Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data

Fabrizio Vecchio, Francesca Miraglia, Maurizio Gorgoni, Michele Ferrara, Francesco Iberite, Placido Bramanti, Luigi De Gennaro, Paolo Maria Rossini

Research output: Contribution to journalArticlepeer-review

Abstract

Sleep onset is characterized by a specific and orchestrated pattern of frequency and topographical EEG changes. Conventional power analyses of electroencephalographic (EEG) and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. Here, we assess how “small world” characteristics of the brain networks, as reflected in the EEG rhythms, are modified in the wakefulness–sleep transition comparing the pre- and post-sleep onset epochs. The results show that sleep onset is characterized by a less ordered brain network (as reflected by the higher value of small world) in the sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in the low frequency delta and theta bands indicating disconnection on the remaining brain areas. Our results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset. Hum Brain Mapp 38:5456–5464, 2017.

Original languageEnglish
Pages (from-to)5456-5464
Number of pages9
JournalHuman Brain Mapping
Volume38
Issue number11
DOIs
Publication statusPublished - Nov 1 2017

Keywords

  • EEG
  • eLORETA
  • functional connectivity
  • graph theory
  • precision medicine
  • sigma band
  • sleep onset

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

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