Analysis of circadian rhythm synchronization under the influence of pain

Authors

DOI:

https://doi.org/10.5902/2179460X73631

Keywords:

Synchronization, Biological rhythms, Pain, PIM model

Abstract

The synchronization of biological rhythms is of fundamental importance for health. The influence of pain on the functioning of vital functions and its effects on the synchronization of biological rhythms in human beings have been explored clinically for a long time. On the other hand, the modeling of this phenomenon can add features that are still unexplored. This bias fits the present contribution: to analyze the existence of synchronization of the circadian rhythm under the influence of external factors such as pain. To that end, we propose and investigate a model of coupled and phase oscillators that describes the sleep-wake, body temperature, and pain rhythms. The simplicity of the modeling allows one to obtain the synchronized solutions analytically as well as derive restrictions in terms of the parameters that guarantee their synchronization. The results obtained by analyzing the proposed model are accompanied by numerical simulations.

Downloads

Download data is not yet available.

Author Biographies

Adriano De Cezaro, Federal University of Rio Grande

PhD in Mathematics, Professor at the Institute of Mathematics, Statistics and Physics.

Fabiana Travessini De Cezaro, Federal University of Rio Grande

PhD in Mathematics, Professor at the Institute of Mathematics, Statistics and Physics.

Stefânia da Silveira Glaeser, Instituto Federal Sul-rio-grandense

PhD in Computational Modeling.

References

Bard, E.; Youngmin, P.; Dan, W.; (2019). Recent advances in coupled oscillator theory. Phil. Trans. R. Soc. A., 337, 2160, 1 – 16. https://doi.org/10.1098/rsta.2019.0092. DOI: https://doi.org/10.1098/rsta.2019.0092

Bick, C.; Goodfellow, M.; Laing, C. R.; Martens, E. A.; (2020). Understanding the dynamics of biological and neural oscillator networks through mean-field reductions: a review. J. Math. Neurosc. 10, 9. https://doi.org/10.1186/s13408-020-00086-9. DOI: https://doi.org/10.1186/s13408-020-00086-9

Bumgarner, J. R., Walker, W. H., Nelson, R. J. (2021). Circadian rhythms and pain. Neuroscience Biobehavioral Reviews, 129, 296–306. doi: 10.1016/j.neubiorev.2021.08.004. DOI: https://doi.org/10.1016/j.neubiorev.2021.08.004

Cai, Z.; Zheng, Z.; Xu, C.; (2022). Exact dynamics of phase transitions in oscillator populations with nonlinear coupling.

Communications in Nonlinear Science and Numerical Simulation, V. 107, P. 106–129. DOI: https://doi.org/10.1016/j.cnsns.2021.106129. DOI: https://doi.org/10.1016/j.cnsns.2021.106129

Contessa, M. N.; De Cezaro, A.; (2017). Derivadas fracionárias na modelagem do ritmo circadiano. Scientia Plena, 13, 4, 1–11. https://doi.org/10.14808/sci.plena.2017.049909. DOI: https://doi.org/10.14808/sci.plena.2017.049909

Dörfler, F.; Bullo, F.; (2014). Synchronization in complex networks of phase oscillators: A survey. Automatica, 50, 6, 1539–1556. DOI: https://doi.org/10.1016/j.automatica.2014.04.012. DOI: https://doi.org/10.1016/j.automatica.2014.04.012

Glaeser, S. S.; Santos, A. T.; De Cezaro, A.; Machado, C. M. d. S., Adamatti, D. F.; (2018). Modeling of circadian rhythm under influence of pain: an approach based on multi-agent simulation. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 7, 2, 17–25. DOI: https://doi.org/10.14201/ADCAIJ2018721725

Glaeser, S. S.; De Cezaro, F.; De Cezaro, A.; (2023). Synchronization of the circadian rhythms with memory: A simple fractional- order dynamical model based on two coupled oscillators. Trends in Comput Appl Mathematics, 24, 2, 1–15. DOI: https://doi.org/10.5540/tcam.2023.024.02.00245. DOI: https://doi.org/10.5540/tcam.2023.024.02.00245

Journal of Biological Rhythms, 22, 2, 91–102. DOI: https://doi.org/10.1177/0748730407299200.

Klerman, E. B.; Hilaire, M. S.; (2007). On mathematical modeling of circadian rhythms, performance, and alertness. DOI: https://doi.org/10.1177/0748730407299200

Kuramoto, Y.; (1984). Chemical Oscillations, Waves, and Turbulence. Vol. 19, Springer, Berlin, https://doi.org/10.1007/978-3-642-69689-3. DOI: https://doi.org/10.1007/978-3-642-69689-3

Neves, A. R.; Albuquerque, T.; Quintela, T.; Costa, D.; (2022). Circadian rhythm and disease: Relationship, new insights, and future perspectives. Journal of Cellular Physiology, 237, 8, 3239–3256. DOI: https://doi.org/10.1002/jcp.30815. DOI: https://doi.org/10.1002/jcp.30815

Palada, V.; Gilron, I.; Canlon, B.; Svensson, C. I.; Kalso, E.; (2020). The circadian clock at the intercept of sleep and pain. PAIN, 161, 5, 894–900. DOI: 10.1097/j.pain.0000000000001786. DOI: https://doi.org/10.1097/j.pain.0000000000001786

Pikovisky A, K. J.; Rosemblum M.; (2001). Synchronization: A Universal Concept in Nonlinear Sciences, 1º edn. Cambridge University Press. ISBN: 052153352X. DOI: https://doi.org/10.1017/CBO9780511755743

Rodrigues, F. A.; Peron, T. K. D.; Ji, P.; Kurths, J.; (2016). The kuramoto model in complex networks. Physics Reports, 610, 26, 1 – 98. https://doi.org/10.1016/j.physrep.2015.10.008. DOI: https://doi.org/10.1016/j.physrep.2015.10.008

Downloads

Published

2024-10-18

How to Cite

Cezaro, A. D., Cezaro, F. T. D., & Glaeser, S. da S. (2024). Analysis of circadian rhythm synchronization under the influence of pain. Ciência E Natura, 46, e73631. https://doi.org/10.5902/2179460X73631