IEEE Trans Biomed Eng. 2019 Feb;66(2):521-529. doi: 10.1109/TBME.2018.2849823. Epub 2018 Jun 28.
The purpose of this study is to introduce a method in quantifying cross-frequency information transfer to characterize directional couplers between irregular oscillations in complex systems. Importantly, the method should be able to reflect the intrinsic mechanism of interacting oscillations faithfully. Six types of interacting oscillators, including phase-amplitude, amplitude-amplitude, and component-amplitude cross-frequency transfer entropy as well as their inverse transfer entropies, are within our scope in untangling the brain connectivity. Challenges with nonlinear and nonstationary patterns are designed to validate the robustness of the proposed method. We suggest this approach could be effective in identifying driving and responding elements of interacting oscillators across different time scales. Meanwhile, an atlas of interacting oscillators in sleep is constructed. High-frequency amplitude can inversely drive low-frequency phase stronger than the standard phase-amplitude coupling, and the low-frequency amplitude can be the driving force to the high-frequency amplitude in addition to the low-frequency phase. Unlike the standard phase-amplitude coupling, the proposed cross-frequency transfer entropy is applicable to quantify the interactions across phases, amplitudes, or even the components without methodological adjustments. Meanwhile, the exploration of causal relationship enables the identification of the driving force of information flow.
本研究旨在介绍一种量化跨频信息传递的方法，以描述复杂系统中不规则振荡之间的定向耦合器。重要的是，该方法应能够忠实地反映相互作用振荡的内在机制。在解开脑连接的过程中，我们研究了六种相互作用的振荡器，包括相位-幅度、幅度-幅度和分量-幅度的跨频转移熵及其逆转移熵。我们设计了具有非线性和非平稳模式的挑战来验证所提出方法的稳健性。我们建议，这种方法可以有效地识别不同时间尺度上相互作用振荡器的驱动和响应元素。同时，构建了睡眠中相互作用振荡器的图谱。高频幅度可以比标准的相位-幅度耦合更强烈地反向驱动低频相位，并且低频幅度除了低频相位之外还可以成为高频幅度的驱动力。与标准的相位-幅度耦合不同，所提出的跨频转移熵可用于量化跨相位、幅度甚至分量的相互作用，而无需进行方法调整。同时，因果关系的探索可以识别信息流的驱动力。
