Dissociable mechanisms of subitizing and counting: neuropsychological evidence from simultanagnosic patients.

Do people have to count to determine visual numerosity, or is there a fast “subitizing” procedure dedicated to small sets of 1-3 items? Numerosity naming time and errors were measured in 5 simultanagnosic patients who suffered from severe difficulties in serial counting. Although these patients made...

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Publicado en:Journal of Experimental Psychology. Human Perception & Performance Vol. 20; pp. 958 - 976
Autores principales: Dehaene, Stanislas, Cohen, Laurent
Formato: Artículo
Publicado: American Psychological Association October 1994
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Acceso en línea:Ver este registro en EBSCOhost
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      dt: October 1994
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      pub: American Psychological Association
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        10.1037/0096-1523.20.5.958
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        atl: Dissociable mechanisms of subitizing and counting: neuropsychological evidence from simultanagnosic patients.
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          Dehaene, Stanislas
          Cohen, Laurent
      su:
        Counting
        Number concept
        Tracking & trailing
      sug:
        subj:
          Counting
          Number concept
          Tracking & trailing
      ab: Do people have to count to determine visual numerosity, or is there a fast “subitizing” procedure dedicated to small sets of 1-3 items? Numerosity naming time and errors were measured in 5 simultanagnosic patients who suffered from severe difficulties in serial counting. Although these patients made close to 100% errors in quantifying sets comprising more than 3 items, they were excellent at quantifying sets of 1, 2, and sometimes 3 items. Their performances in visual search tasks suggested that they suffered from a deficit of serial visual exploration, due to a fundamental inability to use spatial tags to keep track of previously explored locations. The present data suggest that the patients' preserved subitizing abilities were based not on serial processing but rather on a parallel algorithm dedicated to small numerosities. Several ways in which this parallel subitizing algorithm might function are discussed. Reprinted by permission of the publisher.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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