Sleep deprivation changes frequency-specific functional organization of the resting human brain

被引:0
|
作者
Luo, Zhiguo [1 ,2 ,3 ,4 ]
Yin, Erwei [1 ,2 ,3 ]
Yan, Ye [1 ,2 ,3 ]
Zhao, Shaokai [1 ,2 ,3 ]
Xie, Liang [1 ,2 ,3 ]
Shen, Hui [4 ]
Zeng, Ling -Li [4 ]
Wang, Lubin [5 ]
Hu, Dewen [4 ]
机构
[1] Acad Mil Sci AMS, Def Innovat Inst, Beijing 100071, Peoples R China
[2] Intelligent Game & Decis Lab, Beijing 100071, Peoples R China
[3] Tianjin Artificial Intelligence Innovat Ctr TAI, Tianjin 300450, Peoples R China
[4] Natl Univ Def Technol, Coll Intelligence Sci & Technol, Changsha 410073, Hunan, Peoples R China
[5] Beijing Inst Basic Med Sci, Brain Sci Ctr, Beijing 102206, Peoples R China
基金
中国国家自然科学基金;
关键词
Sleep deprivation; Spectral connection; Robust feature selection; Cerebellum; Topology; Frequency specificity; GENDER-DIFFERENCES; CONNECTIVITY; NETWORK; IDENTIFICATION; CONSEQUENCES; WAKEFULNESS; PERFORMANCE; CONNECTOME; MODULARITY; COST;
D O I
10.1016/j.brainresbull.2024.110925
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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.
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页数:11
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