{"title":"New Insights Into Visual Word Recognition: Analyzing Error Distribution in Typical Readers.","authors":"Fanny Grisetto, Clémence Roger, Gwendoline Mahé","doi":"10.5334/joc.441","DOIUrl":null,"url":null,"abstract":"<p><p>Previous studies have examined error dynamics to investigate the origins of incorrect lexical access. The comparison of correct and incorrect reaction times (RTs) and the use of Conditional Accuracy Functions (CAFs) in lexical decision tasks have led to inconclusive findings. The present study aimed to clarify these inconsistencies by integrating both methodological approaches across a larger dataset. Our results revealed a pattern of fast errors for pseudowords in both measures, with faster error trials compared to correct trials and a marked decrease in accuracy for the fastest trials. This pattern is discussed within diffusion models of visual word recognition and cognitive control which suggest that pseudoword errors are associated with uninhibited automatic lexical activation. Word errors appeared relatively insensitive to RTs, as no significant difference was found between correct and error RTs, and the CAF displayed a more uniform pattern, but yet not homogeneous. Indeed, a pattern of slow errors was observed for both words and pseudowords in the CAFs, with less accuracy in the slowest RTs. An exploratory analysis suggested that this pattern of slow errors in the word condition might be characteristic of poor reading skills. These aspects are discussed in regard to visual word recognition models that postulate several factors to explain the occurrence of slow errors. Taken together, this research provides a framework that could be used for identifying cognitive markers of reading difficulties. Future research could explore how factors like word frequency or reading skills influence error dynamics, potentially informing interventions targeting lexical retrieval deficits.</p>","PeriodicalId":32728,"journal":{"name":"Journal of Cognition","volume":"8 1","pages":"29"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11967458/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5334/joc.441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Psychology","Score":null,"Total":0}
引用次数: 0
Abstract
Previous studies have examined error dynamics to investigate the origins of incorrect lexical access. The comparison of correct and incorrect reaction times (RTs) and the use of Conditional Accuracy Functions (CAFs) in lexical decision tasks have led to inconclusive findings. The present study aimed to clarify these inconsistencies by integrating both methodological approaches across a larger dataset. Our results revealed a pattern of fast errors for pseudowords in both measures, with faster error trials compared to correct trials and a marked decrease in accuracy for the fastest trials. This pattern is discussed within diffusion models of visual word recognition and cognitive control which suggest that pseudoword errors are associated with uninhibited automatic lexical activation. Word errors appeared relatively insensitive to RTs, as no significant difference was found between correct and error RTs, and the CAF displayed a more uniform pattern, but yet not homogeneous. Indeed, a pattern of slow errors was observed for both words and pseudowords in the CAFs, with less accuracy in the slowest RTs. An exploratory analysis suggested that this pattern of slow errors in the word condition might be characteristic of poor reading skills. These aspects are discussed in regard to visual word recognition models that postulate several factors to explain the occurrence of slow errors. Taken together, this research provides a framework that could be used for identifying cognitive markers of reading difficulties. Future research could explore how factors like word frequency or reading skills influence error dynamics, potentially informing interventions targeting lexical retrieval deficits.