Effects of Mental Fatigue on Small-World Brain Functional Network Organization
Brain functional network has been widely applied to investigate brain function changes among different conditions and proved to be a small-world-like network. But seldom researches explore the effects of mental fatigue on the small-world brain functional network organization. In the present study, 2...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Neural Plasticity |
| Online Access: | http://dx.doi.org/10.1155/2019/1716074 |
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| author | Gang Li Youdong Luo Zhengru Zhang Yanting Xu Weidong Jiao Yonghua Jiang Shan Huang Chengwu Wang |
| author_facet | Gang Li Youdong Luo Zhengru Zhang Yanting Xu Weidong Jiao Yonghua Jiang Shan Huang Chengwu Wang |
| author_sort | Gang Li |
| collection | DOAJ |
| description | Brain functional network has been widely applied to investigate brain function changes among different conditions and proved to be a small-world-like network. But seldom researches explore the effects of mental fatigue on the small-world brain functional network organization. In the present study, 20 healthy individuals were included to do a consecutive mental arithmetic task to induce mental fatigue, and scalp electroencephalogram (EEG) signals were recorded before and after the task. Correlations between all pairs of EEG channels were determined by mutual information (MI). The resulting adjacency matrices were converted into brain functional networks by applying a threshold, and then, the clustering coefficient (C), characteristic path length (L), and corresponding small-world feature were calculated. Through performing analysis of variance (ANOVA) on the mean MI for every EEG rhythm, only the data of α1 rhythm during the task state were emerged for the further explorations of mental fatigue. For a wide range of thresholds, C increased and L and small-world feature decreased with the deepening mental fatigue. The pattern of the small-world characteristic still existed when computed with a constant degree. Our present findings indicated that more functional connectivities were activated at the mental fatigue stage for efficient information transmission and processing, and mental fatigue can be characterized by a reduced small-world network characteristic. Our results provide a new perspective to understand the neural mechanisms of mental fatigue based on complex network theories. |
| format | Article |
| id | doaj-art-bc21122efe3a4f289672cf1956c9fec6 |
| institution | Kabale University |
| issn | 2090-5904 1687-5443 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neural Plasticity |
| spelling | doaj-art-bc21122efe3a4f289672cf1956c9fec62025-02-03T06:12:08ZengWileyNeural Plasticity2090-59041687-54432019-01-01201910.1155/2019/17160741716074Effects of Mental Fatigue on Small-World Brain Functional Network OrganizationGang Li0Youdong Luo1Zhengru Zhang2Yanting Xu3Weidong Jiao4Yonghua Jiang5Shan Huang6Chengwu Wang7College of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, ChinaBrain functional network has been widely applied to investigate brain function changes among different conditions and proved to be a small-world-like network. But seldom researches explore the effects of mental fatigue on the small-world brain functional network organization. In the present study, 20 healthy individuals were included to do a consecutive mental arithmetic task to induce mental fatigue, and scalp electroencephalogram (EEG) signals were recorded before and after the task. Correlations between all pairs of EEG channels were determined by mutual information (MI). The resulting adjacency matrices were converted into brain functional networks by applying a threshold, and then, the clustering coefficient (C), characteristic path length (L), and corresponding small-world feature were calculated. Through performing analysis of variance (ANOVA) on the mean MI for every EEG rhythm, only the data of α1 rhythm during the task state were emerged for the further explorations of mental fatigue. For a wide range of thresholds, C increased and L and small-world feature decreased with the deepening mental fatigue. The pattern of the small-world characteristic still existed when computed with a constant degree. Our present findings indicated that more functional connectivities were activated at the mental fatigue stage for efficient information transmission and processing, and mental fatigue can be characterized by a reduced small-world network characteristic. Our results provide a new perspective to understand the neural mechanisms of mental fatigue based on complex network theories.http://dx.doi.org/10.1155/2019/1716074 |
| spellingShingle | Gang Li Youdong Luo Zhengru Zhang Yanting Xu Weidong Jiao Yonghua Jiang Shan Huang Chengwu Wang Effects of Mental Fatigue on Small-World Brain Functional Network Organization Neural Plasticity |
| title | Effects of Mental Fatigue on Small-World Brain Functional Network Organization |
| title_full | Effects of Mental Fatigue on Small-World Brain Functional Network Organization |
| title_fullStr | Effects of Mental Fatigue on Small-World Brain Functional Network Organization |
| title_full_unstemmed | Effects of Mental Fatigue on Small-World Brain Functional Network Organization |
| title_short | Effects of Mental Fatigue on Small-World Brain Functional Network Organization |
| title_sort | effects of mental fatigue on small world brain functional network organization |
| url | http://dx.doi.org/10.1155/2019/1716074 |
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