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A mechanistic insight into sources of error of visual working memory in multiple sclerosis
Working memory (WM) is one of the most affected cognitive domains in multiple sclerosis (MS), which is mainly studied by the previously established binary model for information storage (slot model). However, recent observations based on the continuous reproduction paradigms have shown that assuming...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631758/ https://www.ncbi.nlm.nih.gov/pubmed/37937840 http://dx.doi.org/10.7554/eLife.87442 |
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author | Motahharynia, Ali Pourmohammadi, Ahmad Adibi, Armin Shaygannejad, Vahid Ashtari, Fereshteh Adibi, Iman Sanayei, Mehdi |
author_facet | Motahharynia, Ali Pourmohammadi, Ahmad Adibi, Armin Shaygannejad, Vahid Ashtari, Fereshteh Adibi, Iman Sanayei, Mehdi |
author_sort | Motahharynia, Ali |
collection | PubMed |
description | Working memory (WM) is one of the most affected cognitive domains in multiple sclerosis (MS), which is mainly studied by the previously established binary model for information storage (slot model). However, recent observations based on the continuous reproduction paradigms have shown that assuming dynamic allocation of WM resources (resource model) instead of the binary hypothesis will give more accurate predictions in WM assessment. Moreover, continuous reproduction paradigms allow for assessing the distribution of error in recalling information, providing new insights into the organization of the WM system. Hence, by utilizing two continuous reproduction paradigms, memory-guided localization (MGL) and analog recall task with sequential presentation, we investigated WM dysfunction in MS. Our results demonstrated an overall increase in recall error and decreased recall precision in MS. While sequential paradigms were better in distinguishing healthy control from relapsing-remitting MS, MGL were more accurate in discriminating MS subtypes (relapsing-remitting from secondary progressive), providing evidence about the underlying mechanisms of WM deficit in progressive states of the disease. Furthermore, computational modeling of the results from the sequential paradigm determined that imprecision in decoding information and swap error (mistakenly reporting the feature of other presented items) was responsible for WM dysfunction in MS. Overall, this study offered a sensitive measure for assessing WM deficit and provided new insight into the organization of the WM system in MS population. |
format | Online Article Text |
id | pubmed-10631758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-106317582023-11-09 A mechanistic insight into sources of error of visual working memory in multiple sclerosis Motahharynia, Ali Pourmohammadi, Ahmad Adibi, Armin Shaygannejad, Vahid Ashtari, Fereshteh Adibi, Iman Sanayei, Mehdi eLife Neuroscience Working memory (WM) is one of the most affected cognitive domains in multiple sclerosis (MS), which is mainly studied by the previously established binary model for information storage (slot model). However, recent observations based on the continuous reproduction paradigms have shown that assuming dynamic allocation of WM resources (resource model) instead of the binary hypothesis will give more accurate predictions in WM assessment. Moreover, continuous reproduction paradigms allow for assessing the distribution of error in recalling information, providing new insights into the organization of the WM system. Hence, by utilizing two continuous reproduction paradigms, memory-guided localization (MGL) and analog recall task with sequential presentation, we investigated WM dysfunction in MS. Our results demonstrated an overall increase in recall error and decreased recall precision in MS. While sequential paradigms were better in distinguishing healthy control from relapsing-remitting MS, MGL were more accurate in discriminating MS subtypes (relapsing-remitting from secondary progressive), providing evidence about the underlying mechanisms of WM deficit in progressive states of the disease. Furthermore, computational modeling of the results from the sequential paradigm determined that imprecision in decoding information and swap error (mistakenly reporting the feature of other presented items) was responsible for WM dysfunction in MS. Overall, this study offered a sensitive measure for assessing WM deficit and provided new insight into the organization of the WM system in MS population. eLife Sciences Publications, Ltd 2023-11-08 /pmc/articles/PMC10631758/ /pubmed/37937840 http://dx.doi.org/10.7554/eLife.87442 Text en © 2023, Motahharynia, Pourmohammadi et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Motahharynia, Ali Pourmohammadi, Ahmad Adibi, Armin Shaygannejad, Vahid Ashtari, Fereshteh Adibi, Iman Sanayei, Mehdi A mechanistic insight into sources of error of visual working memory in multiple sclerosis |
title | A mechanistic insight into sources of error of visual working memory in multiple sclerosis |
title_full | A mechanistic insight into sources of error of visual working memory in multiple sclerosis |
title_fullStr | A mechanistic insight into sources of error of visual working memory in multiple sclerosis |
title_full_unstemmed | A mechanistic insight into sources of error of visual working memory in multiple sclerosis |
title_short | A mechanistic insight into sources of error of visual working memory in multiple sclerosis |
title_sort | mechanistic insight into sources of error of visual working memory in multiple sclerosis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631758/ https://www.ncbi.nlm.nih.gov/pubmed/37937840 http://dx.doi.org/10.7554/eLife.87442 |
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