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Power Laws and Self-Organized Criticality in Cardiovascular Avalanches
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  • Update Date: 06 May 2025
  • baroreflex
  • cardiovascular avalanches
  • fractals
  • head-up tilt test
  • heart rate variability
  • power laws
  • self-organized criticality
  • vasovagal syncope
  • Zipf’s law
Video Introduction

This video is adapted from 10.3390/fractalfract9040213

Self-organized criticality (SOC) describes natural systems spontaneously tuned at equilibrium yet capable of catastrophic events or avalanches. The cardiovascular system, characterized by homeostasis and vasovagal syncope, is a prime candidate for SOC. Power laws are the cornerstone for demonstrating the presence of SOC. This study aimed to provide evidence of power-law behavior in cardiovascular dynamics. We analyzed beat-by-beat blood pressure and heart rate data from seven healthy subjects in the head-up position over 40 min. Cardiovascular avalanches were quantified by their duration (in beats), and symbolic sequences were identified. Five types of distributions were assessed for power-law behavior: Gutenberg–Richter, classical Zipf, modified Zipf, Zipf of time intervals between avalanches, and Zipf of symbolic sequences. A three-stage approach was used to show power laws: (1) regression coefficient r > 0.95, (2) comparison with randomized data, and (3) Clauset’s statistical test for power law. Numerous avalanches were identified (13.9 ± 0.8 per minute). The classical and modified Zipf distributions met all the criteria (r = 0.99 ± 0.00 and 0.98 ± 0.01, respectively), while the others showed partial agreement, likely due to the limited data duration. These findings reveal that Zipf’s distributions of cardiovascular avalanches strongly support SOC, shedding light on the organization of this complex system. [1][2][3][4]

References
  1. Bak, P. How Nature Works: The Science of Self-Organised Criticality; Copernicus Press: New York, NY, USA, 1996; pp. 1–212.
  2. Fortrat, J.-O.; Ravé, G. Autonomic Nervous System Influences on Cardiovascular Self-Organized Criticality. Entropy 2023, 25, 880. https://doi.org/10.3390/e25060880
  3. Guzzetti S, Borroni E, Garbelli PE, Ceriani E, Della Bella P, Montano N, Cogliati C, Somers VK, Malliani A, Porta A. Symbolic dynamics of heart rate variability: a probe to investigate cardiac autonomic modulation. Circulation. 2005 Jul 26;112(4):465-70. 
  4. Clauset, A.; Shalizi, C.R.; Newman, M.E.J. Power-law distributions in empirical data. SIAM Rev. 2009, 51, 661–703.
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If you have any further questions, please contact Encyclopedia Editorial Office.
Kerkouri, S.; Fortrat, J. Power Laws and Self-Organized Criticality in Cardiovascular Avalanches. Encyclopedia. Available online: https://encyclopedia.pub/video/video_detail/1599 (accessed on 05 December 2025).
Kerkouri S, Fortrat J. Power Laws and Self-Organized Criticality in Cardiovascular Avalanches. Encyclopedia. Available at: https://encyclopedia.pub/video/video_detail/1599. Accessed December 05, 2025.
Kerkouri, Sarah, Jacques-Olivier Fortrat. "Power Laws and Self-Organized Criticality in Cardiovascular Avalanches" Encyclopedia, https://encyclopedia.pub/video/video_detail/1599 (accessed December 05, 2025).
Kerkouri, S., & Fortrat, J. (2025, May 06). Power Laws and Self-Organized Criticality in Cardiovascular Avalanches. In Encyclopedia. https://encyclopedia.pub/video/video_detail/1599
Kerkouri, Sarah and Jacques-Olivier Fortrat. "Power Laws and Self-Organized Criticality in Cardiovascular Avalanches." Encyclopedia. Web. 06 May, 2025.
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