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Time-varying coupling functions: Dynamical inference and cause of synchronization transitions
1Faculty of Medicine, Ss Cyril and Methodius University, 50 Divizija 6, Skopje 1000, Macedonia and Department of Physics, Lancaster University, Lancaster, LA1 4YB, United Kingdom.
Time-varying coupling functions, not just strength, drive synchronization transitions in biological systems. This study highlights the importance of analyzing dynamic coupling functions for accurate interaction detection.
Area of Science:
- Complex systems analysis
- Neuroscience and signal processing
Background:
- Interactions are defined by coupling strength, direction, and function.
- Coupling functions introduce complexity, especially when time-varying.
- Synchronization transitions can occur solely due to time-varying coupling.
Purpose of the Study:
- Investigate synchronization transitions driven by time-varying coupling functions.
- Analyze cross-frequency coupling between delta and alpha brain waves.
- Demonstrate the reality of time-varying coupling functions in biological interactions.
Main Methods:
- Analysis of cross-frequency coupling functions from human EEG data.
- Modeling with phase oscillators to demonstrate synchronization transitions.
- Application of dynamical Bayesian inference for inferring time-varying coupling.
Main Results:
- Synchronization transitions were observed due to time-varying coupling functions.
- Human EEG data confirmed the existence of time-varying coupling functions.
- Dynamical Bayesian inference successfully inferred these dynamic coupling functions.
Conclusions:
- Time-varying coupling functions are crucial for understanding biological interactions.
- The form of coupling functions provides an additional dimension for interaction analysis.
- Accurate detection of biological interactions requires considering dynamic coupling functions.
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