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Dynamic functional connectivity states characterize NREM sleep and wakefulness
According to recent neuroimaging studies, temporal fluctuations in functional connectivity patterns can be clustered into dynamic functional connectivity (DFC) states and correspond to fluctuations in vigilance. However, whether there consistently exist DFC states associated with wakefulness and sle...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865216/ https://www.ncbi.nlm.nih.gov/pubmed/31444893 http://dx.doi.org/10.1002/hbm.24770 |
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author | Zhou, Shuqin Zou, Guangyuan Xu, Jing Su, Zihui Zhu, Huaiqiu Zou, Qihong Gao, Jia‐Hong |
author_facet | Zhou, Shuqin Zou, Guangyuan Xu, Jing Su, Zihui Zhu, Huaiqiu Zou, Qihong Gao, Jia‐Hong |
author_sort | Zhou, Shuqin |
collection | PubMed |
description | According to recent neuroimaging studies, temporal fluctuations in functional connectivity patterns can be clustered into dynamic functional connectivity (DFC) states and correspond to fluctuations in vigilance. However, whether there consistently exist DFC states associated with wakefulness and sleep stages and what are the characteristics and electrophysiological origin of these states remain unclear. The aims of the current study were to investigate the properties of DFC in different sleep stages and to explore the relationship between the characteristics of DFC and slow‐wave activity. We collected both eyes‐closed wakefulness and sleep data from 48 healthy young volunteers with simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. EEG data were employed as the gold standard of sleep stage scoring, and DFC states were estimated based on fMRI data. The results demonstrated that DFC states of the fMRI signals consistently corresponded to wakefulness and nonrapid eye movement sleep stages independent of the number of clusters. Furthermore, the mean dwell time of these states significantly correlated with slow‐wave activity. The inclusion or omission of regression of the global signal and the selection of parcellation schemes exerted minimal effects on the current findings. These results provide strong evidence that DFC states underlying fMRI signals match the fluctuations of vigilance and suggest a possible electrophysiological source of DFC states corresponding to vigilance states. |
format | Online Article Text |
id | pubmed-6865216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68652162020-06-12 Dynamic functional connectivity states characterize NREM sleep and wakefulness Zhou, Shuqin Zou, Guangyuan Xu, Jing Su, Zihui Zhu, Huaiqiu Zou, Qihong Gao, Jia‐Hong Hum Brain Mapp Research Articles According to recent neuroimaging studies, temporal fluctuations in functional connectivity patterns can be clustered into dynamic functional connectivity (DFC) states and correspond to fluctuations in vigilance. However, whether there consistently exist DFC states associated with wakefulness and sleep stages and what are the characteristics and electrophysiological origin of these states remain unclear. The aims of the current study were to investigate the properties of DFC in different sleep stages and to explore the relationship between the characteristics of DFC and slow‐wave activity. We collected both eyes‐closed wakefulness and sleep data from 48 healthy young volunteers with simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. EEG data were employed as the gold standard of sleep stage scoring, and DFC states were estimated based on fMRI data. The results demonstrated that DFC states of the fMRI signals consistently corresponded to wakefulness and nonrapid eye movement sleep stages independent of the number of clusters. Furthermore, the mean dwell time of these states significantly correlated with slow‐wave activity. The inclusion or omission of regression of the global signal and the selection of parcellation schemes exerted minimal effects on the current findings. These results provide strong evidence that DFC states underlying fMRI signals match the fluctuations of vigilance and suggest a possible electrophysiological source of DFC states corresponding to vigilance states. John Wiley & Sons, Inc. 2019-08-24 /pmc/articles/PMC6865216/ /pubmed/31444893 http://dx.doi.org/10.1002/hbm.24770 Text en © 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Zhou, Shuqin Zou, Guangyuan Xu, Jing Su, Zihui Zhu, Huaiqiu Zou, Qihong Gao, Jia‐Hong Dynamic functional connectivity states characterize NREM sleep and wakefulness |
title | Dynamic functional connectivity states characterize NREM sleep and wakefulness |
title_full | Dynamic functional connectivity states characterize NREM sleep and wakefulness |
title_fullStr | Dynamic functional connectivity states characterize NREM sleep and wakefulness |
title_full_unstemmed | Dynamic functional connectivity states characterize NREM sleep and wakefulness |
title_short | Dynamic functional connectivity states characterize NREM sleep and wakefulness |
title_sort | dynamic functional connectivity states characterize nrem sleep and wakefulness |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865216/ https://www.ncbi.nlm.nih.gov/pubmed/31444893 http://dx.doi.org/10.1002/hbm.24770 |
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