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Modeling napping, post-lunch dip, and other variations in human sleep propensity.

机译:模拟小睡,午餐后的倾角以及人类睡眠倾向的其他变化。

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STUDY OBJECTIVES: To model sleep propensity (SP) as a continuous variable across 24 hours and to model the post-noon nap zone, or post-lunch dip in performance, and the early evening trough in SP. METHODS: The present model is a variant of the 2-process model with 2 major modifications. (1) The circadian threshold process was replaced by sleep drive R, derived from REM sleep propensity, which shows a strong circadian modulation. (2) The model is based on a multiplicative interaction between the 2 input variables S and R. The model parameters S and R were estimated from experimental data. Thus, SP is modeled by multiplicative interaction of 2 sleep drives, S and R, the former of homeostatic, the latter of circadian nature. In short: SP = S x R. RESULTS: Under the condition of normal phase and duration of nighttime sleep, SP across 24 hours displays 4 characteristics, (a) a major peak at nighttime, (b) a secondary increase, which peaks post-noon, (c) a first local minimum at sleep offset in the morning, and (d) a second local minimum in the early evening hours. Model simulations with either delayed or advanced sleep times suggest that the magnitude of the post-noon nap zone depends on the phase of the major sleep period within 24 hours. While the nap zone is attenuated or disappears when night sleep is delayed, SP increases during daytime when night sleep is advanced. In all conditions, the evening local minimum of SP remained stable. CONCLUSIONS: SP can be modeled as a continuous variable, based on the multiplicative interaction of 2 basic sleep drives. The model predictions are in agreement with known variations of SP across 24 hours.
机译:研究目标:将睡眠倾向(SP)建模为24小时内的连续变量,并模拟中午后的午睡区或午餐后的表现下降,以及SP中的傍晚低谷。方法:本模型是2流程模型的变体,具有2个主要修改。 (1)将昼夜节律阈值过程替换为源自REM睡眠倾向的睡眠驱动R,这显示了强烈的昼夜节律调制。 (2)该模型基于两个输入变量S和R之间的乘法相互作用。模型参数S和R是根据实验数据估算的。因此,SP是通过2个睡眠驱动器S和R的乘积交互作用建模的,前者是稳态的,后者是昼夜性的。简而言之:SP = S xR。结果:在正常阶段和夜间睡眠时间的情况下,SP在24小时内显示出4个特征,(a)夜间有一个主要峰值,(b)继发性增加,此峰值在后期-中午,(c)早晨在睡眠时出现第一局部最小值,(d)在傍晚时分出现第二局部最小值。具有延迟或高级睡眠时间的模型仿真表明,午后午睡区的大小取决于24小时内主要睡眠时间的阶段。当延迟夜间睡眠时,午睡区域会减弱或消失,而夜间睡眠会在白天使SP增加。在所有情况下,夜间局部最低SP值均保持稳定。结论:基于2个基本睡眠驱动器的乘法相互作用,可以将SP建模为连续变量。模型预测与24小时内SP的已知变化一致。

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