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Chaotic patterns in a coupled oscillator-excitator biochemical cell system.

Igor Schreiber1, Pavel Hasal, Milos Marek

  • 1Department of Chemical Engineering and Center for Nonlinear Dynamics of Chemical and Biological Systems, Institute of Chemical Technology in Prague, 166 28 Prague 6, Czech Republic.

Chaos (Woodbury, N.Y.)
|June 5, 2003
PubMed
Summary

This study explores how two biochemical cells interact when connected through mass transfer. One cell is excitable, and the other can be oscillatory or stable. The researchers found that when these cells interact, they can produce complex behaviors like chaos and oscillations. The results suggest that simple changes in parameters like coupling strength and receptor activation can lead to diverse dynamical patterns. These findings may help explain how cells communicate and organize their activity in real biological systems.

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Area of Science:

  • Nonlinear dynamics in biochemical systems
  • Cell signaling and calcium ion regulation
  • Mathematical modeling of biological oscillations

Background:

The study of dynamic interactions between biochemical cells is a growing field. Prior research has shown that calcium ion regulation can lead to oscillatory behavior. However, the effects of coupling cells with different dynamic constraints remain unclear. This gap motivated the exploration of how excitable and oscillatory cells interact. No prior work had resolved the specific patterns that emerge from such interactions. The ICC model has been used to describe cytosolic calcium dynamics. But its behavior under coupling remains understudied. This paper aims to address that gap. The findings may contribute to understanding complex cellular communication.

Purpose Of The Study:

The goal was to analyze the dynamics of two coupled biochemical cells. One cell was set as excitable, while the other could be oscillatory or a stable focus. The researchers wanted to explore how these interactions change with coupling strength and receptor activation. They aimed to identify patterns like oscillations or chaos. The ICC model was used to simulate calcium ion behavior. The study focused on transitions between different dynamical states. The authors sought to determine if chaos could emerge from these interactions. Understanding these dynamics could clarify how cells communicate under varying conditions.

Keywords:
chaotic oscillationsICC modelbiochemical cell couplingcalcium ion dynamics

Frequently Asked Questions

Compound oscillations arranged as period adding sequences alternate with chaotic windows. The transition to chaos involves period doubling and orbit folding.

The ICC model simulates calcium ion dynamics in the cytosol of each cell, allowing researchers to track oscillatory and chaotic behavior.

It determines whether a cell behaves as an oscillator, excitor, or stable focus, influencing the overall dynamics of the coupled system.

It is associated with the transition to chaos in the focus-excitator interaction, indicating a specific bifurcation mechanism.

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Main Methods:

The researchers used a computational model based on the ICC framework. Each cell simulated calcium ion dynamics in the cytosol. One cell was constrained to be excitable. The other cell's dynamics were adjusted by varying receptor activation. The two cells interacted via mass transfer. Parameters included coupling strength and receptor activation levels. The system's behavior was analyzed as these parameters changed. The authors tracked transitions between oscillatory and chaotic states.

Main Results:

The excitator-excitator interaction did not produce oscillations. The oscillator-excitator setup showed phase-locked and quasiperiodic behavior. Intermediate coupling strength led to chaotic patterns via torus breaking. The focus-excitator interaction produced compound oscillations. Period adding sequences alternated with chaotic windows. Period doubling and orbit folding marked the transition to chaos. A Shilnikov homoclinic orbit was associated with the chaotic regime. These findings suggest complex interactions can arise from simple coupling.

Conclusions:

The authors found that coupling excitable and oscillatory cells leads to complex dynamics. Chaos emerged in the oscillator-excitator setup with intermediate coupling. The focus-excitator interaction showed period adding and chaotic windows. These patterns align with known bifurcations like torus breaking and homoclinic orbits. The study confirms that simple parameter changes can generate diverse behaviors. The authors suggest that these findings may help explain self-organized oscillations in biological systems. They emphasize the role of coupling strength and receptor activation in shaping dynamics. The results highlight the need for further study on how such interactions occur in real cells.

Intermediate coupling strength generates chaos via torus breaking, while low or high coupling leads to periodic or quasiperiodic behavior.

The focus-excitator range may support spontaneous oscillations, suggesting a mechanism for self-organized behavior in biological systems.