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Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings
Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cogniti...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233600/ https://www.ncbi.nlm.nih.gov/pubmed/32374723 http://dx.doi.org/10.1371/journal.pbio.3000685 |
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author | Siebenhühner, Felix Wang, Sheng H. Arnulfo, Gabriele Lampinen, Anna Nobili, Lino Palva, J. Matias Palva, Satu |
author_facet | Siebenhühner, Felix Wang, Sheng H. Arnulfo, Gabriele Lampinen, Anna Nobili, Lino Palva, J. Matias Palva, Satu |
author_sort | Siebenhühner, Felix |
collection | PubMed |
description | Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase–amplitude coupling (PAC) or by n:m-cross–frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high-frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for interareal CFS and PAC being 2 distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks. |
format | Online Article Text |
id | pubmed-7233600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-72336002020-06-02 Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings Siebenhühner, Felix Wang, Sheng H. Arnulfo, Gabriele Lampinen, Anna Nobili, Lino Palva, J. Matias Palva, Satu PLoS Biol Research Article Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase–amplitude coupling (PAC) or by n:m-cross–frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high-frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for interareal CFS and PAC being 2 distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks. Public Library of Science 2020-05-06 /pmc/articles/PMC7233600/ /pubmed/32374723 http://dx.doi.org/10.1371/journal.pbio.3000685 Text en © 2020 Siebenhühner et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Siebenhühner, Felix Wang, Sheng H. Arnulfo, Gabriele Lampinen, Anna Nobili, Lino Palva, J. Matias Palva, Satu Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings |
title | Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings |
title_full | Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings |
title_fullStr | Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings |
title_full_unstemmed | Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings |
title_short | Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings |
title_sort | genuine cross-frequency coupling networks in human resting-state electrophysiological recordings |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233600/ https://www.ncbi.nlm.nih.gov/pubmed/32374723 http://dx.doi.org/10.1371/journal.pbio.3000685 |
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