State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.

Functional connectivity measures applied to magnetoencephalography (MEG) data have the capacity to elucidate neuronal networks. However, the task-related modulation of these measures is essential to identifying the functional relevance of the identified network. In this study, we provide evidence fo...

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Main Authors: Timothy Bardouille, Shaun Boe
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3485371?pdf=render
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spelling doaj-c4e4446d6d2143b28c606a5f9de3c0ff2020-11-25T01:46:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-01710e4868210.1371/journal.pone.0048682State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.Timothy BardouilleShaun BoeFunctional connectivity measures applied to magnetoencephalography (MEG) data have the capacity to elucidate neuronal networks. However, the task-related modulation of these measures is essential to identifying the functional relevance of the identified network. In this study, we provide evidence for the efficacy of measuring "state-related" (i.e., task vs. rest) changes in MEG functional connectivity for revealing a sensorimotor network. We investigate changes in functional connectivity, measured as cortico-cortical coherence (CCC), between rest blocks and the performance of a visually directed motor task in a healthy cohort. Task-positive changes in CCC were interpreted in the context of any concomitant modulations in spectral power. Task-related increases in whole-head CCC relative to the resting state were identified between areas established as part of the sensorimotor network as well as frontal eye fields and prefrontal cortices, predominantly in the beta and gamma frequency bands. This study provides evidence for the use of MEG to identify task-specific functionally connected sensorimotor networks in a non-invasive, patient friendly manner.http://europepmc.org/articles/PMC3485371?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Timothy Bardouille
Shaun Boe
spellingShingle Timothy Bardouille
Shaun Boe
State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.
PLoS ONE
author_facet Timothy Bardouille
Shaun Boe
author_sort Timothy Bardouille
title State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.
title_short State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.
title_full State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.
title_fullStr State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.
title_full_unstemmed State-related changes in MEG functional connectivity reveal the task-positive sensorimotor network.
title_sort state-related changes in meg functional connectivity reveal the task-positive sensorimotor network.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2012-01-01
description Functional connectivity measures applied to magnetoencephalography (MEG) data have the capacity to elucidate neuronal networks. However, the task-related modulation of these measures is essential to identifying the functional relevance of the identified network. In this study, we provide evidence for the efficacy of measuring "state-related" (i.e., task vs. rest) changes in MEG functional connectivity for revealing a sensorimotor network. We investigate changes in functional connectivity, measured as cortico-cortical coherence (CCC), between rest blocks and the performance of a visually directed motor task in a healthy cohort. Task-positive changes in CCC were interpreted in the context of any concomitant modulations in spectral power. Task-related increases in whole-head CCC relative to the resting state were identified between areas established as part of the sensorimotor network as well as frontal eye fields and prefrontal cortices, predominantly in the beta and gamma frequency bands. This study provides evidence for the use of MEG to identify task-specific functionally connected sensorimotor networks in a non-invasive, patient friendly manner.
url http://europepmc.org/articles/PMC3485371?pdf=render
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