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Exploring brain functional connectivity in rest and sleep states: a fNIRS study
This study investigates the brain functional connectivity in the rest and sleep states. We collected EEG, EOG, and fNIRS signals simultaneously during rest and sleep phases. The rest phase was defined as a quiet wake-eyes open (w_o) state, while the sleep phase was separated into three states; quiet...
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/PMC6212555/ https://www.ncbi.nlm.nih.gov/pubmed/30385843 http://dx.doi.org/10.1038/s41598-018-33439-2 |
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author | Nguyen, Thien Babawale, Olajide Kim, Tae Jo, Hang Joon Liu, Hanli Kim, Jae Gwan |
author_facet | Nguyen, Thien Babawale, Olajide Kim, Tae Jo, Hang Joon Liu, Hanli Kim, Jae Gwan |
author_sort | Nguyen, Thien |
collection | PubMed |
description | This study investigates the brain functional connectivity in the rest and sleep states. We collected EEG, EOG, and fNIRS signals simultaneously during rest and sleep phases. The rest phase was defined as a quiet wake-eyes open (w_o) state, while the sleep phase was separated into three states; quiet wake-eyes closed (w_c), non-rapid eye movement sleep stage 1 (N1), and non-rapid eye movement sleep stage 2 (N2) using the EEG and EOG signals. The fNIRS signals were used to calculate the cerebral hemodynamic responses (oxy-, deoxy-, and total hemoglobin). We grouped 133 fNIRS channels into five brain regions (frontal, motor, temporal, somatosensory, and visual areas). These five regions were then used to form fifteen brain networks. A network connectivity was computed by calculating the Pearson correlation coefficients of the hemodynamic responses between fNIRS channels belonging to the network. The fifteen networks were compared across the states using the connection ratio and connection strength calculated from the normalized correlation coefficients. Across all fifteen networks and three hemoglobin types, the connection ratio was high in the w_c and N1 states and low in the w_o and N2 states. In addition, the connection strength was similar between the w_c and N1 states and lower in the w_o and N2 states. Based on our experimental results, we believe that fNIRS has a high potential to be a main tool to study the brain connectivity in the rest and sleep states. |
format | Online Article Text |
id | pubmed-6212555 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62125552018-11-06 Exploring brain functional connectivity in rest and sleep states: a fNIRS study Nguyen, Thien Babawale, Olajide Kim, Tae Jo, Hang Joon Liu, Hanli Kim, Jae Gwan Sci Rep Article This study investigates the brain functional connectivity in the rest and sleep states. We collected EEG, EOG, and fNIRS signals simultaneously during rest and sleep phases. The rest phase was defined as a quiet wake-eyes open (w_o) state, while the sleep phase was separated into three states; quiet wake-eyes closed (w_c), non-rapid eye movement sleep stage 1 (N1), and non-rapid eye movement sleep stage 2 (N2) using the EEG and EOG signals. The fNIRS signals were used to calculate the cerebral hemodynamic responses (oxy-, deoxy-, and total hemoglobin). We grouped 133 fNIRS channels into five brain regions (frontal, motor, temporal, somatosensory, and visual areas). These five regions were then used to form fifteen brain networks. A network connectivity was computed by calculating the Pearson correlation coefficients of the hemodynamic responses between fNIRS channels belonging to the network. The fifteen networks were compared across the states using the connection ratio and connection strength calculated from the normalized correlation coefficients. Across all fifteen networks and three hemoglobin types, the connection ratio was high in the w_c and N1 states and low in the w_o and N2 states. In addition, the connection strength was similar between the w_c and N1 states and lower in the w_o and N2 states. Based on our experimental results, we believe that fNIRS has a high potential to be a main tool to study the brain connectivity in the rest and sleep states. Nature Publishing Group UK 2018-11-01 /pmc/articles/PMC6212555/ /pubmed/30385843 http://dx.doi.org/10.1038/s41598-018-33439-2 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 Nguyen, Thien Babawale, Olajide Kim, Tae Jo, Hang Joon Liu, Hanli Kim, Jae Gwan Exploring brain functional connectivity in rest and sleep states: a fNIRS study |
title | Exploring brain functional connectivity in rest and sleep states: a fNIRS study |
title_full | Exploring brain functional connectivity in rest and sleep states: a fNIRS study |
title_fullStr | Exploring brain functional connectivity in rest and sleep states: a fNIRS study |
title_full_unstemmed | Exploring brain functional connectivity in rest and sleep states: a fNIRS study |
title_short | Exploring brain functional connectivity in rest and sleep states: a fNIRS study |
title_sort | exploring brain functional connectivity in rest and sleep states: a fnirs study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6212555/ https://www.ncbi.nlm.nih.gov/pubmed/30385843 http://dx.doi.org/10.1038/s41598-018-33439-2 |
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