The human circadian pacemaker entrains to the 24-h day, but interindividual differences in properties of the pacemaker, such as intrinsic period, affect chronotype and mediate responses to challenges to the circadian system, such as shift work and jet lag, and the efficacy of therapeutic interventions such as light therapy. Robust characterization of circadian properties requires desynchronization of the circadian system from the rest-activity cycle, and these forced desynchrony protocols are very time and resource intensive. However, circadian protocols designed to derive the relationship between light intensity and phase shift, which is inherently affected by intrinsic period, may be applied more broadly. To exploit this relationship, we applied a mathematical model of the human circadian pacemaker with a Markov-Chain Monte Carlo parameter estimation algorithm to estimate the representative group intrinsic period for a group of participants using their collective illuminance-response curve data. We first validated this methodology using simulated illuminance-response curve data in which the intrinsic period was known. Over a physiological range of intrinsic periods, this method accurately estimated the representative intrinsic period of the group. We also applied the method to previously published experimental data describing the illuminance-response curve for a group of healthy adult participants. We estimated the study participants' representative group intrinsic period to be 24.26 and 24.27 h using uniform and normal priors, respectively, consistent with estimates of the average intrinsic period of healthy adults determined using forced desynchrony protocols. Our results establish an approach to estimate a population's representative intrinsic period from illuminance-response curve data, thereby facilitating the characterization of intrinsic period across a broader range of participant populations than could be studied using forced desynchrony protocols. Future applications of this approach may improve the understanding of demographic differences in the intrinsic circadian period.

中文翻译：

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从照度-响应曲线数据估计代表组内在昼夜周期。

人类昼夜节律起搏器会持续 24 小时，但起搏器特性（如内在周期）的个体间差异会影响计时型并调节对昼夜节律系统挑战（如轮班工作和时差）的反应，以及治疗干预，例如光疗法。昼夜节律特性的稳健表征需要使昼夜节律系统与休息活动周期不同步，并且这些强制不同步协议非常耗费时间和资源。然而，旨在推导出光强度和相移之间关系的昼夜节律协议，其本质上受固有周期的影响，可以更广泛地应用。为了利用这种关系，我们应用了人类昼夜节律起搏器的数学模型和马尔科夫链蒙特卡罗参数估计算法，使用他们的集体照度-响应曲线数据估计一组参与者的代表性组固有周期。我们首先使用已知固有周期的模拟照度响应曲线数据验证了这种方法。在固有周期的生理范围内，该方法准确地估计了该组的代表性固有周期。我们还将该方法应用于先前发布的描述一组健康成人参与者的照度-响应曲线的实验数据。我们分别使用统一和正常先验估计研究参与者的代表性群体内在周期为 24.26 和 24.27 小时，与使用强制不同步协议确定的健康成年人平均内在周期的估计一致。我们的结果建立了一种从照度-响应曲线数据估计人群的代表性内在周期的方法，从而促进了比使用强制不同步协议研究的更广泛参与者群体的内在周期的表征。这种方法的未来应用可能会提高对内在昼夜节律期间人口统计学差异的理解。从而促进在更广泛的参与者群体中表征内在周期，而不是使用强制不同步协议进行研究。这种方法的未来应用可能会提高对内在昼夜节律期间人口统计学差异的理解。从而促进在更广泛的参与者群体中表征内在周期，而不是使用强制不同步协议进行研究。这种方法的未来应用可能会提高对内在昼夜节律期间人口统计学差异的理解。