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Does Bold Emphasis Facilitate the Process of Visual-Word Recognition?

Published online by Cambridge University Press:  20 February 2014

María Macaya
Affiliation:
Universidad de Buenos Aires (Argentina)
Manuel Perea*
Affiliation:
Universitat de València (Spain)
*
*Correspondence concerning this article should be addressed to Manuel Perea. Departamento de Metodología. Av. Blasco Ibáñez, 21. 46010.Valencia (Spain). FAX: +34-963864697. Email: mperea@valencia.edu

Abstract

The study of the effects of typographical factors on lexical access has been rather neglected in the literature on visual-word recognition. Indeed, current computational models of visual-word recognition employ an unrefined letter feature level in their coding schemes. In a letter recognition experiment, Pelli, Burns, Farell, and Moore-Page (2006), letters in Bookman boldface produced more efficiency (i.e., a higher ratio of thresholds of an ideal observer versus a human observer) than the letters in Bookman regular under visual noise. Here we examined whether the effect of bold emphasis can be generalized to a common visual-word recognition task (lexical decision: “is the item a word?”) under standard viewing conditions. Each stimulus was presented either with or without bold emphasis (e.g., actor vs. actor). To help determine the locus of the effect of bold emphasis, word-frequency (low vs. high) was also manipulated. Results revealed that responses to words in boldface were faster than the responses to the words without emphasis –this advantage was restricted to low-frequency words. Thus, typographical features play a non-negligible role during visual-word recognition and, hence, the letter feature level of current models of visual-word recognition should be amended.

Type
Research Article
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2014 

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References

Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. A., Kessler, B., Loftis, B., …, Treiman, R. (2007). The English lexicon project. Behavior Research Methods, 39, 445459. http://dx.doi.org/10.3758/BF03193014 Google Scholar
Balota, D. A., Yap, M. J., & Cortese, M. J. (2006). Visual word recognition: The journey from features to meaning (A travel update). In Traxler, M. & Gernsbacher, M. A. (Eds.), Handbook of psycholinguistics (2 nd Ed., pp. 285375). New York, NY: Academic Press.CrossRefGoogle Scholar
Blais, C., Fiset, D., Jolicoeur, P., Arguin, M., Bub, D. N., & Gosselin, F. (2009). Reading between eye saccades. PLoS ONE 4(7): e6448. http://dx.doi.org/10.1371/journal.pone.0006448 Google Scholar
Coltheart, M., Rastle, K., Perry, C., Ziegler, J., & Langdon, R. (2001). DRC: A dual-route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204256. http://dx.doi.org/10.1037/0033-295X.108.1.204 Google Scholar
Davis, C. J., & Perea, M. (2005). BuscaPalabras: A program for deriving orthographic and phonological neighborhood statistics and other psycholinguistic indices in Spanish. Behavior Research Methods, 37, 665671. http://dx.doi.org/10.3758/BF03192738 Google Scholar
Davis, C. J. (2010). The spatial coding model of visual word identification. Psychological Review, 117, 713758. http://dx.doi.org/10.1037/a0019738 Google Scholar
Forster, K. I., & Forster, J. C. (2003). DMDX: A windows display program with millisecond accuracy. Behavior Research Methods, Instruments, & Computers, 35, 116124. http://dx.doi.org/10.3758/BF03195503 Google Scholar
Grainger, J., & Jacobs, A. M. (1996). Orthographic processing in visual word recognition: A multiple read-out model. Psychological Review, 103, 518565. http://dx.doi.org/10.1037/0033-295X.103.3.518 Google Scholar
Hannagan, T., Ktori, M., Chanceaux, M., & Grainger, J. (2012). Deciphering CAPTCHAs: What a turing test reveals about human cognition. Plos One, 7(3), e32121. http://dx.doi.org/10.1371/journal.pone.0032121 CrossRefGoogle ScholarPubMed
McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychological Review, 88, 375407. http://dx.doi.org/10.1037%2F0033-295X.88.5.375 Google Scholar
Pelli, D. G., Burns, C. W., Farell, B., & Moore-Page, D. C. (2006). Feature detection and letter identification. Vision Research, 46, 46464674. http://dx.doi.org/10.1016/j.visres.2006.04.023 Google Scholar
Perea, M. (2013). Why does the APA recommend the use of serif fonts? Psicothema, 25, 1317. http://dx.doi.org/10.7334/psicothema2012.141 Google Scholar
Perea, M., & Acha, J. (2009). Space information is important for reading. Vision Research, 49, 19942000. http://dx.doi.org/10.1016/j.visres.2009.05.009 Google Scholar
Perea, M., & Gómez, P. (2012). Increasing interletter spacing facilitates encoding of words. Psychonomic Bulletin and Review, 19, 332338. http://dx.doi.org/10.3758/s13423-011-0214-6 CrossRefGoogle ScholarPubMed
Perea, M., & Rosa, E. (2002). Does “whole word shape” play a role in visual word recognition? Perception & Psychophysics, 64, 785794. http://dx.doi.org/10.3758/BF03194745 Google Scholar
Perea, M., Comesaña, M., & Soares, A. P. (2012). Does the advantage of the upper part of words occur at the lexical level? Memory and Cognition, 8, 12571265. http://dx.doi.org/10.3758/s13421-012-0219-z Google Scholar
Perea, M., Rosa, E., & Gómez, C. (2005). The frequency effect for pseudowords in the lexical decision task. Perception and Psychophysics, 67, 301314. http://dx.doi.org/10.3758%2FBF03206493 Google Scholar
Pollatsek, A., & Well, A. D. (1995). On the use of counterbalanced designs in cognitive research: A suggestion for a better and more powerful analysis. Journal of Experimental Psychology. Learning, Memory, and Cognition, 21, 785794. http://dx.doi.org/10.1037/0278-7393.21.3.785 Google Scholar
Rayner, K. (2009). Eye movements and attention in reading, scene perception, and visual search. Quarterly Journal of Experimental Psychology, 62, 14571506. http://dx.doi.org/10.1080/1747021090281646 Google Scholar
Rumelhart, D. E., & Siple, P. (1974). The process of recognizing tachistoscopically presented words. Psychological Review, 81, 99118. http://dx.doi.org/10.1037/h0036117 Google Scholar
Sanocki, T., & Dyson, M. C. (2012). Letter processing and font information during reading: Beyond distinctiveness, where vision meets design. Attention, Perception, & Psychophysics, 74, 132145. http://dx.doi.org/10.3758/s13414-011-0220-9 Google Scholar
Slattery, T. J., & Rayner, K. (2010). Eye movements and text legibility. Applied Cognitive Psychology, 24, 11291148. http://dx.doi.org/10.1002/acp.1623 CrossRefGoogle Scholar
Sternberg, S. (1969). The discovery of processing stages: Extensions of donders’ method. In Koster, W. G. (Ed.), Attention and performance II (pp. 276315). Amsterdam, The Netherlands. North-Holland Publishing Company.Google Scholar
Tinker, M. A. (1963). Legibility of print. Iowa, IA: Iowa State University Press.Google Scholar
Van Orden, G. C., & Goldinger, S. D. (1994). Interdependence of form and function in cognitive systems explains perception of printed words. Journal of experimental psychology. Human perception and performance, 20, 1269–91. http://dx.doi.org/10.1037/0096-1523.20.6.1269 CrossRefGoogle ScholarPubMed