Associating EEG functional networks and the effect of sleep deprivation as measured using psychomotor vigilance tests

Sophie L. Mason*, Leandro Junges, Wessel Woldman, Suzanne Ftouni, Clare Anderson, John R. Terry, Andrew P. Bagshaw

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

People are routinely forced to undertake cognitive challenges under the effect of sleep deprivation, due to professional and social obligations forcing them to ignore their circadian clock. However, low intra-individual and high inter-individual differences in behavioural outcomes are known to occur when people are sleep deprived, leading to the conclusion that trait-like differences to sleep deprivation could explain the differing levels of resilience. Within this study we consider if trait-like resilience to sleep deprivation, measured using psychomotor vigilance tests over a 40 h protocol, could be associated with graph metrics (mean node strength, clustering coefficient, characteristic path length and stability) calculated from EEG functional networks acquired when participants () are well rested (baseline). Furthermore, we investigated how stability (the consistency of a participant’s functional network over time measured using 2-D correlation) changed over the constant routine. We showed evidence of strong significant correlations between high mean node strength, low characteristic path length and high stability at baseline with a general resilience to extended sleep deprivation, although the same features lead to vulnerability during the period of natural sleep onset, highlighting non-uniform correlations over time. We also show significant differences in the levels of stability between resilient and vulnerable groups.
Original languageEnglish
Article number27999
JournalScientific Reports
Volume14
Issue number1
DOIs
Publication statusPublished - 14 Nov 2024

Keywords

  • Functional connectivity
  • Sleep deprivation
  • Psychomotor vigilance test (PVT)
  • EEG
  • Functional networks
  • Graph theory

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