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Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema
The study of mental workload has attracted much interest in neuroergonomics, a frontier field of research. However, there appears no consensus on how to measure mental workload effectively because the mental workload is not only regulated by task difficulty but also affected by individual skill leve...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046556/ https://www.ncbi.nlm.nih.gov/pubmed/36979183 http://dx.doi.org/10.3390/brainsci13030373 |
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author | Gu, Heng Chen, He Yao, Qunli He, Wenbo Wang, Shaodi Yang, Chao Li, Jiaxi Liu, Huapeng Li, Xiaoli Zhao, Xiaochuan Liang, Guanhao |
author_facet | Gu, Heng Chen, He Yao, Qunli He, Wenbo Wang, Shaodi Yang, Chao Li, Jiaxi Liu, Huapeng Li, Xiaoli Zhao, Xiaochuan Liang, Guanhao |
author_sort | Gu, Heng |
collection | PubMed |
description | The study of mental workload has attracted much interest in neuroergonomics, a frontier field of research. However, there appears no consensus on how to measure mental workload effectively because the mental workload is not only regulated by task difficulty but also affected by individual skill level reflected as mental schema. In this study, we investigated the alterations in the functional brain network induced by a 10-day simulated piloting task with different difficulty levels. Topological features quantifying global and local information communication and network organization were analyzed. It was found that during different tests, the global efficiency did not change, but the gravity center of the local efficiency of the network moved from the frontal to the posterior area; the small-worldness of the functional brain network became stronger. These results demonstrate the reconfiguration of the brain network during the development of mental schema. Furthermore, for the first two tests, the global and local efficiency did not have a consistent change trend under different difficulty levels, but after forming the developed mental schema, both of them decreased with the increase in task difficulty, showing sensitivity to the increase in mental workload. Our results demonstrate brain network reconfiguration during the motor learning process and reveal the importance of the developed mental schema for the accurate assessment of mental workload. We concluded that the efficiency of the brain network was associated with mental workload with developed mental schema. |
format | Online Article Text |
id | pubmed-10046556 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100465562023-03-29 Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema Gu, Heng Chen, He Yao, Qunli He, Wenbo Wang, Shaodi Yang, Chao Li, Jiaxi Liu, Huapeng Li, Xiaoli Zhao, Xiaochuan Liang, Guanhao Brain Sci Article The study of mental workload has attracted much interest in neuroergonomics, a frontier field of research. However, there appears no consensus on how to measure mental workload effectively because the mental workload is not only regulated by task difficulty but also affected by individual skill level reflected as mental schema. In this study, we investigated the alterations in the functional brain network induced by a 10-day simulated piloting task with different difficulty levels. Topological features quantifying global and local information communication and network organization were analyzed. It was found that during different tests, the global efficiency did not change, but the gravity center of the local efficiency of the network moved from the frontal to the posterior area; the small-worldness of the functional brain network became stronger. These results demonstrate the reconfiguration of the brain network during the development of mental schema. Furthermore, for the first two tests, the global and local efficiency did not have a consistent change trend under different difficulty levels, but after forming the developed mental schema, both of them decreased with the increase in task difficulty, showing sensitivity to the increase in mental workload. Our results demonstrate brain network reconfiguration during the motor learning process and reveal the importance of the developed mental schema for the accurate assessment of mental workload. We concluded that the efficiency of the brain network was associated with mental workload with developed mental schema. MDPI 2023-02-21 /pmc/articles/PMC10046556/ /pubmed/36979183 http://dx.doi.org/10.3390/brainsci13030373 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gu, Heng Chen, He Yao, Qunli He, Wenbo Wang, Shaodi Yang, Chao Li, Jiaxi Liu, Huapeng Li, Xiaoli Zhao, Xiaochuan Liang, Guanhao Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema |
title | Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema |
title_full | Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema |
title_fullStr | Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema |
title_full_unstemmed | Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema |
title_short | Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema |
title_sort | efficiency of the brain network is associated with the mental workload with developed mental schema |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10046556/ https://www.ncbi.nlm.nih.gov/pubmed/36979183 http://dx.doi.org/10.3390/brainsci13030373 |
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