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Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing
The brain generates predictions about visual word forms to support efficient reading. The “interactive account” suggests that the predictions in visual word processing can be strategic or automatic (non-strategic). Strategic predictions are frequently demonstrated in studies that manipulated task de...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864072/ https://www.ncbi.nlm.nih.gov/pubmed/35221891 http://dx.doi.org/10.3389/fnins.2021.809574 |
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author | Huang, Zehao Yang, Shimeng Xue, Licheng Yang, Hang Lv, Yating Zhao, Jing |
author_facet | Huang, Zehao Yang, Shimeng Xue, Licheng Yang, Hang Lv, Yating Zhao, Jing |
author_sort | Huang, Zehao |
collection | PubMed |
description | The brain generates predictions about visual word forms to support efficient reading. The “interactive account” suggests that the predictions in visual word processing can be strategic or automatic (non-strategic). Strategic predictions are frequently demonstrated in studies that manipulated task demands, however, few studies have investigated automatic predictions. Orthographic knowledge varies greatly among individuals and it offers a unique opportunity in revealing automatic predictions. The present study grouped the participants by level of orthographic knowledge and recorded EEGs in a non-linguistic color matching task. The visual word-selective N170 response was much stronger to pseudo than to real characters in participants with low orthographic knowledge, but not in those with high orthographic knowledge. Previous work on predictive coding has demonstrated that N170 is a good index for prediction errors, i.e., the mismatches between predictions and visual inputs. The present findings provide unambiguous evidence that automatic predictions modulate the early stage of visual word processing. |
format | Online Article Text |
id | pubmed-8864072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88640722022-02-24 Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing Huang, Zehao Yang, Shimeng Xue, Licheng Yang, Hang Lv, Yating Zhao, Jing Front Neurosci Neuroscience The brain generates predictions about visual word forms to support efficient reading. The “interactive account” suggests that the predictions in visual word processing can be strategic or automatic (non-strategic). Strategic predictions are frequently demonstrated in studies that manipulated task demands, however, few studies have investigated automatic predictions. Orthographic knowledge varies greatly among individuals and it offers a unique opportunity in revealing automatic predictions. The present study grouped the participants by level of orthographic knowledge and recorded EEGs in a non-linguistic color matching task. The visual word-selective N170 response was much stronger to pseudo than to real characters in participants with low orthographic knowledge, but not in those with high orthographic knowledge. Previous work on predictive coding has demonstrated that N170 is a good index for prediction errors, i.e., the mismatches between predictions and visual inputs. The present findings provide unambiguous evidence that automatic predictions modulate the early stage of visual word processing. Frontiers Media S.A. 2022-02-09 /pmc/articles/PMC8864072/ /pubmed/35221891 http://dx.doi.org/10.3389/fnins.2021.809574 Text en Copyright © 2022 Huang, Yang, Xue, Yang, Lv and Zhao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Huang, Zehao Yang, Shimeng Xue, Licheng Yang, Hang Lv, Yating Zhao, Jing Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing |
title | Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing |
title_full | Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing |
title_fullStr | Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing |
title_full_unstemmed | Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing |
title_short | Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing |
title_sort | level of orthographic knowledge helps to reveal automatic predictions in visual word processing |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8864072/ https://www.ncbi.nlm.nih.gov/pubmed/35221891 http://dx.doi.org/10.3389/fnins.2021.809574 |
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