Quanten Stijn, de Valck Elke, Cluydts Raymond, Aerts Jean-Marie, Berckmans Daniel
Division Measure, Model and Manage Bioresponses (M3-BIORES), Catholic University of Leuven, Leuven, Belgium.
J Sleep Res. 2006 Jun;15(2):183-98. doi: 10.1111/j.1365-2869.2006.00519.x.
This study makes use of control system model identification techniques to examine the relationship between thermoregulation and sleep regulation. Specifically, data-based mechanistic (DBM) modelling is used to formulate and experimentally test the hypothesis, put forth by Gilbert et al., that there exists a connection between distal heat loss and sleepiness. Six healthy sleepers each spent three nights and the following day in the sleep laboratory: an adaptation, a cognitive arousal and a neutral testing day. In the cognitive arousal condition, a visit of a television camera crew took place and subjects were asked to be interviewed. During each of the three 25-min driving simulator tasks per day, the distal-to-proximal gradient and the electroencephalogram are recorded. It is observed from these experimental data that there exists a feedback connection between thermoregulation and sleep. In addition to providing experimental evidence in support of the Gilbert et al. (2004) hypothesis, the authors propose that the nature of the feedback connection is determined by the nature of sleep/wake state (i.e. NREM sleep versus unwanted sleepiness in active subjects). Besides this, an individualized and time-variant model for the linkage between thermoregulation and sleep onset is presented. This compact model feeds on real-time data regarding distal heat loss and sleepiness and contains a physically meaningful parameter that delivers an individual- and time-depending quantification of a well known biological features in the field of thermoregulation: the thermoregulatory error signal T(hypo)(t)-T(set)(t). A validation of these physical/biological features emphasizes the reliability and power of DBM in describing individual differences related to the sleep process.
本研究利用控制系统模型识别技术来检验体温调节与睡眠调节之间的关系。具体而言，基于数据的机制（DBM）建模被用于构建并通过实验验证吉尔伯特等人提出的假设，即远端热量散失与嗜睡之间存在联系。六名健康的睡眠者每人在睡眠实验室度过三个夜晚及随后的一天：一个适应日、一个认知唤醒日和一个中性测试日。在认知唤醒条件下，电视摄制组前来访问，受试者被要求接受采访。在每天的三个25分钟驾驶模拟器任务期间，记录远端到近端的梯度和脑电图。从这些实验数据中观察到体温调节与睡眠之间存在反馈联系。除了提供实验证据支持吉尔伯特等人（2004年）的假设外，作者还提出反馈联系的性质由睡眠/觉醒状态的性质决定（即非快速眼动睡眠与活跃受试者中不必要的嗜睡）。除此之外，还提出了一个关于体温调节与睡眠开始之间联系的个性化且随时间变化的模型。这个紧凑的模型以关于远端热量散失和嗜睡的实时数据为输入，并包含一个具有物理意义的参数，该参数对体温调节领域中一个众所周知的生物学特征进行个体和时间依赖的量化：体温调节误差信号T（hypo）（t）-T（set）（t）。对这些物理/生物学特征的验证强调了DBM在描述与睡眠过程相关的个体差异方面的可靠性和能力。
