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Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks
Frequency-specific oscillations and phase-coupling of neuronal populations are essential mechanisms for the coordination of activity between brain areas during cognitive tasks. Therefore, the ongoing activity ascribed to the different functional brain networks should also be able to reorganise and c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6065434/ https://www.ncbi.nlm.nih.gov/pubmed/30061566 http://dx.doi.org/10.1038/s41467-018-05316-z |
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author | Vidaurre, Diego Hunt, Laurence T. Quinn, Andrew J. Hunt, Benjamin A. E. Brookes, Matthew J. Nobre, Anna C. Woolrich, Mark W. |
author_facet | Vidaurre, Diego Hunt, Laurence T. Quinn, Andrew J. Hunt, Benjamin A. E. Brookes, Matthew J. Nobre, Anna C. Woolrich, Mark W. |
author_sort | Vidaurre, Diego |
collection | PubMed |
description | Frequency-specific oscillations and phase-coupling of neuronal populations are essential mechanisms for the coordination of activity between brain areas during cognitive tasks. Therefore, the ongoing activity ascribed to the different functional brain networks should also be able to reorganise and coordinate via similar mechanisms. We develop a novel method for identifying large-scale phase-coupled network dynamics and show that resting networks in magnetoencephalography are well characterised by visits to short-lived transient brain states, with spatially distinct patterns of oscillatory power and coherence in specific frequency bands. Brain states are identified for sensory, motor networks and higher-order cognitive networks. The cognitive networks include a posterior alpha (8–12 Hz) and an anterior delta/theta range (1–7 Hz) network, both exhibiting high power and coherence in areas that correspond to posterior and anterior subdivisions of the default mode network. Our results show that large-scale cortical phase-coupling networks have characteristic signatures in very specific frequency bands, possibly reflecting functional specialisation at different intrinsic timescales. |
format | Online Article Text |
id | pubmed-6065434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-60654342018-07-31 Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks Vidaurre, Diego Hunt, Laurence T. Quinn, Andrew J. Hunt, Benjamin A. E. Brookes, Matthew J. Nobre, Anna C. Woolrich, Mark W. Nat Commun Article Frequency-specific oscillations and phase-coupling of neuronal populations are essential mechanisms for the coordination of activity between brain areas during cognitive tasks. Therefore, the ongoing activity ascribed to the different functional brain networks should also be able to reorganise and coordinate via similar mechanisms. We develop a novel method for identifying large-scale phase-coupled network dynamics and show that resting networks in magnetoencephalography are well characterised by visits to short-lived transient brain states, with spatially distinct patterns of oscillatory power and coherence in specific frequency bands. Brain states are identified for sensory, motor networks and higher-order cognitive networks. The cognitive networks include a posterior alpha (8–12 Hz) and an anterior delta/theta range (1–7 Hz) network, both exhibiting high power and coherence in areas that correspond to posterior and anterior subdivisions of the default mode network. Our results show that large-scale cortical phase-coupling networks have characteristic signatures in very specific frequency bands, possibly reflecting functional specialisation at different intrinsic timescales. Nature Publishing Group UK 2018-07-30 /pmc/articles/PMC6065434/ /pubmed/30061566 http://dx.doi.org/10.1038/s41467-018-05316-z Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Vidaurre, Diego Hunt, Laurence T. Quinn, Andrew J. Hunt, Benjamin A. E. Brookes, Matthew J. Nobre, Anna C. Woolrich, Mark W. Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks |
title | Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks |
title_full | Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks |
title_fullStr | Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks |
title_full_unstemmed | Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks |
title_short | Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks |
title_sort | spontaneous cortical activity transiently organises into frequency specific phase-coupling networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6065434/ https://www.ncbi.nlm.nih.gov/pubmed/30061566 http://dx.doi.org/10.1038/s41467-018-05316-z |
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