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The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition
To characterize the functional role of the left-ventral occipito-temporal cortex (lvOT) during reading in a quantitatively explicit and testable manner, we propose the lexical categorization model (LCM). The LCM assumes that lvOT optimizes linguistic processing by allowing fast meaning access when w...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182256/ https://www.ncbi.nlm.nih.gov/pubmed/35679333 http://dx.doi.org/10.1371/journal.pcbi.1009995 |
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author | Gagl, Benjamin Richlan, Fabio Ludersdorfer, Philipp Sassenhagen, Jona Eisenhauer, Susanne Gregorova, Klara Fiebach, Christian J. |
author_facet | Gagl, Benjamin Richlan, Fabio Ludersdorfer, Philipp Sassenhagen, Jona Eisenhauer, Susanne Gregorova, Klara Fiebach, Christian J. |
author_sort | Gagl, Benjamin |
collection | PubMed |
description | To characterize the functional role of the left-ventral occipito-temporal cortex (lvOT) during reading in a quantitatively explicit and testable manner, we propose the lexical categorization model (LCM). The LCM assumes that lvOT optimizes linguistic processing by allowing fast meaning access when words are familiar and filtering out orthographic strings without meaning. The LCM successfully simulates benchmark results from functional brain imaging described in the literature. In a second evaluation, we empirically demonstrate that quantitative LCM simulations predict lvOT activation better than alternative models across three functional magnetic resonance imaging studies. We found that word-likeness, assumed as input into a lexical categorization process, is represented posteriorly to lvOT, whereas a dichotomous word/non-word output of the LCM could be localized to the downstream frontal brain regions. Finally, training the process of lexical categorization resulted in more efficient reading. In sum, we propose that word recognition in the ventral visual stream involves word-likeness extraction followed by lexical categorization before one can access word meaning. |
format | Online Article Text |
id | pubmed-9182256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-91822562022-06-10 The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition Gagl, Benjamin Richlan, Fabio Ludersdorfer, Philipp Sassenhagen, Jona Eisenhauer, Susanne Gregorova, Klara Fiebach, Christian J. PLoS Comput Biol Research Article To characterize the functional role of the left-ventral occipito-temporal cortex (lvOT) during reading in a quantitatively explicit and testable manner, we propose the lexical categorization model (LCM). The LCM assumes that lvOT optimizes linguistic processing by allowing fast meaning access when words are familiar and filtering out orthographic strings without meaning. The LCM successfully simulates benchmark results from functional brain imaging described in the literature. In a second evaluation, we empirically demonstrate that quantitative LCM simulations predict lvOT activation better than alternative models across three functional magnetic resonance imaging studies. We found that word-likeness, assumed as input into a lexical categorization process, is represented posteriorly to lvOT, whereas a dichotomous word/non-word output of the LCM could be localized to the downstream frontal brain regions. Finally, training the process of lexical categorization resulted in more efficient reading. In sum, we propose that word recognition in the ventral visual stream involves word-likeness extraction followed by lexical categorization before one can access word meaning. Public Library of Science 2022-06-09 /pmc/articles/PMC9182256/ /pubmed/35679333 http://dx.doi.org/10.1371/journal.pcbi.1009995 Text en © 2022 Gagl et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Gagl, Benjamin Richlan, Fabio Ludersdorfer, Philipp Sassenhagen, Jona Eisenhauer, Susanne Gregorova, Klara Fiebach, Christian J. The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition |
title | The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition |
title_full | The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition |
title_fullStr | The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition |
title_full_unstemmed | The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition |
title_short | The lexical categorization model: A computational model of left ventral occipito-temporal cortex activation in visual word recognition |
title_sort | lexical categorization model: a computational model of left ventral occipito-temporal cortex activation in visual word recognition |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182256/ https://www.ncbi.nlm.nih.gov/pubmed/35679333 http://dx.doi.org/10.1371/journal.pcbi.1009995 |
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