Determining the Mathematical Principles of Daily Timekeeping

确定日常计时的数学原理

• 批准号: 1714094
• 负责人: Daniel Forger
• 金额: $ 30万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1714094&HistoricalAwards=false
• 关键词: Determining; Mathematical; Principles; Daily; Timekeeping

Accurate circadian (daily) timekeeping is essential to the survival of almost all organisms. A better understanding of circadian timekeeping is particularly important for the millions of Americans who travel overseas or work on irregular schedules. Recent research on circadian rhythms has discovered the complex biological mechanisms that generate timekeeping in each of the thousands of cells within the suprachiasmatic nuclei (SCN), the region of the brain that acts as the central circadian clock in mammals. Here, detailed mathematical models of neurons within the SCN are developed based on data from many experimental groups. These models are mathematically analyzed and simplified to determine the key properties that govern timekeeping. New mathematical and numerical methods are developed to allow for the study of complex neuronal networks and determine how timekeeping emerges from the collective behavior of coupled oscillators. These results should be applicable to many biological systems. Circadian clocks are studied as a model system in cellular biology and electrophysiology to determine design principles that can be applied to other physiological systems, particularly those consisting of coupled oscillators. Mathematical models of electrophysiology will follow the Hodgkin-Huxley formalism. Mathematical models of cellular biology will follow the mass action formalism. Recent experimental research on the mechanisms of circadian timekeeping in individual cells will be incorporated into these mathematical models. Understanding the dynamics controlling circadian timekeeping will be extremely helpful for the field of circadian rhythms, which seeks to determine how a large number of proteins, ion channels and neurons work together to form the body's central clock. The general mathematical work in this proposal includes studying the attractors of biochemical feedback loops through iterative maps, a population density method for efficiently simulating large dimensional neuronal oscillators, and a new ansatz that can reduce a model of a large number of coupled oscillators to a two dimensional model. These mathematical approaches will be tested using our models of circadian timekeeping.

精确的昼夜节律（每日）计时对几乎所有生物体的生存至关重要。更好地了解昼夜节律计时对数百万海外旅行或不规律工作的美国人来说尤为重要。最近对昼夜节律的研究发现了在视交叉上核（SCN）内的数千个细胞中的每一个中产生计时的复杂生物机制，视交叉上核是哺乳动物中充当中央昼夜节律钟的大脑区域。在这里，详细的数学模型的SCN内的神经元开发的基础上，从许多实验组的数据。这些模型经过数学分析和简化，以确定控制计时的关键属性。新的数学和数值方法的发展，使复杂的神经网络的研究，并确定如何计时出现从耦合振荡器的集体行为。这些结果应该适用于许多生物系统。生物钟作为细胞生物学和电生理学的模型系统进行研究，以确定可应用于其他生理系统的设计原则，特别是那些由耦合振荡器组成的系统。电生理学的数学模型将遵循Hodgkin-Huxley形式主义。细胞生物学的数学模型将遵循质量作用形式主义。最近的实验研究的机制，昼夜节律的时间保持在个别细胞将被纳入这些数学模型。了解控制昼夜节律计时的动力学将对昼夜节律领域非常有帮助，该领域旨在确定大量蛋白质，离子通道和神经元如何共同形成身体的中央时钟。在这个建议中的一般数学工作包括研究吸引子的生化反馈回路通过迭代映射，人口密度方法有效地模拟大尺寸的神经元振荡器，和一个新的ananterior，可以减少一个模型的大量耦合振荡器的二维模型。这些数学方法将使用我们的昼夜节律计时模型进行测试。

项目成果

A method for characterizing daily physiology from widely used wearables

• DOI: 10.1016/j.crmeth.2021.100058
• 发表时间: 2021-08-23
• 期刊: CELL REPORTS METHODS
• 作者: Bowman, Clark;Huang, Yitong;Forger, Daniel B.
• 通讯作者: Forger, Daniel B.

Phase Estimation from Noisy Data with Gaps

根据带间隙的噪声数据进行相位估计

• DOI: 10.1109/sampta45681.2019.9030828
• 发表时间: 2019
• 期刊: SAMPTA
• 作者: Huang, Yitong Bowman

Learning dynamics from large biological data sets: Machine learning meets systems biology

• DOI: 10.1016/j.coisb.2020.07.009
• 发表时间: 2020-08-01
• 期刊: CURRENT OPINION IN SYSTEMS BIOLOGY
• 影响因子: 3.7
• 作者: Gilpin, William;Huang, Yitong;Forger, Daniel B.
• 通讯作者: Forger, Daniel B.

Predicting circadian phase across populations: a comparison of mathematical models and wearable devices

• DOI: 10.1093/sleep/zsab126
• 发表时间: 2021-10-01
• 期刊: SLEEP
• 影响因子: 5.6
• 作者: Huang, Yitong;Mayer, Caleb;Forger, Daniel B.
• 通讯作者: Forger, Daniel B.

Macroscopic Models for Human Circadian Rhythms

• DOI: 10.1177/0748730419878298
• 发表时间: 2019-10-16
• 期刊: JOURNAL OF BIOLOGICAL RHYTHMS
• 影响因子: 3.5
• 作者: Hannay, Kevin M.;Booth, Victoria;Forger, Daniel B.
• 通讯作者: Forger, Daniel B.