/Dynamical Systems [math.DS]</classCode><classCode scheme="halDomain" n="scco.neur">Cognitive science/Neuroscience</classCode><classCode scheme="halTypology" n="ART">Journal articles</classCode></textClass><abstract xml:lang="en">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.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Lorraine/explor/InforLorV4/Data/Hal/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001417 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Hal/Curation/biblio.hfd -nk 001417 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Lorraine
|area= InforLorV4
|flux= Hal
|étape= Curation
|type= RBID
|clé= Hal:hal-00390768
|texte= Categorization of neural excitability using threshold models
}}
| This area was generated with Dilib version V0.6.33. |  |