Breaking the boundaries: the power of ligatures in visual-word recognition.

lexical access lexical decision reading visual similarity word recognition

Journal

Frontiers in psychology
ISSN: 1664-1078
Titre abrégé: Front Psychol
Pays: Switzerland
ID NLM: 101550902

Informations de publication

Date de publication:
2023
Historique:
received: 14 02 2023
accepted: 25 04 2023
medline: 29 6 2023
pubmed: 29 6 2023
entrez: 29 6 2023
Statut: epublish

Résumé

Current neurobiological-inspired models of visual-word recognition propose that letter detectors in the word recognition system can tolerate some variations in the visual form of the letters. However, it is unclear whether this tolerance extends to novel ligatures, which combine two letters into a single glyph. To investigate this, the present study utilized a masked priming experiment with a lexical decision task to examine whether primes containing novel ligatures are effective in activating their corresponding base word, relative to omitted-letter primes, in the initial stages of word processing. For each target word (e.g., VIRTUAL), were created an identity prime (virtual), a prime containing a novel ligature of two of the letters (e.g., virtual; "ir" in a single glyph), and an omitted-letter prime where one letter was removed (e.g., vrtual [omitted-vowel] in Experiment 1; vitual [omitted-consonant] in Experiment 2). Results showed that the presence of a novel ligature in the prime resulted in faster lexical decision times compared to a prime with an omitted vowel (Experiment 1), but not with an omitted consonant (Experiment 2). Furthermore, the performance with the primes containing the novel ligature was not different from that of the identity primes. These results suggest that the word recognition system can quickly enable separate letter detectors for novel ligatures. These findings have important implications for our understanding of the front-end of visual-word recognition.

Identifiants

pubmed: 37384168
doi: 10.3389/fpsyg.2023.1166192
pmc: PMC10294432
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1166192

Informations de copyright

Copyright © 2023 Fernández-López, Perea and Marcet.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Behav Res Methods. 2010 Aug;42(3):627-33
pubmed: 20805584
Psychol Rev. 1996 Jul;103(3):518-65
pubmed: 8759046
Neuropsychologia. 2010 Apr;48(5):1343-55
pubmed: 20038435
J Exp Psychol Hum Percept Perform. 2010 Aug;36(4):906-23
pubmed: 20695708
PLoS One. 2012;7(3):e32121
pubmed: 22396750
Cogn Affect Behav Neurosci. 2019 Aug;19(4):966-984
pubmed: 30746614
Behav Res Methods. 2013 Dec;45(4):1246-58
pubmed: 23468181
J Exp Psychol Learn Mem Cogn. 2022 Dec;48(12):2004-2014
pubmed: 34424023
J Exp Psychol Learn Mem Cogn. 2018 May;44(5):699-706
pubmed: 29094993
Acta Psychol (Amst). 2018 Oct;190:142-149
pubmed: 30119047
J Cogn. 2018 Jan 12;1(1):9
pubmed: 31517183
Psychol Rev. 2010 Jul;117(3):713-58
pubmed: 20658851
Psychol Res. 2021 Sep;85(6):2279-2290
pubmed: 32870370
J Exp Psychol Hum Percept Perform. 2008 Feb;34(1):237-41
pubmed: 18248151
Psychol Rev. 1982 Jan;89(1):60-94
pubmed: 7058229
Psychon Bull Rev. 2017 Aug;24(4):1180-1185
pubmed: 27873186
Psychol Rev. 2012 Jul;119(3):517-45
pubmed: 22663560
Trends Cogn Sci. 2005 Jul;9(7):335-41
pubmed: 15951224
Behav Res Methods Instrum Comput. 2003 Feb;35(1):116-24
pubmed: 12723786
Neuropsychologia. 2021 Aug 20;159:107924
pubmed: 34175372
Q J Exp Psychol (Hove). 2023 May;76(5):1111-1119
pubmed: 35619235

Auteurs

María Fernández-López (M)

Department of Methodology of Behavioral Sciences and ERI-Lectura, Universitat de València, Valencia, Spain.

Manuel Perea (M)

Department of Methodology of Behavioral Sciences and ERI-Lectura, Universitat de València, Valencia, Spain.
Center of Research in Cognition, Universidad Antonio de Nebrija, Madrid, Spain.

Ana Marcet (A)

Grupo de Investigación en Enseñanza de Lenguas (GIEL), Department of Language and Literature Teaching, Universitat de València, Valencia, Spain.

Classifications MeSH