Self-training of dynamic touch: Striking improves judgment by wielding
Identifieur interne : 004934 ( Main/Merge ); précédent : 004933; suivant : 004935Self-training of dynamic touch: Striking improves judgment by wielding
Auteurs : Damian G. Stephen [États-Unis] ; Ryan Arzamarshi [États-Unis]Source :
- Attention, perception & psychophysics [ 1943-3921 ] ; 2009.
Descripteurs français
- Pascal (Inist)
- Wicri :
English descriptors
- KwdEn :
Abstract
In traditional theories of perceptual learning, sensory modalities support one another. A good example comes from research on dynamic touch, the wielding of an unseen object to perceive its properties. Wielding provides the haptic system with mechanical information related to the length of the object. Visual feedback can improve the accuracy of subsequent length judgments; visual perception supports haptic perception. Such cross-modal support is not the only route to perceptual learning. We present a dynamic touch task in which we replaced visual feedback with the instruction to strike the unseen object against an unseen surface following length judgment. This additional mechanical information improved subsequent length judgments. We propose a self-organizing perspective in which a single modality trains itself.
Links toward previous steps (curation, corpus...)
- to stream PascalFrancis, to step Corpus: 000679
- to stream PascalFrancis, to step Corpus: 000719
- to stream PascalFrancis, to step Curation: 000D26
- to stream PascalFrancis, to step Checkpoint: 000541
Links to Exploration step
Pascal:10-0072601Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Self-training of dynamic touch: Striking improves judgment by wielding</title>
<author><name sortKey="Stephen, Damian G" sort="Stephen, Damian G" uniqKey="Stephen D" first="Damian G." last="Stephen">Damian G. Stephen</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>University of Connecticut</s1>
<s2>Storrs, Connecticut</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Connecticut</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Arzamarshi, Ryan" sort="Arzamarshi, Ryan" uniqKey="Arzamarshi R" first="Ryan" last="Arzamarshi">Ryan Arzamarshi</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>University of Connecticut</s1>
<s2>Storrs, Connecticut</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Connecticut</region>
</placeName>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">10-0072601</idno>
<date when="2009">2009</date>
<idno type="stanalyst">PASCAL 10-0072601 INIST</idno>
<idno type="RBID">Pascal:10-0072601</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000679</idno>
<idno type="stanalyst">FRANCIS 10-0072601 INIST</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000719</idno>
<idno type="wicri:Area/PascalFrancis/Curation">000D26</idno>
<idno type="wicri:Area/PascalFrancis/Checkpoint">000541</idno>
<idno type="wicri:doubleKey">1943-3921:2009:Stephen D:self:training:of</idno>
<idno type="wicri:Area/Main/Merge">004934</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Self-training of dynamic touch: Striking improves judgment by wielding</title>
<author><name sortKey="Stephen, Damian G" sort="Stephen, Damian G" uniqKey="Stephen D" first="Damian G." last="Stephen">Damian G. Stephen</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>University of Connecticut</s1>
<s2>Storrs, Connecticut</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Connecticut</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Arzamarshi, Ryan" sort="Arzamarshi, Ryan" uniqKey="Arzamarshi R" first="Ryan" last="Arzamarshi">Ryan Arzamarshi</name>
<affiliation wicri:level="2"><inist:fA14 i1="01"><s1>University of Connecticut</s1>
<s2>Storrs, Connecticut</s2>
<s3>USA</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
</inist:fA14>
<country>États-Unis</country>
<placeName><region type="state">Connecticut</region>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">Attention, perception & psychophysics</title>
<title level="j" type="abbreviated">Atten. percept. psychophys. </title>
<idno type="ISSN">1943-3921</idno>
<imprint><date when="2009">2009</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">Attention, perception & psychophysics</title>
<title level="j" type="abbreviated">Atten. percept. psychophys. </title>
<idno type="ISSN">1943-3921</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Experimental study</term>
<term>Human</term>
<term>Judgment</term>
<term>Mechanical stimulus</term>
<term>Perceptive learning</term>
<term>Tactile sensitivity</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Etude expérimentale</term>
<term>Sensibilité tactile</term>
<term>Jugement</term>
<term>Apprentissage perceptif</term>
<term>Stimulus mécanique</term>
<term>Homme</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Jugement</term>
<term>Homme</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">In traditional theories of perceptual learning, sensory modalities support one another. A good example comes from research on dynamic touch, the wielding of an unseen object to perceive its properties. Wielding provides the haptic system with mechanical information related to the length of the object. Visual feedback can improve the accuracy of subsequent length judgments; visual perception supports haptic perception. Such cross-modal support is not the only route to perceptual learning. We present a dynamic touch task in which we replaced visual feedback with the instruction to strike the unseen object against an unseen surface following length judgment. This additional mechanical information improved subsequent length judgments. We propose a self-organizing perspective in which a single modality trains itself.</div>
</front>
</TEI>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Connecticut</li>
</region>
</list>
<tree><country name="États-Unis"><region name="Connecticut"><name sortKey="Stephen, Damian G" sort="Stephen, Damian G" uniqKey="Stephen D" first="Damian G." last="Stephen">Damian G. Stephen</name>
</region>
<name sortKey="Arzamarshi, Ryan" sort="Arzamarshi, Ryan" uniqKey="Arzamarshi R" first="Ryan" last="Arzamarshi">Ryan Arzamarshi</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/HapticV1/Data/Main/Merge
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 004934 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Merge/biblio.hfd -nk 004934 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= HapticV1 |flux= Main |étape= Merge |type= RBID |clé= Pascal:10-0072601 |texte= Self-training of dynamic touch: Striking improves judgment by wielding }}
![]() | This area was generated with Dilib version V0.6.23. | ![]() |