Sleep deprivation changes frequency-specific functional organization of the resting human brain
Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies have widely explored the temporal connection changes in the human brain following long-term sleep deprivation (SD). However, the frequency-specific topological properties of sleep-deprived functional networks remain virtu...
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Elsevier
2024-05-01
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Series: | Brain Research Bulletin |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S0361923024000583 |
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author | Zhiguo Luo Erwei Yin Ye Yan Shaokai Zhao Liang Xie Hui Shen Ling-Li Zeng Lubin Wang Dewen Hu |
author_facet | Zhiguo Luo Erwei Yin Ye Yan Shaokai Zhao Liang Xie Hui Shen Ling-Li Zeng Lubin Wang Dewen Hu |
author_sort | Zhiguo Luo |
collection | DOAJ |
description | Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies have widely explored the temporal connection changes in the human brain following long-term sleep deprivation (SD). However, the frequency-specific topological properties of sleep-deprived functional networks remain virtually unclear. In this study, thirty-seven healthy male subjects underwent resting-state fMRI during rested wakefulness (RW) and after 36 hours of SD, and we examined frequency-specific spectral connection changes (0.01–0.08 Hz, interval = 0.01 Hz) caused by SD. First, we conducted a multivariate pattern analysis combining linear SVM classifiers with a robust feature selection algorithm, and the results revealed that accuracies of 74.29%-84.29% could be achieved in the classification between RW and SD states in leave-one-out cross-validation at different frequency bands, moreover, the spectral connection at the lowest and highest frequency bands exhibited higher discriminative power. Connection involving the cingulo-opercular network increased most, while connection involving the default-mode network decreased most following SD. Then we performed a graph-theoretic analysis and observed reduced low-frequency modularity and high-frequency global efficiency in the SD state. Moreover, hub regions, which were primarily situated in the cerebellum and the cingulo-opercular network after SD, exhibited high discriminative power in the aforementioned classification consistently. The findings may indicate the frequency-dependent effects of SD on the functional network topology and its efficiency of information exchange, providing new insights into the impact of SD on the human brain. |
first_indexed | 2024-04-24T11:56:09Z |
format | Article |
id | doaj.art-11a633fdd8774a5090529e323abf6078 |
institution | Directory Open Access Journal |
issn | 1873-2747 |
language | English |
last_indexed | 2024-04-24T11:56:09Z |
publishDate | 2024-05-01 |
publisher | Elsevier |
record_format | Article |
series | Brain Research Bulletin |
spelling | doaj.art-11a633fdd8774a5090529e323abf60782024-04-09T04:12:39ZengElsevierBrain Research Bulletin1873-27472024-05-01210110925Sleep deprivation changes frequency-specific functional organization of the resting human brainZhiguo Luo0Erwei Yin1Ye Yan2Shaokai Zhao3Liang Xie4Hui Shen5Ling-Li Zeng6Lubin Wang7Dewen Hu8Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China; College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, ChinaDefense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China; Corresponding author at: Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China.Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, ChinaDefense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, ChinaDefense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100071, China; Intelligent Game and Decision Laboratory, Beijing 100071, China; Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, ChinaThe Brain Science Center, Beijing Institute of Basic Medical Sciences, Beijing 102206, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China; Corresponding author.Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies have widely explored the temporal connection changes in the human brain following long-term sleep deprivation (SD). However, the frequency-specific topological properties of sleep-deprived functional networks remain virtually unclear. In this study, thirty-seven healthy male subjects underwent resting-state fMRI during rested wakefulness (RW) and after 36 hours of SD, and we examined frequency-specific spectral connection changes (0.01–0.08 Hz, interval = 0.01 Hz) caused by SD. First, we conducted a multivariate pattern analysis combining linear SVM classifiers with a robust feature selection algorithm, and the results revealed that accuracies of 74.29%-84.29% could be achieved in the classification between RW and SD states in leave-one-out cross-validation at different frequency bands, moreover, the spectral connection at the lowest and highest frequency bands exhibited higher discriminative power. Connection involving the cingulo-opercular network increased most, while connection involving the default-mode network decreased most following SD. Then we performed a graph-theoretic analysis and observed reduced low-frequency modularity and high-frequency global efficiency in the SD state. Moreover, hub regions, which were primarily situated in the cerebellum and the cingulo-opercular network after SD, exhibited high discriminative power in the aforementioned classification consistently. The findings may indicate the frequency-dependent effects of SD on the functional network topology and its efficiency of information exchange, providing new insights into the impact of SD on the human brain.http://www.sciencedirect.com/science/article/pii/S0361923024000583Sleep deprivationSpectral connectionRobust feature selectionCerebellumTopologyFrequency specificity |
spellingShingle | Zhiguo Luo Erwei Yin Ye Yan Shaokai Zhao Liang Xie Hui Shen Ling-Li Zeng Lubin Wang Dewen Hu Sleep deprivation changes frequency-specific functional organization of the resting human brain Brain Research Bulletin Sleep deprivation Spectral connection Robust feature selection Cerebellum Topology Frequency specificity |
title | Sleep deprivation changes frequency-specific functional organization of the resting human brain |
title_full | Sleep deprivation changes frequency-specific functional organization of the resting human brain |
title_fullStr | Sleep deprivation changes frequency-specific functional organization of the resting human brain |
title_full_unstemmed | Sleep deprivation changes frequency-specific functional organization of the resting human brain |
title_short | Sleep deprivation changes frequency-specific functional organization of the resting human brain |
title_sort | sleep deprivation changes frequency specific functional organization of the resting human brain |
topic | Sleep deprivation Spectral connection Robust feature selection Cerebellum Topology Frequency specificity |
url | http://www.sciencedirect.com/science/article/pii/S0361923024000583 |
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