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Decision making in noisy bistable systems with time-dependent asymmetry
1Department of Mathematics, Imperial College London, South Kensington Campus, SW7 2AZ London, United Kingdom.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 16, 2013
Summary
Time-dependent parameters significantly impact decision-making in bistable systems. Slow passage through critical regions enhances specific outcomes, especially when asymmetry peaks near the critical point to mitigate noise effects.
Area of Science:
- * Biophysics and Dynamical Systems
- * Theoretical Biology and Genetic Circuits
Background:
- * Bistable systems exhibit switch-like behavior, crucial in biological processes like genetic switches.
- * Previous studies explored speed-dependent cellular decision-making in genetic circuits.
- * Time-dependent parameters introduce complexities not fully addressed in prior research.
Purpose of the Study:
- * To analytically investigate the influence of time-dependent parameters on decision-making in bistable systems.
- * To extend the understanding of speed-dependent cellular decision-making mechanisms.
- * To analyze attractor selection under time-varying asymmetry and control parameters.
Main Methods:
- * Analytical treatment of a supercritical pitchfork bifurcation model.
- * Incorporation of time-dependent asymmetry and control parameters.
- * Examination of system behavior during slow passage through the critical region.
Main Results:
- * Transient asymmetries and fluctuations significantly increase the probability of specific decision outcomes during slow passage.
- * The timing of maximum asymmetry relative to the critical region impacts attractor selection.
- * Optimal timing of peak asymmetry can compensate for noise and retain memory of transient states.
Conclusions:
- * Time-dependent parameters are critical for understanding decision-making in biological systems.
- * Strategic manipulation of asymmetry timing can control system outcomes and memory.
- * The findings offer insights into noise resilience and information processing in genetic circuits.
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