The optimal use of non-optimal letter information in foveal and parafoveal word recognition.
Crowding
Letter recognition
Reading
Word recognition
Word recognition model
Journal
Vision research
ISSN: 1878-5646
Titre abrégé: Vision Res
Pays: England
ID NLM: 0417402
Informations de publication
Date de publication:
02 2019
02 2019
Historique:
received:
11
06
2018
revised:
14
12
2018
accepted:
18
12
2018
pubmed:
11
1
2019
medline:
22
3
2019
entrez:
11
1
2019
Statut:
ppublish
Résumé
Letters and words across the visual field can be difficult to identify due to limiting visual factors such as acuity, crowding and position uncertainty. Here, we show that when human readers identify words presented at foveal and para-foveal locations, they act like theoretical observers making optimal use of letter identity and letter position information independently extracted from each letter after an unavoidable and non-optimal letter recognition guess. The novelty of our approach is that we carefully considered foveal and parafoveal letter identity and position uncertainties by measuring crowded letter recognition performance in five subjects without any word context influence. Based on these behavioral measures, lexical access was simulated for each subject by an observer making optimal use of each subject's uncertainties. This free-parameter model was able to predict individual behavioral recognition rates of words presented at different positions across the visual field. Importantly, the model was also able to predict individual mislocation and identity letter errors made during behavioral word recognition. These results reinforce the view that human readers recognize foveal and parafoveal words by parts (the word letters) in a first stage, independently of word context. They also suggest a second step where letter identity and position uncertainties are generated based on letter first guesses and positions. During the third lexical access stage, identity and position uncertainties from each letter look remarkably combined together through an optimal word recognition decision process.
Identifiants
pubmed: 30629974
pii: S0042-6989(19)30002-1
doi: 10.1016/j.visres.2018.12.006
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
44-61Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.