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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.

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Summary
This summary is machine-generated.

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.

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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.
  • 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.