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EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions
The weighted Phase Lag Index (wPLI) and the weighted Symbolic Mutual Information (wSMI) represent two robust and widely used methods for MEG/EEG functional connectivity estimation. Interestingly, both methods have been shown to detect relative alterations of brain functional connectivity in conditio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586889/ https://www.ncbi.nlm.nih.gov/pubmed/31222021 http://dx.doi.org/10.1038/s41598-019-45289-7 |
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author | Imperatori, Laura Sophie Betta, Monica Cecchetti, Luca Canales-Johnson, Andrés Ricciardi, Emiliano Siclari, Francesca Pietrini, Pietro Chennu, Srivas Bernardi, Giulio |
author_facet | Imperatori, Laura Sophie Betta, Monica Cecchetti, Luca Canales-Johnson, Andrés Ricciardi, Emiliano Siclari, Francesca Pietrini, Pietro Chennu, Srivas Bernardi, Giulio |
author_sort | Imperatori, Laura Sophie |
collection | PubMed |
description | The weighted Phase Lag Index (wPLI) and the weighted Symbolic Mutual Information (wSMI) represent two robust and widely used methods for MEG/EEG functional connectivity estimation. Interestingly, both methods have been shown to detect relative alterations of brain functional connectivity in conditions associated with changes in the level of consciousness, such as following severe brain injury or under anaesthesia. Despite these promising findings, it was unclear whether wPLI and wSMI may account for distinct or similar types of functional interactions. Using simulated high-density (hd-)EEG data, we demonstrate that, while wPLI has high sensitivity for couplings presenting a mixture of linear and nonlinear interdependencies, only wSMI can detect purely nonlinear interaction dynamics. Moreover, we evaluated the potential impact of these differences on real experimental data by computing wPLI and wSMI connectivity in hd-EEG recordings of 12 healthy adults during wakefulness and deep (N3-)sleep, characterised by different levels of consciousness. In line with the simulation-based findings, this analysis revealed that both methods have different sensitivity for changes in brain connectivity across the two vigilance states. Our results indicate that the conjoint use of wPLI and wSMI may represent a powerful tool to study the functional bases of consciousness in physiological and pathological conditions. |
format | Online Article Text |
id | pubmed-6586889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65868892019-06-27 EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions Imperatori, Laura Sophie Betta, Monica Cecchetti, Luca Canales-Johnson, Andrés Ricciardi, Emiliano Siclari, Francesca Pietrini, Pietro Chennu, Srivas Bernardi, Giulio Sci Rep Article The weighted Phase Lag Index (wPLI) and the weighted Symbolic Mutual Information (wSMI) represent two robust and widely used methods for MEG/EEG functional connectivity estimation. Interestingly, both methods have been shown to detect relative alterations of brain functional connectivity in conditions associated with changes in the level of consciousness, such as following severe brain injury or under anaesthesia. Despite these promising findings, it was unclear whether wPLI and wSMI may account for distinct or similar types of functional interactions. Using simulated high-density (hd-)EEG data, we demonstrate that, while wPLI has high sensitivity for couplings presenting a mixture of linear and nonlinear interdependencies, only wSMI can detect purely nonlinear interaction dynamics. Moreover, we evaluated the potential impact of these differences on real experimental data by computing wPLI and wSMI connectivity in hd-EEG recordings of 12 healthy adults during wakefulness and deep (N3-)sleep, characterised by different levels of consciousness. In line with the simulation-based findings, this analysis revealed that both methods have different sensitivity for changes in brain connectivity across the two vigilance states. Our results indicate that the conjoint use of wPLI and wSMI may represent a powerful tool to study the functional bases of consciousness in physiological and pathological conditions. Nature Publishing Group UK 2019-06-20 /pmc/articles/PMC6586889/ /pubmed/31222021 http://dx.doi.org/10.1038/s41598-019-45289-7 Text en © The Author(s) 2019 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 Imperatori, Laura Sophie Betta, Monica Cecchetti, Luca Canales-Johnson, Andrés Ricciardi, Emiliano Siclari, Francesca Pietrini, Pietro Chennu, Srivas Bernardi, Giulio EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions |
title | EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions |
title_full | EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions |
title_fullStr | EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions |
title_full_unstemmed | EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions |
title_short | EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions |
title_sort | eeg functional connectivity metrics wpli and wsmi account for distinct types of brain functional interactions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586889/ https://www.ncbi.nlm.nih.gov/pubmed/31222021 http://dx.doi.org/10.1038/s41598-019-45289-7 |
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