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

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...

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Autores principales: Sorrentino, Pierpaolo, Ambrosanio, Michele, Rucco, Rosaria, Cabral, Joana, Gollo, Leonardo L., Breakspear, Michael, Baselice, Fabio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9083011/
https://www.ncbi.nlm.nih.gov/pubmed/35546895
http://dx.doi.org/10.3389/fnins.2022.846623
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author Sorrentino, Pierpaolo
Ambrosanio, Michele
Rucco, Rosaria
Cabral, Joana
Gollo, Leonardo L.
Breakspear, Michael
Baselice, Fabio
author_facet Sorrentino, Pierpaolo
Ambrosanio, Michele
Rucco, Rosaria
Cabral, Joana
Gollo, Leonardo L.
Breakspear, Michael
Baselice, Fabio
author_sort Sorrentino, Pierpaolo
collection PubMed
description 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.
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spelling pubmed-90830112022-05-10 Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement Sorrentino, Pierpaolo Ambrosanio, Michele Rucco, Rosaria Cabral, Joana Gollo, Leonardo L. Breakspear, Michael Baselice, Fabio Front Neurosci Neuroscience 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. Frontiers Media S.A. 2022-04-25 /pmc/articles/PMC9083011/ /pubmed/35546895 http://dx.doi.org/10.3389/fnins.2022.846623 Text en Copyright © 2022 Sorrentino, Ambrosanio, Rucco, Cabral, Gollo, Breakspear and Baselice. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Sorrentino, Pierpaolo
Ambrosanio, Michele
Rucco, Rosaria
Cabral, Joana
Gollo, Leonardo L.
Breakspear, Michael
Baselice, Fabio
Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement
title Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement
title_full Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement
title_fullStr Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement
title_full_unstemmed Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement
title_short Detection of Cross-Frequency Coupling Between Brain Areas: An Extension of Phase Linearity Measurement
title_sort detection of cross-frequency coupling between brain areas: an extension of phase linearity measurement
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9083011/
https://www.ncbi.nlm.nih.gov/pubmed/35546895
http://dx.doi.org/10.3389/fnins.2022.846623
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