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A dynamic neural field approach to the covert and overt deployment of spatial attention

Identifieur interne : 002537 ( Main/Exploration ); précédent : 002536; suivant : 002538

A dynamic neural field approach to the covert and overt deployment of spatial attention

Auteurs : Jérémy Fix [France] ; Nicolas P. Rougier [France] ; Frédéric Alexandre [France]

Source :

RBID : Hal:inria-00536374

English descriptors

Abstract

Abstract The visual exploration of a scene involves the in- terplay of several competing processes (for example to se- lect the next saccade or to keep fixation) and the integration of bottom-up (e.g. contrast) and top-down information (the target of a visual search task). Identifying the neural mech- anisms involved in these processes and in the integration of these information remains a challenging question. Visual attention refers to all these processes, both when the eyes remain fixed (covert attention) and when they are moving (overt attention). Popular computational models of visual attention consider that the visual information remains fixed when attention is deployed while the primates are executing around three saccadic eye movements per second, changing abruptly this information. We present in this paper a model relying on neural fields, a paradigm for distributed, asyn- chronous and numerical computations and show that covert and overt attention can emerge from such a substratum. We identify and propose a possible interaction of four elemen- tary mechanisms for selecting the next locus of attention, memorizing the previously attended locations, anticipating the consequences of eye movements and integrating bottom- up and top-down information in order to perform a visual search task with saccadic eye movements.

Url:
DOI: 10.1007/s12559-010-9083-y


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<date type="start">1939-10-19</date>
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<country key="FR"></country>
</address>
<ref type="url">http://www.cnrs.fr/</ref>
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<orgName>Institut National de Recherche en Informatique et en Automatique</orgName>
<orgName type="acronym">Inria</orgName>
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<address>
<addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine>
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</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>
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</address>
</desc>
</org>
</tutelle>
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<org type="institution" xml:id="struct-300292" status="OLD">
<orgName>Université Nancy 2</orgName>
<date type="end">2011-12-31</date>
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<address>
<addrLine>91 avenue de la Libération, BP 454, 54001 Nancy cedex</addrLine>
<country key="FR"></country>
</address>
</desc>
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</tutelle>
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<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>
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</address>
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<orgName>INRIA Lorraine</orgName>
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<addrLine>615 rue du Jardin Botanique 54600 Villers-lès-Nancy</addrLine>
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</address>
<ref type="url">http://www.inria.fr/centre-de-recherche-inria/nancy-grand-est</ref>
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<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>
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<idno type="DOI">10.1007/s12559-010-9083-y</idno>
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<keywords scheme="mix" xml:lang="en">
<term>dynamic neural fields</term>
<term>emergence</term>
<term>eye movements</term>
<term>visual attention</term>
</keywords>
</textClass>
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<front>
<div type="abstract" xml:lang="en">Abstract The visual exploration of a scene involves the in- terplay of several competing processes (for example to se- lect the next saccade or to keep fixation) and the integration of bottom-up (e.g. contrast) and top-down information (the target of a visual search task). Identifying the neural mech- anisms involved in these processes and in the integration of these information remains a challenging question. Visual attention refers to all these processes, both when the eyes remain fixed (covert attention) and when they are moving (overt attention). Popular computational models of visual attention consider that the visual information remains fixed when attention is deployed while the primates are executing around three saccadic eye movements per second, changing abruptly this information. We present in this paper a model relying on neural fields, a paradigm for distributed, asyn- chronous and numerical computations and show that covert and overt attention can emerge from such a substratum. We identify and propose a possible interaction of four elemen- tary mechanisms for selecting the next locus of attention, memorizing the previously attended locations, anticipating the consequences of eye movements and integrating bottom- up and top-down information in order to perform a visual search task with saccadic eye movements.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>France</li>
</country>
<region>
<li>Grand Est</li>
<li>Lorraine (région)</li>
</region>
<settlement>
<li>Nancy</li>
</settlement>
<orgName>
<li>Institut national polytechnique de Lorraine</li>
<li>Université Nancy 2</li>
<li>Université de Lorraine</li>
</orgName>
</list>
<tree>
<country name="France">
<noRegion>
<name sortKey="Fix, Jeremy" sort="Fix, Jeremy" uniqKey="Fix J" first="Jérémy" last="Fix">Jérémy Fix</name>
</noRegion>
<name sortKey="Alexandre, Frederic" sort="Alexandre, Frederic" uniqKey="Alexandre F" first="Frédéric" last="Alexandre">Frédéric Alexandre</name>
<name sortKey="Rougier, Nicolas P" sort="Rougier, Nicolas P" uniqKey="Rougier N" first="Nicolas P." last="Rougier">Nicolas P. Rougier</name>
</country>
</tree>
</affiliations>
</record>

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