Auto organisation d'une carte de neurones par modulation de la règle BCM dans un cadre multimodal
Identifieur interne : 002724 ( Hal/Checkpoint ); précédent : 002723; suivant : 002725Auto organisation d'une carte de neurones par modulation de la règle BCM dans un cadre multimodal
Auteurs : Mathieu Lefort [France] ; Yann Boniface [France] ; Bernard Girau [France]Source :
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Abstract
The cortex must permanently deal with stimuli coming from the environment, perceived through different sensors spatially separated. These stimuli converge in the cortex to be processed together in order to construct a multisensory and coherent view of the world. When somebody is hearing /ba/ and is simultaneously viewing the lips movements corresponding to /ga/, he is perceiving /da/. This phenomenon, known as McGurk effect, reveals the cross correlation between different modalities. Some cortical areas are mainly dedicated to the processing of a specific perception. These areas are topographically organized, meaning that two spatially close neurons respond to close stimuli. The purpose of this paper is to modify the BCM synaptic rule to obtain a self organization of a neuronal map. We introduce a feedback modulation of the learning rule, representing multimodal constraints of the environment. This feedback will be obtained by using a multimap and multilevel architecture of modality assembling.
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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></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>BCM rule</term><term>feedback modulation</term><term>multimodality</term><term>self organization</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The cortex must permanently deal with stimuli coming from the environment, perceived through different sensors spatially separated. These stimuli converge in the cortex to be processed together in order to construct a multisensory and coherent view of the world. When somebody is hearing /ba/ and is simultaneously viewing the lips movements corresponding to /ga/, he is perceiving /da/. This phenomenon, known as McGurk effect, reveals the cross correlation between different modalities. Some cortical areas are mainly dedicated to the processing of a specific perception. These areas are topographically organized, meaning that two spatially close neurons respond to close stimuli. The purpose of this paper is to modify the BCM synaptic rule to obtain a self organization of a neuronal map. We introduce a feedback modulation of the learning rule, representing multimodal constraints of the environment. This feedback will be obtained by using a multimap and multilevel architecture of modality assembling.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="fr">Auto organisation d'une carte de neurones par modulation de la règle BCM dans un cadre multimodal</title><author role="aut"><persName><forename type="first">Mathieu</forename><surname>Lefort</surname></persName><email>mathieu.lefort@loria.fr</email><idno type="idhal">mathieu-lefort</idno><idno type="halauthor">418935</idno><affiliation ref="#struct-2348"></affiliation></author><author role="aut"><persName><forename type="first">Yann</forename><surname>Boniface</surname></persName><email>Yann.Boniface@loria.fr</email><idno type="halauthor">448815</idno><affiliation ref="#struct-2348"></affiliation></author><author role="aut"><persName><forename type="first">Bernard</forename><surname>Girau</surname></persName><email>Bernard.Girau@loria.fr</email><idno type="halauthor">56303</idno><affiliation ref="#struct-2348"></affiliation></author><editor role="depositor"><persName><forename>Mathieu</forename><surname>Lefort</surname></persName><email>mathieu.lefort@liris.cnrs.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2009-11-23 14:07:53</date><date type="whenWritten">2009-11-27</date><date type="whenModified">2016-05-19 01:04:28</date><date type="whenReleased">2009-11-23 14:38:43</date><date type="whenProduced">2010-01-19</date><date type="whenEndEmbargoed">2009-11-23</date><ref type="file" target="https://hal.archives-ouvertes.fr/hal-00434530/document"><date notBefore="2009-11-23"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.archives-ouvertes.fr/hal-00434530/file/article.pdf"><date notBefore="2009-11-23"></date></ref></edition><respStmt><resp>contributor</resp><name key="142280"><persName><forename>Mathieu</forename><surname>Lefort</surname></persName><email>mathieu.lefort@liris.cnrs.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00434530</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00434530</idno><idno type="halBibtex">lefort:hal-00434530</idno><idno type="halRefHtml">17e congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle - RFIA 2010, Jan 2010, Caen, France. pp.423-430, 2010</idno><idno type="halRef">17e congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle - RFIA 2010, Jan 2010, Caen, France. pp.423-430, 2010</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="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="AFIA">Association Française d'Intelligence Artificielle</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="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="3">National</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="fr">Auto organisation d'une carte de neurones par modulation de la règle BCM dans un cadre multimodal</title><author role="aut"><persName><forename type="first">Mathieu</forename><surname>Lefort</surname></persName><email>mathieu.lefort@loria.fr</email><idno type="idHal">mathieu-lefort</idno><idno type="halAuthorId">418935</idno><affiliation ref="#struct-2348"></affiliation></author><author role="aut"><persName><forename type="first">Yann</forename><surname>Boniface</surname></persName><email>Yann.Boniface@loria.fr</email><idno type="halAuthorId">448815</idno><affiliation ref="#struct-2348"></affiliation></author><author role="aut"><persName><forename type="first">Bernard</forename><surname>Girau</surname></persName><email>Bernard.Girau@loria.fr</email><idno type="halAuthorId">56303</idno><affiliation ref="#struct-2348"></affiliation></author></analytic><monogr><title level="m">RFIA 2010</title><meeting><title>17e congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle - RFIA 2010</title><date type="start">2010-01-19</date><date type="end">2010-01-22</date><settlement>Caen</settlement><country key="FR">France</country></meeting><imprint><biblScope unit="pp">423-430</biblScope><date type="datePub">2010-01-19</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="fr">French</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">self organization</term><term xml:lang="en">BCM rule</term><term xml:lang="en">feedback modulation</term><term xml:lang="en">multimodality</term></keywords><classCode scheme="halDomain" n="info.info-ne">Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">The cortex must permanently deal with stimuli coming from the environment, perceived through different sensors spatially separated. These stimuli converge in the cortex to be processed together in order to construct a multisensory and coherent view of the world. When somebody is hearing /ba/ and is simultaneously viewing the lips movements corresponding to /ga/, he is perceiving /da/. This phenomenon, known as McGurk effect, reveals the cross correlation between different modalities. Some cortical areas are mainly dedicated to the processing of a specific perception. These areas are topographically organized, meaning that two spatially close neurons respond to close stimuli. The purpose of this paper is to modify the BCM synaptic rule to obtain a self organization of a neuronal map. We introduce a feedback modulation of the learning rule, representing multimodal constraints of the environment. This feedback will be obtained by using a multimap and multilevel architecture of modality assembling.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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