Sorrentino Pierpaolo, Ambrosanio Michele, Rucco Rosaria, Cabral Joana, Gollo Leonardo L, Breakspear Michael, Baselice Fabio
Systems Neuroscience Institute, Marseille, France.
Hermitage Capodimonte Hospital, Naples, Italy.
Front Neurosci. 2022 Apr 25;16:846623. doi: 10.3389/fnins.2022.846623. eCollection 2022.
The current paper proposes a method to estimate phase to phase cross-frequency coupling between brain areas, applied to broadband signals, without any a priori hypothesis about the frequency of the synchronized components. N:m synchronization is the only form of cross-frequency synchronization that allows the exchange of information at the time resolution of the faster signal, hence likely to play a fundamental role in large-scale coordination of brain activity. The proposed method, named cross-frequency phase linearity measurement (CF-PLM), builds and expands upon the phase linearity measurement, an iso-frequency connectivity metrics previously published by our group. The main idea lies in using the shape of the interferometric spectrum of the two analyzed signals in order to estimate the strength of cross-frequency coupling. We first provide a theoretical explanation of the metrics. Then, we test the proposed metric on simulated data from coupled oscillators synchronized in iso- and cross-frequency (using both Rössler and Kuramoto oscillator models), and subsequently apply it on real data from brain activity. Results show that the method is useful to estimate n:m synchronization, based solely on the phase of the signals (independently of the amplitude), and no a-priori hypothesis is available about the expected frequencies.
本文提出了一种估计脑区之间相位到相位交叉频率耦合的方法，该方法适用于宽带信号，且无需对同步成分的频率做任何先验假设。N:m同步是交叉频率同步的唯一形式，它允许在较快信号的时间分辨率下进行信息交换，因此可能在大脑活动的大规模协调中发挥重要作用。所提出的方法名为交叉频率相位线性测量（CF-PLM），它建立并扩展了相位线性测量，这是我们小组之前发表的一种同频连通性指标。其主要思想在于利用两个分析信号的干涉频谱形状来估计交叉频率耦合的强度。我们首先对该指标进行理论解释。然后，我们在同频和交叉频率同步的耦合振荡器的模拟数据上测试所提出的指标（使用Rössler和Kuramoto振荡器模型），随后将其应用于大脑活动的真实数据。结果表明，该方法仅基于信号的相位（与幅度无关）就可用于估计n:m同步，并且无需对预期频率做先验假设。
