Sleep deprivation leads to a loss of functional connectivity in frontal brain regions

被引:111
|
作者
Verweij, Ilse M. [1 ]
Romeijn, Nico [1 ]
Smit, Dirk J. A. [2 ]
Piantoni, Giovanni [1 ]
Van Someren, Eus J. W. [1 ,3 ,4 ]
van der Werf, Ysbrand D. [1 ,5 ]
机构
[1] Inst Royal Netherlands Acad Arts & Sci, Netherlands Inst Neurosci, NL-1105 BA Amsterdam, Netherlands
[2] Vrije Univ Amsterdam, Dept Psychol, Amsterdam, Netherlands
[3] Vrije Univ Amsterdam, Fac Earth & Life Sci, Dept Integrat Neurophysiol, Amsterdam, Netherlands
[4] Vrije Univ Amsterdam, Med Ctr, Dept Med Psychol, Amsterdam, Netherlands
[5] Vrije Univ Amsterdam, Med Ctr, Dept Anat & Neurosci, Amsterdam, Netherlands
来源
BMC NEUROSCIENCE | 2014年 / 15卷
关键词
Sleep deprivation; Brain connectivity; Graph theory; EEG analysis; Small-world networks; DEFAULT-MODE NETWORK; GRAPH-THEORETICAL ANALYSIS; SMALL-WORLD NETWORKS; SLOW-WAVE SLEEP; RESTING-STATE; SYNCHRONIZATION LIKELIHOOD; SYNAPTIC HOMEOSTASIS; COMPLEX NETWORKS; EEG; COGNITION;
D O I
10.1186/1471-2202-15-88
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: The restorative effect of sleep on waking brain activity remains poorly understood. Previous studies have compared overall neural network characteristics after normal sleep and sleep deprivation. To study whether sleep and sleep deprivation might differentially affect subsequent connectivity characteristics in different brain regions, we performed a within-subject study of resting state brain activity using the graph theory framework adapted for the individual electrode level. In balanced order, we obtained high-density resting state electroencephalography (EEG) in 8 healthy participants, during a day following normal sleep and during a day following total sleep deprivation. We computed topographical maps of graph theoretical parameters describing local clustering and path length characteristics from functional connectivity matrices, based on synchronization likelihood, in five different frequency bands. A non-parametric permutation analysis with cluster correction for multiple comparisons was applied to assess significance of topographical changes in clustering coefficient and path length. Results: Significant changes in graph theoretical parameters were only found on the scalp overlying the prefrontal cortex, where the clustering coefficient (local integration) decreased in the alpha frequency band and the path length (global integration) increased in the theta frequency band. These changes occurred regardless, and independent of, changes in power due to the sleep deprivation procedure. Conclusions: The findings indicate that sleep deprivation most strongly affects the functional connectivity of prefrontal cortical areas. The findings extend those of previous studies, which showed sleep deprivation to predominantly affect functions mediated by the prefrontal cortex, such as working memory. Together, these findings suggest that the restorative effect of sleep is especially relevant for the maintenance of functional connectivity of prefrontal brain regions.
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页数:10
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