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Research Article | Open Access

The effect of fatigue on brain connectivity networks

Shangen Zhang1Jingnan Sun2Xiaorong Gao2( )
Department of School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
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Abstract

In the fatigue state, the neural response characteristics of the brain might be different from those in the normal state. Brain functional connectivity analysis is an effective tool for distinguishing between different brain states. For example, comparative studies on the brain functional connectivity have the potential to reveal the functional differences in different mental states. The purpose of this study was to explore the relationship between human mental states and brain control abilities by analyzing the effect of fatigue on the brain response connectivity. In particular, the phase-scrambling method was used to generate images with two noise levels, while the N-back working memory task was used to induce the fatigue state in subjects. The paradigm of rapid serial visual presentation (RSVP) was used to present visual stimuli. The analysis of brain connections in the normal and fatigue states was conducted using the open-source eConnectome toolbox. The results demonstrated that the control areas of neural responses were mainly distributed in the parietal region in both the normal and fatigue states. Compared to the normal state, the brain connectivity power in the parietal region was significantly weakened under the fatigue state, which indicates that the control ability of the brain is reduced in the fatigue state.

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Brain Science Advances
Pages 120-131

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Cite this article:
Zhang S, Sun J, Gao X. The effect of fatigue on brain connectivity networks. Brain Science Advances, 2020, 6(2): 120-131. https://doi.org/10.26599/BSA.2020.9050008

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Received: 24 February 2020
Revised: 23 March 2020
Accepted: 24 March 2020
Published: 31 August 2020
© The authors 2020

This article is published with open access at journals.sagepub.com/home/BSA

Creative Commons Non Commercial CC BY- NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/ en-us/nam/open-access-at-sage).