Testing computational models of letter perception with item-level event-related potentials
Identifieur interne : 002798 ( PascalFrancis/Checkpoint ); précédent : 002797; suivant : 002799Testing computational models of letter perception with item-level event-related potentials
Auteurs : Arnaud Rey [France] ; Stéphane Dufau [France] ; Stéphanie Massol [France] ; Jonathan Grainger [France]Source :
- Cognitive neuropsychology : (Print) [ 0264-3294 ] ; 2009.
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- Pascal (Inist)
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- topic : Homme.
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Abstract
In the present study, online measures of letter identification were used to test computational models of letter perception. Event-related potentials (ERPs) were recorded to letters and pseudoletters revealing a transition from feature analysis to letter identification in the 100-200-ms time window. Measures indexing this transition were then computed at the level of individual letters. Simulations with several versions of an interactive-activation model of letter perception were fitted with these item-level ERP measures. The results are in favour of a model of letter perception with feedforward excitatory connections from the feature to the letter levels, lateral inhibition at the letter level, and excitatory feedback from the letter to the feature levels.
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i1="01"><s1>Laboratoire de Psychologie Cognitive-CNRS, Université de Provence</s1><s2>Marseille</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region">Provence-Alpes-Côte d'Azur</region><region type="old region">Provence-Alpes-Côte d'Azur</region><settlement type="city">Marseille</settlement><settlement type="city">Marseille</settlement></placeName><orgName type="university">Université de Provence</orgName></affiliation></author><author><name sortKey="Dufau, Stephane" sort="Dufau, Stephane" uniqKey="Dufau S" first="Stéphane" last="Dufau">Stéphane Dufau</name><affiliation wicri:level="4"><inist:fA14 i1="01"><s1>Laboratoire de Psychologie Cognitive-CNRS, Université de Provence</s1><s2>Marseille</s2><s3>FRA</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>France</country><placeName><region type="region">Provence-Alpes-Côte d'Azur</region><region type="old 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perception. Event-related potentials (ERPs) were recorded to letters and pseudoletters revealing a transition from feature analysis to letter identification in the 100-200-ms time window. Measures indexing this transition were then computed at the level of individual letters. Simulations with several versions of an interactive-activation model of letter perception were fitted with these item-level ERP measures. 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