Mathematical models have a long and influential history in the study of human circadian rhythms. Accurate predictive models for the human circadian light response have been used to study the impact of a host of light exposures on the circadian system. However, generally, these models do not account for the physiological basis of these rhythms. We illustrate a new paradigm for deriving models of the human circadian light response. Beginning from a high-dimensional model of the circadian neural network, we systematically derive low-dimensional models using an approach motivated by experimental measurements of circadian neurons. This systematic reduction allows for the variables and parameters of the derived model to be interpreted in a physiological context. We fit and validate the resulting models to a library of experimental measurements. Finally, we compare model predictions for experimental measurements of light levels and discuss the differences between our model's predictions and previous models. Our modeling paradigm allows for the integration of experimental measurements across the single-cell, tissue, and behavioral scales, thereby enabling the development of accurate low-dimensional models for human circadian rhythms.

中文翻译：

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人类昼夜节律的宏观模型。

在人类昼夜节律的研究中，数学模型具有悠久的历史。人体昼夜节律反应的精确预测模型已用于研究大量光照对昼夜节律系统的影响。但是，通常，这些模型不能解释这些节律的生理基础。我们举例说明了人类昼夜节律响应模型的新范式。从生物钟神经网络的高维模型开始，我们使用由生物钟神经元的实验测量所激发的方法来系统地导出低维模型。这种系统的简化使派生模型的变量和参数可以在生理环境中进行解释。我们将结果模型拟合并验证到实验测量库中。最后，我们比较模型预测值以进行光水平的实验测量，并讨论模型预测值与先前模型之间的差异。我们的建模范例可整合跨单细胞，组织和行为尺度的实验测量结果，从而能够开发出精确的低维人体昼夜节律模型。