Mental Fatigue Has Great Impact on the Fractal Dimension of Brain Functional Network
Copyright © 2020 Gang Li et al.
| Veröffentlicht in: | Neural plasticity. - 1998. - 2020(2020) vom: 01., Seite 8825547 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | Neural plasticity |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Zusammenfassung: | Copyright © 2020 Gang Li et al. Mental fatigue has serious negative impacts on the brain cognitive functions and has been widely explored by the means of brain functional networks with the neuroimaging technique of electroencephalogram (EEG). Recently, several researchers reported that brain functional network constructed from EEG signals has fractal feature, raising an important question: what are the effects of mental fatigue on the fractal dimension of brain functional network? In the present study, the EEG data of alpha1 rhythm (8-10 Hz) at task state obtained by a mental fatigue model were chosen to construct brain functional networks. A modified greedy colouring algorithm was proposed for fractal dimension calculation in both binary and weighted brain functional networks. The results indicate that brain functional networks still maintain fractal structures even when the brain is at fatigue state; fractal dimension presented an increasing trend along with the deepening of mental fatigue fractal dimension of the weighted network was more sensitive to mental fatigue than that of binary network. Our current results suggested that mental fatigue has great regular impacts on the fractal dimension in both binary and weighted brain functional networks |
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| Beschreibung: | Date Completed 11.10.2021 Date Revised 30.03.2024 published: Electronic-eCollection Citation Status MEDLINE |
| ISSN: | 1687-5443 |
| DOI: | 10.1155/2020/8825547 |