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Network physiology reveals relations between network topology and physiological function

Author

Listed:
  • Amir Bashan

    (Bar-Ilan University)

  • Ronny P. Bartsch

    (Brigham and Women's Hospital)

  • Jan. W. Kantelhardt

    (Institute of Physics, Martin-Luther-Universität Halle-Wittenberg)

  • Shlomo Havlin

    (Bar-Ilan University)

  • Plamen Ch. Ivanov

    (Brigham and Women's Hospital
    Boston University
    Institute of Solid State Physics, Bulgarian Academy of Sciences)

Abstract

The human organism is an integrated network where complex physiological systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here we develop a framework to probe interactions among diverse systems, and we identify a physiological network. We find that each physiological state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiological states, the network undergoes topological transitions associated with fast reorganization of physiological interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.

Suggested Citation

  • Amir Bashan & Ronny P. Bartsch & Jan. W. Kantelhardt & Shlomo Havlin & Plamen Ch. Ivanov, 2012. "Network physiology reveals relations between network topology and physiological function," Nature Communications, Nature, vol. 3(1), pages 1-9, January.
    • Handle: RePEc:nat:natcom:v:3:y:2012:i:1:d:10.1038_ncomms1705
    DOI: 10.1038/ncomms1705
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    8. Pyko, Nikita S. & Pyko, Svetlana A. & Markelov, Oleg A. & Karimov, Artur I. & Butusov, Denis N. & Zolotukhin, Yaroslav V. & Uljanitski, Yuri D. & Bogachev, Mikhail I., 2018. "Assessment of cooperativity in complex systems with non-periodical dynamics: Comparison of five mutual information metrics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1054-1072.
    9. Wang, Yan-Jun & Zhu, Yun-Feng & Zhu, Chen-Ping & Wu, Fan & Yang, Hui-Jie & Yan, Yong-Jie & Hu, Chin-Kun, 2019. "Indicator of serious flight delays with the approach of time-delay stability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 363-373.
    10. Pavlov, A.N. & Pavlova, O.N. & Koronovskii, A.A. & Guyo, G.A., 2022. "Extended detrended cross-correlation analysis of nonstationary processes," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    11. Livi, Lorenzo & Maiorino, Enrico & Pinna, Andrea & Sadeghian, Alireza & Rizzi, Antonello & Giuliani, Alessandro, 2016. "Analysis of heat kernel highlights the strongly modular and heat-preserving structure of proteins," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 199-214.
    12. Shekhtman, Louis M. & Danziger, Michael M. & Havlin, Shlomo, 2016. "Recent advances on failure and recovery in networks of networks," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 28-36.
    13. David Jiménez-Grande & S Farokh Atashzar & Eduardo Martinez-Valdes & Deborah Falla, 2021. "Muscle network topology analysis for the classification of chronic neck pain based on EMG biomarkers extracted during walking," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-17, June.
    14. Butusov, Denis N. & Karimov, Artur I. & Pyko, Nikita S. & Pyko, Svetlana A. & Bogachev, Mikhail I., 2018. "Discrete chaotic maps obtained by symmetric integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 955-970.
    15. George Xianzhi Yuan & Huiqi Wang, 2019. "The general dynamic risk assessment for the enterprise by the hologram approach in financial technology," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-48, March.
    16. Yeh, Chien-Hung & Lo, Men-Tzung & Hu, Kun, 2016. "Spurious cross-frequency amplitude–amplitude coupling in nonstationary, nonlinear signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 143-150.
    17. Lucila G Alvarez-Zuzek & Cristian E La Rocca & Federico Vazquez & Lidia A Braunstein, 2016. "Interacting Social Processes on Interconnected Networks," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-17, September.
    18. Liu, Yunxiao & Lin, Youfang & Wang, Jing & Shang, Pengjian, 2018. "Refined generalized multiscale entropy analysis for physiological signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 975-985.
    19. Bumhee Park & Dae-Shik Kim & Hae-Jeong Park, 2014. "Graph Independent Component Analysis Reveals Repertoires of Intrinsic Network Components in the Human Brain," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    20. Havlin, Shlomo & Stanley, H. Eugene & Bashan, Amir & Gao, Jianxi & Kenett, Dror Y., 2015. "Percolation of interdependent network of networks," Chaos, Solitons & Fractals, Elsevier, vol. 72(C), pages 4-19.
    21. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    22. Feng Hu & Lin Ma & Xiu-Xiu Zhan & Yinzuo Zhou & Chuang Liu & Haixing Zhao & Zi-Ke Zhang, 2021. "The aging effect in evolving scientific citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4297-4309, May.

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