Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
Elife. 2021 Mar 8;10:e62073. doi: 10.7554/eLife.62073.
Although brain temperature has neurobiological and clinical importance, it remains unclear which factors contribute to its daily dynamics and to what extent. Using a statistical approach, we previously demonstrated that hourly brain temperature values co-varied strongly with time spent awake (Hoekstra et al., 2019). Here we develop and make available a mathematical tool to simulate and predict cortical temperature in mice based on a 4-s sleep-wake sequence. Our model estimated cortical temperature with remarkable precision and accounted for 91% of the variance based on three factors: sleep-wake sequence, time-of-day ('circadian'), and a novel 'prior wake prevalence' factor, contributing with 74%, 9%, and 43%, respectively (including shared variance). We applied these optimized parameters to an independent cohort of mice and predicted cortical temperature with similar accuracy. This model confirms the profound influence of sleep-wake state on brain temperature, and can be harnessed to differentiate between thermoregulatory and sleep-wake-driven effects in experiments affecting both.
虽然大脑温度具有神经生物学和临床意义，但仍不清楚哪些因素导致其日常动态变化，以及变化的程度。我们之前使用统计方法证明，每小时的大脑温度值与清醒时间强烈相关（Hoekstra 等人，2019 年）。在这里，我们开发并提供了一种数学工具，可根据 4 小时的睡眠-觉醒序列模拟和预测小鼠的皮质温度。我们的模型以惊人的精度估计皮质温度，基于三个因素解释了 91%的变异性：睡眠-觉醒序列、时间（“昼夜节律”）和一个新的“先前觉醒流行”因素，分别贡献了 74%、9%和 43%（包括共享方差）。我们将这些优化参数应用于另一组独立的小鼠，并以类似的精度预测皮质温度。该模型证实了睡眠-觉醒状态对大脑温度的深远影响，并可用于区分影响两者的实验中的体温调节和睡眠-觉醒驱动效应。
