Cargando…

Frequency‐dependent functional connectivity in resting state networks

Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large‐scale networks, called resting‐state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been...

Descripción completa

Detalles Bibliográficos
Autores principales: Samogin, Jessica, Marino, Marco, Porcaro, Camillo, Wenderoth, Nicole, Dupont, Patrick, Swinnen, Stephan P., Mantini, Dante
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670639/
https://www.ncbi.nlm.nih.gov/pubmed/32840936
http://dx.doi.org/10.1002/hbm.25184
_version_ 1783610778080772096
author Samogin, Jessica
Marino, Marco
Porcaro, Camillo
Wenderoth, Nicole
Dupont, Patrick
Swinnen, Stephan P.
Mantini, Dante
author_facet Samogin, Jessica
Marino, Marco
Porcaro, Camillo
Wenderoth, Nicole
Dupont, Patrick
Swinnen, Stephan P.
Mantini, Dante
author_sort Samogin, Jessica
collection PubMed
description Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large‐scale networks, called resting‐state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been used for investigating the electrophysiological basis of RSNs. To date, it is largely unclear how neural oscillations measured with EEG and MEG are related to functional connectivity in the resting state. In addition, it remains to be elucidated whether and how the observed neural oscillations are related to the spatial distribution of the network nodes over the cortex. To address these questions, we examined frequency‐dependent functional connectivity between the main nodes of several RSNs, spanning large part of the cortex. We estimated connectivity using band‐limited power correlations from high‐density EEG data collected in healthy participants. We observed that functional interactions within RSNs are characterized by a specific combination of neuronal oscillations in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–80 Hz) bands, which highly depend on the position of the network nodes. This finding may contribute to a better understanding of the mechanisms through which neural oscillations support functional connectivity in the brain.
format Online
Article
Text
id pubmed-7670639
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley & Sons, Inc.
record_format MEDLINE/PubMed
spelling pubmed-76706392020-11-23 Frequency‐dependent functional connectivity in resting state networks Samogin, Jessica Marino, Marco Porcaro, Camillo Wenderoth, Nicole Dupont, Patrick Swinnen, Stephan P. Mantini, Dante Hum Brain Mapp Research Articles Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large‐scale networks, called resting‐state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been used for investigating the electrophysiological basis of RSNs. To date, it is largely unclear how neural oscillations measured with EEG and MEG are related to functional connectivity in the resting state. In addition, it remains to be elucidated whether and how the observed neural oscillations are related to the spatial distribution of the network nodes over the cortex. To address these questions, we examined frequency‐dependent functional connectivity between the main nodes of several RSNs, spanning large part of the cortex. We estimated connectivity using band‐limited power correlations from high‐density EEG data collected in healthy participants. We observed that functional interactions within RSNs are characterized by a specific combination of neuronal oscillations in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–80 Hz) bands, which highly depend on the position of the network nodes. This finding may contribute to a better understanding of the mechanisms through which neural oscillations support functional connectivity in the brain. John Wiley & Sons, Inc. 2020-08-25 /pmc/articles/PMC7670639/ /pubmed/32840936 http://dx.doi.org/10.1002/hbm.25184 Text en © 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Samogin, Jessica
Marino, Marco
Porcaro, Camillo
Wenderoth, Nicole
Dupont, Patrick
Swinnen, Stephan P.
Mantini, Dante
Frequency‐dependent functional connectivity in resting state networks
title Frequency‐dependent functional connectivity in resting state networks
title_full Frequency‐dependent functional connectivity in resting state networks
title_fullStr Frequency‐dependent functional connectivity in resting state networks
title_full_unstemmed Frequency‐dependent functional connectivity in resting state networks
title_short Frequency‐dependent functional connectivity in resting state networks
title_sort frequency‐dependent functional connectivity in resting state networks
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670639/
https://www.ncbi.nlm.nih.gov/pubmed/32840936
http://dx.doi.org/10.1002/hbm.25184
work_keys_str_mv AT samoginjessica frequencydependentfunctionalconnectivityinrestingstatenetworks
AT marinomarco frequencydependentfunctionalconnectivityinrestingstatenetworks
AT porcarocamillo frequencydependentfunctionalconnectivityinrestingstatenetworks
AT wenderothnicole frequencydependentfunctionalconnectivityinrestingstatenetworks
AT dupontpatrick frequencydependentfunctionalconnectivityinrestingstatenetworks
AT swinnenstephanp frequencydependentfunctionalconnectivityinrestingstatenetworks
AT mantinidante frequencydependentfunctionalconnectivityinrestingstatenetworks