SHB: Type I (EXP): Long-term Mobile Monitoring and Analysis of Sleep-Cognition Relationship

睡眠对人类健康和福祉的重要性早已被认识到。当代研究强调了睡眠影响我们日常生活的两个核心过程：记忆巩固和情绪调节。然而，基于实验室的睡眠研究充分描述睡眠对大脑功能作用的能力受到了实验要求的阻碍，到目前为止，这些要求要求受试者必须在连接到脑电记录器的睡眠实验室里度过一到两个晚上，这种设置的生态有效性有限，通常只适用于一两个晚上。这些要求限制了我们回答有关睡眠对认知和情绪的长期影响的重要问题的能力。该项目旨在通过以下方式回答这些问题：(I)长期移动睡眠和活动监测，以便能够对多个参与者在自己家中数周的睡眠模式进行经济、实用和并行的评估；以及(Ii)移动个性化认知评估，在参与者的家中提供每天两次的短期认知测试和其他自我评估。该项目旨在开发一种智能健康方法，将这两种技术结合起来，在几周的时间内评估睡眠-醒来模式对参与者认知表现的影响，从而获得必要的数据，以回答有关睡眠对认知和情绪的长期影响的研究问题，包括：(I)睡眠模式的波动在许多天内对认知和情绪健康的累积影响是什么？(Ii)在需要几天或几周的持续练习才能掌握的活动中，睡眠对记忆的逐渐巩固有什么影响？智力价值：该项目的预期结果包括对有关睡眠自然波动及其对认知和情绪健康的影响之间复杂相互作用的重要悬而未决问题的答案，通过以下创新：(I)利用移动睡眠、活动和认知评估，以便在参与者的家中进行长期研究；(Ii)使用先前在广泛的临床人群中得到验证的认知任务，并测量参与睡眠相关认知变化的两个关键大脑区域：基底节和内侧颞叶的细微变化。(3)应用基于数学模型的方法来推导参与者使用的学习策略，以提供一种新颖而简明的方法来分析和解释来自认知评估的大量学习数据，以提取可能与睡眠模式变化相关的关键神经认知参数。广泛影响：将移动睡眠监测与认知和情绪评估相结合将通过对个人基线的不显眼监测来促进以患者为中心的健康的卫生保健目标。对于睡眠实验室不可行的受损个体来说，移动睡眠监测可能特别有用。该项目为罗格斯大学的研究生和本科生，包括代表性不足群体的成员，提供了更多以研究为基础的培训机会。所有的研究结果、数据、出版物、数学模型都将免费提供给更大的研究社区。

The importance of sleep to human health and well-being has long been recognized. Contemporary research emphasizes two central processes by which sleep affects our daily lives: Memory-consolidation and emotional regulation. However, the ability of lab-based sleep research to fully characterize the role of sleep in brain function has been hampered by experimental requirements that heretofore have necessitated subjects spending a night or two in a sleep lab wired to an EEG recorder, a setting of limited ecological validity that is usually practical for only one or two nights. These requirements limit our ability to answer important questions regarding the long-term effects of sleep on cognition and mood. This project aims to answer these questions using: (i) Long-term Mobile Sleep and Activity Monitoring to enable the economical, practical, and parallel assessment of sleep patterns of multiple participants in their own homes for several weeks; and (ii) Mobile Individualized Cognitive Assessment to deliver twice-daily short cognitive tests and other self-assessments in participants' homes. The project aims to develop a smart health approach that integrates these two technologies to assess the effect of sleep-wake patterns on the cognitive performance of participants for a period of several weeks, thus obtaining the necessary data needed to answer the research questions regarding the long-term effects of sleep on cognition and mood including: (i) What is the cumulative effect, over many days, of fluctuations in sleep patterns on cognitive and emotional wellbeing? (ii) What are the effects of sleep on the gradual consolidation of memory in activities which require ongoing practice for days or weeks to master? Intellectual Merit: Anticipated results of the project include answers to important unanswered questions about the complex interactions between natural fluctuations in sleep and their influence on cognitive and emotional well-being through innovations in (i) Utilization of mobile sleep, activity, and cognitive assessments to allow long-term studies to take place in participants' homes, (ii) Use of cognitive tasks that have previously been validated in a wide range of clinical populations, and which measure subtle variations in two key brain regions involved in sleep-related changes in cognition: the basal ganglia and medial temporal lobe. (3) Application of mathematical model-based methods for deriving learning strategies used by participants to provide a novel and parsimonious approach to analyzing and interpreting large sets of learning data from the cognitive assessments to extract the key neuro-cognitive parameters which can be related to variations in sleep patterns.Broader Impacts: Integrating mobile sleep monitoring with cognitive and emotional assessments will further the SHB goal of empowering patient-centric wellness using unobtrusive monitoring of individual baselines. Mobile sleep monitoring may be especially useful for impaired individuals for whom a sleep-lab is not viable. The project offers enhanced research-based training opportunities for graduate and undergraduate students, including members of under-represented groups, at Rutgers University. All of the research results, data, publications, mathematical models, will be made freely available to the larger research community.