Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement

• Published in: Frontiers in neuroscience Vol. 16; p. 846623
• Main Authors: Sorrentino, Pierpaolo, Ambrosanio, Michele, Rucco, Rosaria, Cabral, Joana, Gollo, Leonardo L, Breakspear, Michael, Baselice, Fabio
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers 25.04.2022; Frontiers Media S.A
• Subjects: brain functional connectivity; brain network; Cognitive science; cross frequency coupling; Life Sciences; Neurons and Cognition; Neuroscience; phase coupling; phase linearity measurement; PLM; PLM; phase coupling; brain functional connectivity; cross frequency coupling; phase linearity measurement; brain network
• ISSN: 1662-4548; 1662-453X; 1662-453X
• DOI: 10.3389/fnins.2022.846623

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.