The spatial coding model of visual word identification
Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes. Current models of this lexical matching process posit context-specific letter codes in which letter representations are tied to either specific se...
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| Vydáno v: | Psychological review Ročník 117; číslo 3; s. 713 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
01.07.2010
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| Témata: | |
| ISSN: | 1939-1471, 1939-1471 |
| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Abstract | Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes. Current models of this lexical matching process posit context-specific letter codes in which letter representations are tied to either specific serial positions or specific local contexts (e.g., letter clusters). The spatial coding model described here adopts a different approach to letter position coding and lexical matching based on context-independent letter representations. In this model, letter position is coded dynamically, with a scheme called spatial coding. Lexical matching is achieved via a method called superposition matching, in which input codes and learned codes are matched on the basis of the relative positions of their common letters. Simulations of the model illustrate its ability to explain a broad range of results from the masked form priming literature, as well as to capture benchmark findings from the unprimed lexical decision task. |
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| AbstractList | Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes. Current models of this lexical matching process posit context-specific letter codes in which letter representations are tied to either specific serial positions or specific local contexts (e.g., letter clusters). The spatial coding model described here adopts a different approach to letter position coding and lexical matching based on context-independent letter representations. In this model, letter position is coded dynamically, with a scheme called spatial coding. Lexical matching is achieved via a method called superposition matching, in which input codes and learned codes are matched on the basis of the relative positions of their common letters. Simulations of the model illustrate its ability to explain a broad range of results from the masked form priming literature, as well as to capture benchmark findings from the unprimed lexical decision task. Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes. Current models of this lexical matching process posit context-specific letter codes in which letter representations are tied to either specific serial positions or specific local contexts (e.g., letter clusters). The spatial coding model described here adopts a different approach to letter position coding and lexical matching based on context-independent letter representations. In this model, letter position is coded dynamically, with a scheme called spatial coding. Lexical matching is achieved via a method called superposition matching, in which input codes and learned codes are matched on the basis of the relative positions of their common letters. Simulations of the model illustrate its ability to explain a broad range of results from the masked form priming literature, as well as to capture benchmark findings from the unprimed lexical decision task.Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes. Current models of this lexical matching process posit context-specific letter codes in which letter representations are tied to either specific serial positions or specific local contexts (e.g., letter clusters). The spatial coding model described here adopts a different approach to letter position coding and lexical matching based on context-independent letter representations. In this model, letter position is coded dynamically, with a scheme called spatial coding. Lexical matching is achieved via a method called superposition matching, in which input codes and learned codes are matched on the basis of the relative positions of their common letters. Simulations of the model illustrate its ability to explain a broad range of results from the masked form priming literature, as well as to capture benchmark findings from the unprimed lexical decision task. |
| Author | Davis, Colin J |
| Author_xml | – sequence: 1 givenname: Colin J surname: Davis fullname: Davis, Colin J email: c.davis@rhul.ac.uk organization: Department of Psychology, Royal Holloway, University of London, Egham Hill, Egham, Surrey TW20 0EX, England. c.davis@rhul.ac.uk |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/20658851$$D View this record in MEDLINE/PubMed |
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| Snippet | Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes.... |
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| StartPage | 713 |
| SubjectTerms | Comprehension Humans Linguistics Models, Psychological Pattern Recognition, Visual Reading Recognition (Psychology) |
| Title | The spatial coding model of visual word identification |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/20658851 https://www.proquest.com/docview/734033430 |
| Volume | 117 |
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