Research article

BMC Neuroscience

, 15:88

Open Access This content is freely available online to anyone, anywhere at any time.

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

  • Ilse M VerweijAffiliated withNetherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences
  • , Nico RomeijnAffiliated withNetherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences
  • , Dirk JA SmitAffiliated withDepartment of Psychology, VU University
  • , Giovanni PiantoniAffiliated withNetherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences
  • , Eus JW Van SomerenAffiliated withNetherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and SciencesDepartment of Integrative Neurophysiology, Faculty of Earth and Life Sciences, VU UniversityDepartment of Medical Psychology, VU University Medical Centre
  • , Ysbrand D van der WerfAffiliated withNetherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and SciencesDepartment of Anatomy and Neurosciences, VU University Medical Centre Email author 

Abstract

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.

Keywords

Sleep deprivation Brain connectivity Graph theory EEG analysis Small-world networks