One more trip to Barcetona: on the special status of visual similarity effects in city names.


Journal

Psychological research
ISSN: 1430-2772
Titre abrégé: Psychol Res
Pays: Germany
ID NLM: 0435062

Informations de publication

Date de publication:
23 Jun 2023
Historique:
received: 19 01 2023
accepted: 21 05 2023
medline: 24 6 2023
pubmed: 24 6 2023
entrez: 23 6 2023
Statut: aheadofprint

Résumé

Previous research has shown that, unlike misspelled common words, misspelled brand names are sensitive to visual letter similarity effects (e.g., amazom is often recognized as a legitimate brand name, but not amazot). This pattern poses problems for those models that assume that word identification is exclusively based on abstract codes. Here, we investigated the role of visual letter similarity using another type of word often presented in a more homogenous format than common words: city names. We found a visual letter similarity effect for misspelled city names (e.g., Barcetona was often recognized as a word, but not Barcesona) for relatively short durations of the stimuli (200 ms; Experiment 2), but not when the stimuli were presented until response (Experiment 1). Notably, misspelled common words did not show a visual letter similarity effect for brief 200- and 150-ms durations (e.g., votume was not as often recognized as a word than vosume; Experiments 3-4). These findings provide further evidence that the consistency in the format of presentations may shape the representation of words in the mental lexicon, which may be more salient in scenarios where processing resources are limited (e.g., brief exposure presentations).

Identifiants

pubmed: 37353613
doi: 10.1007/s00426-023-01839-3
pii: 10.1007/s00426-023-01839-3
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Ministerio de Ciencia e Innovación
ID : PID2020-116740 GB-I00 (funded by the MCIN/AEI/10.13039/501100011033)
Organisme : Ministerio de Ciencia e Innovación
ID : PID2020-116740 GB-I00 (funded by the MCIN/AEI/10.13039/501100011033)
Organisme : Ministerio de Ciencia e Innovación
ID : PID2020-116740 GB-I00 (funded by the MCIN/AEI/10.13039/501100011033)
Organisme : Ministerio de Ciencia e Innovación
ID : PID2020-116740 GB-I00 (funded by the MCIN/AEI/10.13039/501100011033)
Organisme : Ministerio de Ciencia e Innovación
ID : PID2020-116740 GB-I00 (funded by the MCIN/AEI/10.13039/501100011033)
Organisme : Ministerio de Ciencia e Innovación
ID : PID2020-116740 GB-I00 (funded by the MCIN/AEI/10.13039/501100011033)
Organisme : Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
ID : CIAICO/2021/172
Organisme : Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
ID : CIAICO/2021/172
Organisme : Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
ID : CIAICO/2021/172
Organisme : Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
ID : CIAICO/2021/172
Organisme : Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
ID : CIAICO/2021/172
Organisme : Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
ID : CIAICO/2021/172
Organisme : National Science Foundation
ID : SMA- 2127135

Informations de copyright

© 2023. The Author(s).

Références

Agrawal, A., Hari, K., & Arun, S. (2020). A compositional neural code in high-level visual cortex can explain jumbled word reading. eLife. https://doi.org/10.7554/eLife.54846
doi: 10.7554/eLife.54846 pubmed: 33263281 pmcid: 7752136
Baciero, A., Gómez, P., Duñabeitia, J. A., & Perea, M. (2022). Letter-similarity effects in braille word recognition. Quarterly Journal of Experimental Psychology. https://doi.org/10.1177/17470218221142145
doi: 10.1177/17470218221142145
Bowers, J. S., Malhotra, G., Dujmović, M., Montero, M. L., Tsvetkov, C., Biscione, V., & Blything, R. (2022). Deep problems with neural network models of human vision. Brain and Behavioral Sciences. https://doi.org/10.31234/osf.io/5zf4s
doi: 10.31234/osf.io/5zf4s
Bridges, D., Pitiot, A., MacAskill, M. R., & Peirce, J. W. (2020). The timing mega-study: comparing a range of experiment generators, both lab-based and online. PeerJ, 8, e9414. https://doi.org/10.7717/peerj.9414
doi: 10.7717/peerj.9414 pubmed: 33005482 pmcid: 7512138
Brysbaert, M., & Stevens, M. (2018). Power analysis and effect size in mixed effects models: A tutorial. Journal of Cognition. https://doi.org/10.5334/joc.10
doi: 10.5334/joc.10 pubmed: 31517183 pmcid: 6646942
Bürkner, P.-C. (2017). brms: An R package for bayesian multilevel models using stan. Journal of Statistical Software, 80(1), 1–28. https://doi.org/10.18637/jss.v080.i01
doi: 10.18637/jss.v080.i01
Carreiras, M., Perea, M., Gil-López, C., Abu Mallouh, R., & Salillas, E. (2013). Neural correlates of visual vs. abstract letter processing in Roman and Arabic scripts. Journal of Cognitive Neuroscience, 25, 1975–1985. https://doi.org/10.1162/jocn_a_00438
doi: 10.1162/jocn_a_00438 pubmed: 23806176
Davis, C. J. (1999). The self-organising lexical acquisition and recognition (SOLAR) model of visual word recognition (Doctoral dissertation). University of New South Wales.
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, 665–671. https://doi.org/10.3758/bf03192738
doi: 10.3758/bf03192738 pubmed: 16629300
Dehaene, S., Cohen, L., Sigman, M., & Vinckier, F. (2005). The neural code for written words: A proposal. Trends in Cognitive Sciences, 9, 335–341. https://doi.org/10.1016/j.tics.2005.05.004
doi: 10.1016/j.tics.2005.05.004 pubmed: 15951224
Duchon, A., Perea, M., Sebastián-Gallés, N., & Carreiras, M. (2013). EsPal: One-stop shopping for Spanish word properties. Behavior Research Methods, 45, 1246–1258. https://doi.org/10.3758/s13428-013-0326-1
doi: 10.3758/s13428-013-0326-1 pubmed: 23468181
Emmorey, K., Holcomb, P. J., & Midgley, K. J. (2021). Masked ERP repetition priming in deaf and hearing readers. Brain and Language, 214, 104903. https://doi.org/10.1016/j.bandl.2020.104903
doi: 10.1016/j.bandl.2020.104903 pubmed: 33486233 pmcid: 8299519
Foroudi, P., Melewar, T. C., & Gupta, S. (2017). Corporate Logo: History, Definition, and Components. International Studies of Management & Organization, 47, 176–196. https://doi.org/10.1080/00208825.2017.1256166
doi: 10.1080/00208825.2017.1256166
Goldinger, S. D. (1998). Echoes of echoes? An episodic theory of lexical access. Psychological Review, 105, 251–279. https://doi.org/10.1037/0033-295X.105.2.251
doi: 10.1037/0033-295X.105.2.251 pubmed: 9577239
Gontijo, P. F. G., & Zhang, S. (2007). The mental representation of brand names: Are brand names a class by themselves? In T. M. Lowrey (Ed.), Psycholinguistic phenomena in marketing communications (pp. 23–37). Erlbaum.
Grainger, J. (2018). Orthographic processing: A “mid-level” vision of reading. Quarterly Journal of Experimental Psychology, 71, 335–359. https://doi.org/10.1080/17470218.2017.1314515
doi: 10.1080/17470218.2017.1314515
Grainger, J., & Dufau, S. (2012). The front-end of visual word recognition. In J. S. Adelman (Ed.), Visual Word Recognition Vol. 1: Models and Methods, Orthography and Phonology (pp. 159–184). Psychology Press.
Grossberg, S., & Stone, G. O. (1986). Neural dynamics of word recognition and recall: Attentional priming, learning, and resonance. Psychological Review, 93, 46–74. https://doi.org/10.1037/0033-295x.93.1.46
doi: 10.1037/0033-295x.93.1.46 pubmed: 3961051
Grainger, J., Rey, A., & Dufau, S. (2008). Letter perception: From pixels to pandemonium. Trends in Cognitive Sciences, 12, 381–387. https://doi.org/10.1016/j.tics.2008.06.006
doi: 10.1016/j.tics.2008.06.006 pubmed: 18760658
Gutierrez-Sigut, E., Marcet, A., & Perea, M. (2019). Tracking the time course of letter visual-similarity effects during word recognition: A masked priming ERP investigation. Cognitive, Affective, and Behavioral Neuroscience, 19, 966–984. https://doi.org/10.3758/s13415-019-00696-1
doi: 10.3758/s13415-019-00696-1
Gutierrez-Sigut, E., Vergara-Martínez, M., & Perea, M. (2022). The impact of visual cues during visual word recognition in deaf readers: An ERP study. Cognition, 218, 104938. https://doi.org/10.1016/j.cognition.2021.104938
doi: 10.1016/j.cognition.2021.104938 pubmed: 34678681
Hannagan, T., Agrawal, A., Cohen, L., & Dehaene, S. (2021). Emergence of a compositional neural code for written words: Recycling of a convolutional neural network for reading. Proceedings of the National Academy of Sciences, 118, e2104779118. https://doi.org/10.1073/pnas.2104779118
doi: 10.1073/pnas.2104779118
Henderson, L. (1987). Word recognition: A tutorial review. In M. Coltheart (Ed.), Attention and performance XII: The psychology of reading (pp. 171–200). Erlbaum.
Lally, C., & Rastle, K. (2022). Orthographic and feature-level contributions to letter identification. Quarterly Journal of Experimental Psychology. https://doi.org/10.1177/17470218221106155
doi: 10.1177/17470218221106155
Lavidor, M. (2011). Whole-word shape effect in dyslexia. Journal of Research in Reading, 34, 443–454. https://doi.org/10.1111/j.1467-9817.2010.01444.x
doi: 10.1111/j.1467-9817.2010.01444.x
Marcet, A., & Perea, M. (2017). Is nevtral NEUTRAL? Visual similarity effects in the early phases of written-word recognition. Psychonomic Bulletin and Review, 24, 1180–1185. https://doi.org/10.3758/s13423-016-1180-9
doi: 10.3758/s13423-016-1180-9 pubmed: 27873186
Marcet, A., & Perea, M. (2018). Can I order a burger at rnacdonalds.com? Visual similarity effects of multi-letter combinations at the early stages of word recognition. Journal of Experimental Psychology: Learning, Memory, & Cognition, 44, 699–706. https://doi.org/10.1037/xlm0000477
doi: 10.1037/xlm0000477
Paap, K. R., Johansen, L. S., Chun, E., & Vonnahme, P. (2000). Neighborhood frequency does affect performance in the Reicher task: Encoding or decision? Journal of Experimental Psychology: Human Perception & Performance, 26, 1691–1720. https://doi.org/10.1037/0096-1523.26.6.1691
doi: 10.1037/0096-1523.26.6.1691
Pathak, A., Velasco, C., & Calvert, G. A. (2019). Identifying counterfeit brand logos: On the importance of the first and last letters of a logotype. European Journal of Marketing, 53, 2109–2125. https://doi.org/10.1108/EJM-09-2017-0586
doi: 10.1108/EJM-09-2017-0586
Peirce, J. W., Hirst, R. J., & MacAskill, M. R. (2022). Building experiments in PsychoPy. Sage.
Perea, M., & Panadero, V. (2014). Does viotin activate violin more than viocin? On the use of visual cues during visual-word recognition. Experimental Psychology, 61, 23–29. https://doi.org/10.1027/1618-3169/a000223
doi: 10.1027/1618-3169/a000223 pubmed: 23948388
Perea, M., Baciero, A., Labusch, M., Fernández-López, M., & Marcet, A. (2022). Are brand names special words? Letter visual-similarity affects the identification of brand names, but not common words. British Journal of Psychology, 113, 835–852. https://doi.org/10.1111/bjop.12557
doi: 10.1111/bjop.12557 pubmed: 35107840 pmcid: 9545185
Perea, M., Baciero, A., Rocabado, F., & Marcet, A. (2021). Does the cowl make the monk? Detecting counterfeits in brand names versus logos. Psychonomic Bulletin and Review, 28, 969–977. https://doi.org/10.3758/s13423-020-01863-z
doi: 10.3758/s13423-020-01863-z pubmed: 33565044
Perea, M., Jiménez, M., Talero, F., & López-Cañada, S. (2015). Letter-case information and the identification of brand names. British Journal of Psychology, 106, 162–173. https://doi.org/10.1111/bjop.12071
doi: 10.1111/bjop.12071 pubmed: 24766365
Perea, M., Marcet, A., & Vergara-Martínez, M. (2018). Are you taking the fastest route to the RESTAURANT? The role of the usual letter-case configuration of words in lexical decision. Experimental Psychology, 65, 98–104. https://doi.org/10.1027/1618-3169/a000391
doi: 10.1027/1618-3169/a000391 pubmed: 29631520
Perea, M., Rosa, E., & Gómez, C. (2005). The frequency effect for pseudowords in the lexical decision task. Perception and Psychophysics, 67, 301–314. https://doi.org/10.3758/bf03206493
doi: 10.3758/bf03206493 pubmed: 15971693
Peressotti, F., Cubelli, R., & Job, R. (2003). On recognizing proper names: The orthographic cue hypothesis. Cognitive Psychology, 47, 87–116. https://doi.org/10.1016/s0010-0285(03)00004-5
doi: 10.1016/s0010-0285(03)00004-5 pubmed: 12852936
R Core Team. (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/
Simpson, I. C., Mousikou, P., Montoya, J. M., & Defior, S. (2013). A letter visual-similarity matrix for Latin-based alphabets. Behavior Research Methods, 45, 431–439. https://doi.org/10.3758/s13428-012-0271-4
doi: 10.3758/s13428-012-0271-4 pubmed: 23055176
Stoet, G. (2010). PsyToolkit—A software package for programming psychological experiments using Linux. Behavior Research Methods, 42, 1096–1104. https://doi.org/10.3758/BRM.42.4.1096
doi: 10.3758/BRM.42.4.1096 pubmed: 21139177
Stoet, G. (2017). PsyToolkit: A novel web-based method for running online questionnaires and reaction-time experiments. Teaching of Psychology, 44, 24–31. https://doi.org/10.1177/0098628316677
doi: 10.1177/0098628316677
Sulpizio, S., & Job, R. (2018). Early and multiple-loci divergency of proper and common names: An event-related potential investigation. Neuropsychologia, 119, 107–117. https://doi.org/10.1016/j.neuropsychologia.2018.07.034
doi: 10.1016/j.neuropsychologia.2018.07.034 pubmed: 30075217
Tenpenny, P. L. (1995). Abstractionist versus episodic theories of repetition priming and word identification. Psychonomic Bulletin & Review, 2, 339–363. https://doi.org/10.3758/BF03210972
doi: 10.3758/BF03210972
UK Association for Accessible Formats. (2017). Standard dimensions for the UK Braille Cell. https://www.ukaaf.org/wp-content/uploads/2020/03/Braille-Standard-Dimensions.pdf . Retrieved on January 15, 2023
Wimmer, H., Ludersdorfer, P., Richlan, F., & Kronbichler, M. (2016). Visual experience shapes orthographic representations in the visual word form area. Psychological Science, 27, 1240–1248. https://doi.org/10.1177/0956797616657319
doi: 10.1177/0956797616657319 pubmed: 27435995
Yin, D., Biscionea, V., & Bowers, J. S. (2022). Convolutional neural networks trained to identify words provide a good account of visual form priming effects. https://doi.org/10.21203/rs.3.rs-2289281/v1 . Retrieved on January 15, 2023
Ziegler, J. C., Hannagan, T., Dufau, S., Montant, M., Fagot, J., & Grainger, J. (2013). Transposed-letter effects reveal orthographic processing in baboons. Psychological Science, 24, 1609–1611. https://doi.org/10.1177/0956797612474322
doi: 10.1177/0956797612474322 pubmed: 23757307

Auteurs

Manuel Perea (M)

Universitat de València, Av. Blasco Ibáñez, 21, 46010, Valencia, Spain. mperea@uv.es.
Centro de Investigación Nebrija en Cognición, Universidad Nebrija, Madrid, Spain. mperea@uv.es.

Melanie Labusch (M)

Universitat de València, Av. Blasco Ibáñez, 21, 46010, Valencia, Spain.
Centro de Investigación Nebrija en Cognición, Universidad Nebrija, Madrid, Spain.

María Fernández-López (M)

Universitat de València, Av. Blasco Ibáñez, 21, 46010, Valencia, Spain.

Ana Marcet (A)

Universitat de València, Av. Blasco Ibáñez, 21, 46010, Valencia, Spain.

Eva Gutierrez-Sigut (E)

University of Essex, Essex, UK.

Pablo Gómez (P)

California State University, San Bernardino, Palm Desert Campus, San Bernardino, USA.

Classifications MeSH