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Coherence-incoherence patterns in coupled excitable systems
Igor Franović1, Sebastian Eydam2, Jinjie Zhu3
1Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, Belgrade, 11080, Serbia.
Physics of Life Reviews
|July 21, 2026
Summary
This review explores coherence-incoherence patterns in excitable systems, crucial for understanding biological functions and diseases. It highlights how noise and interactions shape complex patterns in living systems.
Area of Science:
- Complex Systems Biology
- Nonlinear Dynamics
- Network Physiology
Background:
- Excitability is a core dynamic principle in diverse biological systems, from single cells to networks.
- Understanding coherence and incoherence patterns in coupled excitable systems is vital for physiology and pathology.
Purpose of the Study:
- To review theoretical and experimental research on coherence-incoherence patterns in coupled excitable systems.
- To emphasize how excitable dynamics influence pattern formation, distinct from oscillator networks.
- To explore the role of noise and inhibitory interactions in generating characteristic patterns.
Main Methods:
- Theoretical analysis of excitable dynamics, pattern formation, and noise effects (e.g., coherence resonance).
- Review of experimental evidence from electrophysiological and optical imaging techniques.
- Discussion of extensions to heterogeneous and complex biological systems.
Main Results:
- Excitable dynamics generate unique patterns like bumps, patched patterns, and noise-facilitated chimera states.
- Inhibitory interactions and noise play constructive roles in pattern formation.
- Coherence-incoherence patterns are linked to various physiological (sleep, cognition) and pathological (epilepsy, arrhythmia) processes.
Conclusions:
- Coherence-incoherence patterns are a fundamental aspect of biological system dynamics.
- Further research is needed to address challenges in characterizing chaos, experimental validation, and control.
- Developing biologically realistic theoretical frameworks is crucial for advancing the field.
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