Literature DB >> 22524868

How strongly do word reading times and lexical decision times correlate? Combining data from eye movement corpora and megastudies.

Victor Kuperman1, Denis Drieghe, Emmanuel Keuleers, Marc Brysbaert.   

Abstract

We assess the amount of shared variance between three measures of visual word recognition latencies: eye movement latencies, lexical decision times, and naming times. After partialling out the effects of word frequency and word length, two well-documented predictors of word recognition latencies, we see that 7-44% of the variance is uniquely shared between lexical decision times and naming times, depending on the frequency range of the words used. A similar analysis of eye movement latencies shows that the percentage of variance they uniquely share either with lexical decision times or with naming times is much lower. It is 5-17% for gaze durations and lexical decision times in studies with target words presented in neutral sentences, but drops to 0.2% for corpus studies in which eye movements to all words are analysed. Correlations between gaze durations and naming latencies are lower still. These findings suggest that processing times in isolated word processing and continuous text reading are affected by specific task demands and presentation format, and that lexical decision times and naming times are not very informative in predicting eye movement latencies in text reading once the effect of word frequency and word length are taken into account. The difference between controlled experiments and natural reading suggests that reading strategies and stimulus materials may determine the degree to which the immediacy-of-processing assumption and the eye-mind assumption apply. Fixation times are more likely to exclusively reflect the lexical processing of the currently fixated word in controlled studies with unpredictable target words rather than in natural reading of sentences or texts.

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Year:  2012        PMID: 22524868     DOI: 10.1080/17470218.2012.658820

Source DB:  PubMed          Journal:  Q J Exp Psychol (Hove)        ISSN: 1747-0218            Impact factor:   2.143


  13 in total

1.  Single-Word Recognition Need Not Depend on Single-Word Features: Narrative Coherence Counteracts Effects of Single-Word Features that Lexical Decision Emphasizes.

Authors:  Dan W Teng; Sebastian Wallot; Damian G Kelty-Stephen
Journal:  J Psycholinguist Res       Date:  2016-12

2.  An Investigation into the Processing of Lexicalized English Blend Words: Evidence from Lexical Decisions and Eye Movements During Reading.

Authors:  Barbara J Juhasz; Rebecca L Johnson; Jennifer Brewer
Journal:  J Psycholinguist Res       Date:  2017-04

3.  Estimating the average need of semantic knowledge from distributional semantic models.

Authors:  Geoff Hollis
Journal:  Mem Cognit       Date:  2017-11

4.  Contributions of reader- and text-level characteristics to eye-movement patterns during passage reading.

Authors:  Victor Kuperman; Kazunaga Matsuki; Julie A Van Dyke
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2018-07-19       Impact factor: 3.051

5.  Task effects reveal cognitive flexibility responding to frequency and predictability: evidence from eye movements in reading and proofreading.

Authors:  Elizabeth R Schotter; Klinton Bicknell; Ian Howard; Roger Levy; Keith Rayner
Journal:  Cognition       Date:  2014-01-14

6.  Reassessing word frequency as a determinant of word recognition for skilled and unskilled readers.

Authors:  Victor Kuperman; Julie A Van Dyke
Journal:  J Exp Psychol Hum Percept Perform       Date:  2013-01-21       Impact factor: 3.332

7.  How Noisy is Lexical Decision?

Authors:  Kevin Diependaele; Marc Brysbaert; Peter Neri
Journal:  Front Psychol       Date:  2012-09-24

8.  Hands Down: Cognate Effects Persist During Written Word Production.

Authors:  Evy Woumans; Robin Clauws; Wouter Duyck
Journal:  Front Psychol       Date:  2021-07-05

9.  Eye Movement Patterns in Natural Reading: A Comparison of Monolingual and Bilingual Reading of a Novel.

Authors:  Uschi Cop; Denis Drieghe; Wouter Duyck
Journal:  PLoS One       Date:  2015-08-19       Impact factor: 3.240

Review 10.  Models of visual word recognition.

Authors:  Dennis Norris
Journal:  Trends Cogn Sci       Date:  2013-09-04       Impact factor: 20.229

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