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Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty
Working memory, which is regarded as the foundation of cognitive processes, is a system that stores, processes, and manipulates information in short intervals of time that are actually needed for daily functioning. This study aimed to assess the brain activity of healthy controls (HC) while performi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543376/ https://www.ncbi.nlm.nih.gov/pubmed/37777667 http://dx.doi.org/10.1038/s41598-023-43837-w |
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author | Miri Ashtiani, Seyedeh Naghmeh Daliri, Mohammad Reza |
author_facet | Miri Ashtiani, Seyedeh Naghmeh Daliri, Mohammad Reza |
author_sort | Miri Ashtiani, Seyedeh Naghmeh |
collection | PubMed |
description | Working memory, which is regarded as the foundation of cognitive processes, is a system that stores, processes, and manipulates information in short intervals of time that are actually needed for daily functioning. This study aimed to assess the brain activity of healthy controls (HC) while performing the N-back task, which is one of the most popularly used tests for evaluating working memory along with functional magnetic resonance imaging (fMRI). In this regard, we collected fMRI data from right-handed individuals in a 3.0 T scanner during the Persian version of the visual variant N-back task performance with three levels of complexity varied throughout the experiment (1, 2, and 3-back conditions) to increase the cognitive demands. The statistical parametric mapping (SPM12) software was used to analyze fMRI data for the identification of cognitive load-dependent activation patterns based on contrast images obtained from different levels of task difficulty. Our findings showed that as cognitive complexity increased, the number of significant activation clusters and cluster extent increased in several areas distributed in the cerebellum, frontoparietal lobes, insula, SMA, and lenticular nucleus, the majority of which are recognized for their role in working memory. Furthermore, deactivation patterns during 1-, 2-, and 3-back vs. 0-back contrasts revealed significant clusters in brain regions that are mostly described as being part of the default mode network (DMN). Based on previous research, our results supported the recognized involvement of the mentioned cortical and subcortical areas in various types or levels of N-back tasks. This study found that altering activation patterns by increasing task difficulty could aid in evaluating the various stages of cognitive dysfunction in many brain diseases such as multiple sclerosis (MS) and Alzheimer's disease by comparing controls in future studies to apply early appropriate treatment strategies. |
format | Online Article Text |
id | pubmed-10543376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105433762023-10-03 Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty Miri Ashtiani, Seyedeh Naghmeh Daliri, Mohammad Reza Sci Rep Article Working memory, which is regarded as the foundation of cognitive processes, is a system that stores, processes, and manipulates information in short intervals of time that are actually needed for daily functioning. This study aimed to assess the brain activity of healthy controls (HC) while performing the N-back task, which is one of the most popularly used tests for evaluating working memory along with functional magnetic resonance imaging (fMRI). In this regard, we collected fMRI data from right-handed individuals in a 3.0 T scanner during the Persian version of the visual variant N-back task performance with three levels of complexity varied throughout the experiment (1, 2, and 3-back conditions) to increase the cognitive demands. The statistical parametric mapping (SPM12) software was used to analyze fMRI data for the identification of cognitive load-dependent activation patterns based on contrast images obtained from different levels of task difficulty. Our findings showed that as cognitive complexity increased, the number of significant activation clusters and cluster extent increased in several areas distributed in the cerebellum, frontoparietal lobes, insula, SMA, and lenticular nucleus, the majority of which are recognized for their role in working memory. Furthermore, deactivation patterns during 1-, 2-, and 3-back vs. 0-back contrasts revealed significant clusters in brain regions that are mostly described as being part of the default mode network (DMN). Based on previous research, our results supported the recognized involvement of the mentioned cortical and subcortical areas in various types or levels of N-back tasks. This study found that altering activation patterns by increasing task difficulty could aid in evaluating the various stages of cognitive dysfunction in many brain diseases such as multiple sclerosis (MS) and Alzheimer's disease by comparing controls in future studies to apply early appropriate treatment strategies. Nature Publishing Group UK 2023-09-30 /pmc/articles/PMC10543376/ /pubmed/37777667 http://dx.doi.org/10.1038/s41598-023-43837-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Miri Ashtiani, Seyedeh Naghmeh Daliri, Mohammad Reza Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty |
title | Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty |
title_full | Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty |
title_fullStr | Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty |
title_full_unstemmed | Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty |
title_short | Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty |
title_sort | identification of cognitive load-dependent activation patterns using working memory task-based fmri at various levels of difficulty |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543376/ https://www.ncbi.nlm.nih.gov/pubmed/37777667 http://dx.doi.org/10.1038/s41598-023-43837-w |
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