The effect of fatigue on brain connectivity networks

Shangen Zhang, Jingnan Sun, Xiaorong Gao
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引用次数: 7

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.
疲劳对大脑连接网络的影响
在疲劳状态下,大脑的神经反应特征可能与正常状态下不同。大脑功能连接分析是区分不同大脑状态的有效工具。例如,对大脑功能连接的比较研究有可能揭示不同精神状态下的功能差异。本研究旨在通过分析疲劳对大脑反应连接的影响,探讨人类心理状态与大脑控制能力之间的关系。特别是,相位置乱方法用于生成具有两个噪声水平的图像,而N-back工作记忆任务用于诱导受试者的疲劳状态。快速序列视觉呈现(RSVP)的范例被用来呈现视觉刺激。使用开源eConnectome工具箱对正常和疲劳状态下的大脑连接进行分析。结果表明,在正常和疲劳状态下,神经反应的控制区主要分布在顶叶区。与正常状态相比,疲劳状态下顶叶区的大脑连接能力明显减弱,表明疲劳状态下大脑的控制能力下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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