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Criticality Analysis: Bio-Inspired Nonlinear Data Representation.

Entropy (Basel, Switzerland)ยท2023
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Controlled bio-inspired self-organised criticality.

Tjeerd V Olde Scheper1

  • 1School of Engineering, Computing and Mathematics, Oxford Brookes University, Wheatley Campus, Oxford, United Kingdom.

Plos One
|January 24, 2022
PubMed
Summary

Self-Organised Criticality (SOC) in biological systems, generated by Rate Control of Chaos (RCC), explains how local control creates global stability. This mechanism may underlie protein production and homeostasis.

Area of Science:

  • Complex biological systems
  • Nonlinear dynamics
  • Systems biology

Background:

  • Traditional reduced models struggle with the complexity of biological feedback mechanisms.
  • Self-Organised Criticality (SOC) describes systems exhibiting critical dynamics and power-law relations.
  • Understanding localized control for global stability in biology is a significant challenge.

Purpose of the Study:

  • To investigate Self-Organised Criticality (SOC) as a mechanism for biological control.
  • To explore the Rate Control of Chaos (RCC) method for generating SOC in biological systems.
  • To demonstrate how localized control can achieve global stable states in biological networks.

Main Methods:

  • Utilizing the bio-inspired Rate Control of Chaos (RCC) method to generate SOC.

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  • Modeling systems with local interactions and nonlinear perturbations.
  • Analyzing the emergent properties of connected RCC-controlled oscillators.

    • Main Results:

    • RCC successfully generates SOC, operating at the edge of chaos.
    • Connected RCC oscillators maintain global multi-stable states and exhibit power-law relations.
    • Perturbation-amplitude relationships show exponential and power-law correlations, mimicking protein control.

    Conclusions:

    • Controlled SOC via RCC offers a robust mechanism for biological regulation, including homeostasis.
    • This approach enhances understanding of distributed biological control systems.
    • Localized control mechanisms are crucial for achieving global stability in complex biological networks.