Data-driven mathematical modeling of sleep consolidation in early childhood

被引:0
|
作者
Athanasouli, Christina [1 ,2 ]
Stowe, Shelby R. [3 ]
LeBourgeois, Monique K. [4 ]
Booth, Victoria [1 ,5 ]
Behn, Cecilia G. Diniz [3 ,6 ]
机构
[1] Univ Michigan, Dept Math, 530 Church St, Ann Arbor, MI 48109 USA
[2] Georgia Inst Technol, Sch Math, 686 Cherry St NW, Atlanta, GA 30332 USA
[3] Colorado Sch Mines, Dept Appl Math & Stat, 1500 Illinois St, Golden, CO 80401 USA
[4] Univ Colorado, Dept Integrat Physiol, 354 UCB, Boulder, CO 80309 USA
[5] Univ Michigan, Dept Anesthesiol, 1500 E Med Ctr Dr, Ann Arbor, MI 48109 USA
[6] Univ Colorado, Dept Pediat, Anschutz Med Campus,13001 E 17th PL, Aurora, CO 80045 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
Early childhood development; Homeostatic sleep drive; Bifurcation analysis; Data-driven modeling; Sleep-wake regulation; CIRCADIAN PACEMAKER; LIGHT; ENTRAINMENT; MELATONIN; DYNAMICS; DURATION; TIMES; DISORDERS; PATTERNS; CHILDREN;
D O I
10.1016/j.jtbi.2024.111892
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Across early childhood development, sleep behavior transitions from a biphasic pattern (a daytime nap and nighttime sleep) to a monophasic pattern (only nighttime sleep). The transition to consolidated nighttime sleep, which occurs in most children between 2- and 5-years-old, is a major developmental milestone and reflects interactions between the developing homeostatic sleep drive and circadian system. Using a physiologically-based mathematical model of the sleep-wake regulatory network constrained by observational and experimental data from preschool-aged participants, we analyze how developmentally-mediated changes in the homeostatic sleep drive may contribute to the transition from napping to non-napping sleep patterns. We establish baseline behavior by identifying parameter sets that model typical 2-year-old napping behavior and 5-year-old non-napping behavior. Then we vary six model parameters associated with the dynamics of and sensitivity to the homeostatic sleep drive between the 2-year-old and 5-year-old parameter values to induce the transition from biphasic to monophasic sleep. We analyze the individual contributions of these parameters to sleep patterning by independently varying their age-dependent developmental trajectories. Parameters vary according to distinct evolution curves and produce bifurcation sequences representing various ages of transition onset, transition durations, and transitional sleep patterns. Finally, we consider the ability of napping and non-napping light schedules to reinforce napping or promote a transition to consolidated sleep, respectively. These modeling results provide insight into the role of the homeostatic sleep drive in promoting interindividual variability in developmentally-mediated transitions in sleep behavior and lay foundations for the identification of light- or behavior-based interventions that promote healthy sleep consolidation in early childhood.
引用
收藏
页数:17
相关论文
共 50 条
  • [21] On the Data-Driven Modeling of Reactive Extrusion
    Ibanez, Ruben
    Casteran, Fanny
    Argerich, Clara
    Ghnatios, Chady
    Hascoet, Nicolas
    Ammar, Amine
    Cassagnau, Philippe
    Chinesta, Francisco
    FLUIDS, 2020, 5 (02)
  • [22] Data-driven modeling and control of droughts
    Zaniolo, Marta
    Giuliani, Matteo
    Castelletti, Andrea
    IFAC PAPERSONLINE, 2019, 52 (23): : 54 - 60
  • [23] Data-driven modeling for scoliosis prediction
    Deng, Liming
    Li, Han-Xiong
    Hu, Yong
    Cheung, Jason P. Y.
    Jin, Richu
    Luk, Keith D. K.
    Cheung, Prudence W. H.
    2016 INTERNATIONAL CONFERENCE ON SYSTEM SCIENCE AND ENGINEERING (ICSSE), 2016,
  • [24] Data-driven modeling of power networks
    Safaee, Bita
    Gugercin, Serkan
    2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2021, : 4236 - 4241
  • [25] Data-driven Modeling of Airlines Pricing
    Lantseva, Anastasia
    Mukhina, Ksenia
    Nikishova, Anna
    Ivanov, Sergey
    Knyazkov, Konstantin
    4TH INTERNATIONAL YOUNG SCIENTIST CONFERENCE ON COMPUTATIONAL SCIENCE, 2015, 66 : 267 - 276
  • [26] Data driven modeling in mathematical biology
    Demongeot, Jacques
    Magal, Pierre
    FRONTIERS IN APPLIED MATHEMATICS AND STATISTICS, 2023, 9
  • [27] Data-Driven Order Fulfillment Consolidation for Online Grocery Retailing
    Wang, Yang
    Wang, Tong
    Wang, Xiaoqing
    Deng, Yuming
    Cao, Lei
    INFORMS JOURNAL ON APPLIED ANALYTICS, 2024, 54 (03):
  • [28] A physics-informed data-driven approach for consolidation analysis
    Zhang, Pin
    Yin, Zhen-Yu
    Sheil, Brian
    GEOTECHNIQUE, 2022, 74 (07): : 620 - 631
  • [29] Special issue: Data-driven mathematical sciences and econophysics
    Tanaka-Yamawaki, Mieko
    EVOLUTIONARY AND INSTITUTIONAL ECONOMICS REVIEW, 2024, 21 (02) : 199 - 201
  • [30] Characterization of multicellular breast tumor spheroids using image data-driven biophysical mathematical modeling
    Haley J. Bowers
    Emily E. Fannin
    Alexandra Thomas
    Jared A. Weis
    Scientific Reports, 10