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Is there evidence for a noisy computation deficit in developmental dyslexia?
The noisy computation hypothesis of developmental dyslexia (DD) is particularly appealing because it can explain deficits across a variety of domains, such as temporal, auditory, phonological, visual and attentional processes. A key prediction is that noisy computations lead to more variable and les...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561132/ https://www.ncbi.nlm.nih.gov/pubmed/36248689 http://dx.doi.org/10.3389/fnhum.2022.919465 |
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author | Tan, Yufei Chanoine, Valérie Cavalli, Eddy Anton, Jean-Luc Ziegler, Johannes C. |
author_facet | Tan, Yufei Chanoine, Valérie Cavalli, Eddy Anton, Jean-Luc Ziegler, Johannes C. |
author_sort | Tan, Yufei |
collection | PubMed |
description | The noisy computation hypothesis of developmental dyslexia (DD) is particularly appealing because it can explain deficits across a variety of domains, such as temporal, auditory, phonological, visual and attentional processes. A key prediction is that noisy computations lead to more variable and less stable word representations. A way to test this hypothesis is through repetition of words, that is, when there is noise in the system, the neural signature of repeated stimuli should be more variable. The hypothesis was tested in an functional magnetic resonance imaging experiment with dyslexic and typical readers by repeating words twelve times. Variability measures were computed both at the behavioral and neural levels. At the behavioral level, we compared the standard deviation of reaction time distributions of repeated words. At the neural level, in addition to standard univariate analyses and measures of intra-item variability, we also used multivariate pattern analyses (representational similarity and classification) to find out whether there was evidence for noisier representations in dyslexic readers compared to typical readers. Results showed that there were no significant differences between the two groups in any of the analyses despite robust results within each group (i.e., high representational similarity between repeated words, good classification of words vs. non-words). In summary, there was no evidence in favor of the idea that dyslexic readers would have noisier neural representations than typical readers. |
format | Online Article Text |
id | pubmed-9561132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95611322022-10-15 Is there evidence for a noisy computation deficit in developmental dyslexia? Tan, Yufei Chanoine, Valérie Cavalli, Eddy Anton, Jean-Luc Ziegler, Johannes C. Front Hum Neurosci Neuroscience The noisy computation hypothesis of developmental dyslexia (DD) is particularly appealing because it can explain deficits across a variety of domains, such as temporal, auditory, phonological, visual and attentional processes. A key prediction is that noisy computations lead to more variable and less stable word representations. A way to test this hypothesis is through repetition of words, that is, when there is noise in the system, the neural signature of repeated stimuli should be more variable. The hypothesis was tested in an functional magnetic resonance imaging experiment with dyslexic and typical readers by repeating words twelve times. Variability measures were computed both at the behavioral and neural levels. At the behavioral level, we compared the standard deviation of reaction time distributions of repeated words. At the neural level, in addition to standard univariate analyses and measures of intra-item variability, we also used multivariate pattern analyses (representational similarity and classification) to find out whether there was evidence for noisier representations in dyslexic readers compared to typical readers. Results showed that there were no significant differences between the two groups in any of the analyses despite robust results within each group (i.e., high representational similarity between repeated words, good classification of words vs. non-words). In summary, there was no evidence in favor of the idea that dyslexic readers would have noisier neural representations than typical readers. Frontiers Media S.A. 2022-09-30 /pmc/articles/PMC9561132/ /pubmed/36248689 http://dx.doi.org/10.3389/fnhum.2022.919465 Text en Copyright © 2022 Tan, Chanoine, Cavalli, Anton and Ziegler. 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 Tan, Yufei Chanoine, Valérie Cavalli, Eddy Anton, Jean-Luc Ziegler, Johannes C. Is there evidence for a noisy computation deficit in developmental dyslexia? |
title | Is there evidence for a noisy computation deficit in developmental dyslexia? |
title_full | Is there evidence for a noisy computation deficit in developmental dyslexia? |
title_fullStr | Is there evidence for a noisy computation deficit in developmental dyslexia? |
title_full_unstemmed | Is there evidence for a noisy computation deficit in developmental dyslexia? |
title_short | Is there evidence for a noisy computation deficit in developmental dyslexia? |
title_sort | is there evidence for a noisy computation deficit in developmental dyslexia? |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561132/ https://www.ncbi.nlm.nih.gov/pubmed/36248689 http://dx.doi.org/10.3389/fnhum.2022.919465 |
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