Standard low-resolution electromagnetic tomography imaging of brain for the analysis of mental fatigue during a simulated air traffic control task.

Neuro endocrinology letters Pub Date : 2023-12-12
Lin Cong, Meiqing Huang, Jinghua Yang, Shan Cheng, Chaolin Teng, Kaiwen Xiong, Taihui Zhang, Weitao Dang, Cui Liu, Jin Ma, Wendong Hu
{"title":"Standard low-resolution electromagnetic tomography imaging of brain for the analysis of mental fatigue during a simulated air traffic control task.","authors":"Lin Cong, Meiqing Huang, Jinghua Yang, Shan Cheng, Chaolin Teng, Kaiwen Xiong, Taihui Zhang, Weitao Dang, Cui Liu, Jin Ma, Wendong Hu","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Standard low-resolution electromagnetic tomography (sLORETA) was used to accurately detect EEG changes in mental fatigue of air traffic controllers (ATCo) under a simulated air traffic control (ATC) task. We explored the changes in standard current density, activated cortical intensity, and brain source location.</p><p><strong>Methods: </strong>The participants were instructed to use the tower flight command simulation training system for three hours of uninterrupted ATC task. The 3-hour EEG signal was divided into four stages: task start, 1st hour, 2nd hour, and task end. Each stage was preprocessed for 3 minutes to explore the EEG changes and then processed by sLORETA in a statistical non-parametric mapping analysis.</p><p><strong>Results: </strong>The current density distribution of δ and α oscillations differed significantly during the four tasks, while θ, β and γ oscillations did not. Changes in δ oscillations of the brain during mental fatigue were detected mainly in the postcentral gyrus (BA2 and BA3), precentral gyrus (BA4 and BA6), inferior temporal gyrus (BA20), and superior temporal gyrus (BA38). The α oscillations were found mainly decreased in the postcentral gyrus (BA2) and inferior parietal lobule (BA40) when the task was in progress compared with the end of the task.</p><p><strong>Conclusion: </strong>The superior temporal gyrus and somatosensory cortex were the main activated cortical regions during the simulated ATC task. The α and δ oscillations showed contrasting activity during simulated ATC task, which might reflect the release of task-relevant brain's areas from inhibition and enhance the neural activity.</p>","PeriodicalId":94154,"journal":{"name":"Neuro endocrinology letters","volume":"44 8","pages":"491-499"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuro endocrinology letters","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Standard low-resolution electromagnetic tomography (sLORETA) was used to accurately detect EEG changes in mental fatigue of air traffic controllers (ATCo) under a simulated air traffic control (ATC) task. We explored the changes in standard current density, activated cortical intensity, and brain source location.

Methods: The participants were instructed to use the tower flight command simulation training system for three hours of uninterrupted ATC task. The 3-hour EEG signal was divided into four stages: task start, 1st hour, 2nd hour, and task end. Each stage was preprocessed for 3 minutes to explore the EEG changes and then processed by sLORETA in a statistical non-parametric mapping analysis.

Results: The current density distribution of δ and α oscillations differed significantly during the four tasks, while θ, β and γ oscillations did not. Changes in δ oscillations of the brain during mental fatigue were detected mainly in the postcentral gyrus (BA2 and BA3), precentral gyrus (BA4 and BA6), inferior temporal gyrus (BA20), and superior temporal gyrus (BA38). The α oscillations were found mainly decreased in the postcentral gyrus (BA2) and inferior parietal lobule (BA40) when the task was in progress compared with the end of the task.

Conclusion: The superior temporal gyrus and somatosensory cortex were the main activated cortical regions during the simulated ATC task. The α and δ oscillations showed contrasting activity during simulated ATC task, which might reflect the release of task-relevant brain's areas from inhibition and enhance the neural activity.

分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
标准低分辨率电磁断层扫描脑成像,用于分析模拟空中交通管制任务中的精神疲劳。
背景:标准低分辨率电磁断层扫描(sLORETA)用于准确检测模拟空中交通管制(ATC)任务下空中交通管制员(ATC)精神疲劳时的脑电图变化。我们探讨了标准电流密度、激活皮层强度和脑源位置的变化:方法:指导参与者使用塔台飞行指挥模拟训练系统进行 3 小时不间断的空管任务。3 小时的脑电信号分为四个阶段:任务开始、第一小时、第二小时和任务结束。每个阶段都经过 3 分钟的预处理,以探索脑电图的变化,然后用 sLORETA 进行非参数映射统计分析:结果:在四项任务中,δ和α振荡的电流密度分布有显著差异,而θ、β和γ振荡则没有。精神疲劳时大脑δ振荡的变化主要出现在中央后回(BA2和BA3)、中央前回(BA4和BA6)、颞下回(BA20)和颞上回(BA38)。与任务结束时相比,任务进行时α振荡主要在中央后回(BA2)和顶叶下小叶(BA40)减少:结论:颞上回和躯体感觉皮层是模拟 ATC 任务过程中被激活的主要皮层区域。结论:颞上回和躯体感觉皮层是模拟 ATC 任务过程中被激活的主要皮层区域,α 和 δ 振荡在模拟 ATC 任务过程中表现出截然不同的活动性,这可能反映了与任务相关的脑区从抑制中释放出来并增强了神经活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Building skills in cognitive behavioral supervision. Hybrid Artificial Intelligence Solution Combining Convolutional Neural Network and Analytical Approach Showed Higher Accuracy in A-lines Detection on Lung Ultrasound in Thoracic Surgery Patients Compared with Radiology Resident. Impact of an over-the-counter "sleep lotion" on human salivary melatonin levels and sleep quality: a randomized controlled trial. New approach and strategy in the assessment of labour pain - Czech version of the labour coping pain assessment tool. Protective effects and mechanisms of deer blood phospholipids (DBP) on zearalenone-induced oxidative damage in swine Sertoli cells.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1