首页> 美国卫生研究院文献>Journal of Undergraduate Neuroscience Education >Use of Personal EEG Monitors in a Behavioral Neuroscience Course to Investigate Natural Setting Sleep Patterns and the Factors Affecting Them in College Students
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Use of Personal EEG Monitors in a Behavioral Neuroscience Course to Investigate Natural Setting Sleep Patterns and the Factors Affecting Them in College Students

机译:在行为神经科学课程中使用个人脑电监测器调查大学生的自然环境睡眠模式及其影响因素

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摘要

Sleep is often a topic of avid interest to college students, yet it is one that does not yield itself well to hands-on, interactive learning modules. Supplementing classroom learning with interactive “real world” laboratory activities provides students with a deeper understanding of behavior and its neural control. The project described here was designed to supplement the teaching of EEGs, sleep and circadian rhythms and involved students in the empirical process from hypothesizing about the factors that affect sleep, to personal data collection, data analysis and writing in the style of a peer-reviewed manuscript. Students enrolled in Behavioral Neuroscience at Connecticut College were provided with a home-based personal EEG monitor used to collect sleep data in their natural sleep setting. Participants recorded sleep data with the use of the ZEO® Personal Sleep Coach system and completed a nightly sleep journal questionnaire for seven nights. The ZEO® system uses EEG patterns to define sleep stages including wakefulness, light, deep and REM sleep. The journal included questions about factors known to affect sleep such as stress, caffeine, academic activity, exercise and alcohol. A class data set was compiled and used by students to perform univariate correlations examining the relationships between ZEO® variables and sleep journal variables. The data set allowed students to choose specific variables to investigate, analyze and write a peer-reviewed style manuscript. Significant class-wide correlations were found between specific sleep stages and behavioral variables suggesting that the ZEO® system is sophisticated yet inexpensive enough to be used as an effective tool in the classroom setting. Overall student feedback on the exercise was positive with many students indicating that it significantly enhanced their understanding of sleep architecture and made them keenly aware of the factors that affect quality of sleep.
机译:睡眠通常是大学生非常感兴趣的话题,但对于动手操作的交互式学习模块而言,睡眠本身并不令人满意。通过交互式“真实世界”实验室活动补充课堂学习,使学生对行为及其神经控制有更深入的了解。这里描述的项目旨在补充脑电图,睡眠和昼夜节律的教学,并让学生参与经验过程,从假设影响睡眠的因素到个人数据收集,数据分析和以同行评审的方式撰写。手稿。向康涅狄格大学的行为神经科学学院的学生提供了一个基于家庭的个人EEG监视器,用于在他们的自然睡眠环境中收集睡眠数据。参与者使用ZEO®个人睡眠教练系统记录了睡眠数据,并完成了七个晚上的夜间睡眠日记调查表。 ZEO®系统使用EEG模式定义睡眠阶段,包括清醒,浅睡,深度睡眠和REM睡眠。该期刊包括有关已知影响睡眠的因素的问题,例如压力,咖啡因,学习活动,运动和酗酒。学生汇编了一个班级数据集,并用于执行单变量相关性,检查ZEO®变量与睡眠日志变量之间的关系。该数据集使学生可以选择特定的变量来调查,分析和编写经过同行评审的样式手稿。在特定的睡眠阶段和行为变量之间发现了全班级的显着相关性,这表明ZEO®系统既复杂又便宜,足以用作教室环境中的有效工具。学生对该运动的总体反馈是积极的,许多学生表明,该运动大大增强了他们对睡眠结构的理解,并使他们敏锐地意识到影响睡眠质量的因素。

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