Cross-Frequency Transfer Entropy Characterize Coupling of Interacting Nonlinear Oscillators in Complex Systems

Area of Science:

• Neuroscience
• Complex Systems Analysis
• Information Theory

Background:

• Understanding brain connectivity relies on quantifying interactions between neural oscillations.
• Existing methods like phase-amplitude coupling have limitations in capturing complex, directional information transfer.
• Neural oscillations exhibit diverse patterns, including phase-amplitude, amplitude-amplitude, and component-amplitude couplings, necessitating advanced analytical tools.

Purpose of the Study:

• To introduce a robust method for quantifying cross-frequency information transfer between interacting oscillations.
• To characterize directional coupling mechanisms in complex systems, reflecting intrinsic interaction dynamics.
• To untangle brain connectivity by analyzing various types of cross-frequency transfer entropies.

Main Methods:

• Development and application of a cross-frequency transfer entropy quantification method.
• Validation of the method using simulated nonlinear and nonstationary oscillatory patterns.
• Construction of an atlas of interacting oscillators during sleep states.

Main Results:

• The proposed method accurately quantifies information transfer across different oscillatory components (phase, amplitude).
• Demonstrated that high-frequency amplitude can inversely drive low-frequency phase, and low-frequency amplitude can drive high-frequency amplitude.
• Identified driving and responding elements of interacting oscillators across diverse time scales, revealing causal relationships.

Conclusions:

• The novel cross-frequency transfer entropy method offers a versatile tool for analyzing complex system interactions beyond standard phase-amplitude coupling.
• This approach provides a more comprehensive understanding of brain connectivity and neural oscillation dynamics.
• The method's ability to explore causal relationships facilitates the identification of information flow drivers.