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.

Details

Title
Associating EEG functional networks and the effect of sleep deprivation as measured using psychomotor vigilance tests
Author
Mason, Sophie L. 1 ; Junges, Leandro 2 ; Woldman, Wessel 3 ; Ftouni, Suzanne 4 ; Anderson, Clare 5 ; Terry, John R. 3 ; Bagshaw, Andrew P. 6 

 University of Birmingham, Centre for Systems Modelling and Quantitative Biomedicine, Birmingham, UK (GRID:grid.6572.6) (ISNI:0000 0004 1936 7486); University of Birmingham, Centre for Human Brain Health, College of Life and Environmental Sciences, Birmingham, UK (GRID:grid.6572.6) (ISNI:0000 0004 1936 7486) 
 University of Birmingham, Centre for Systems Modelling and Quantitative Biomedicine, Birmingham, UK (GRID:grid.6572.6) (ISNI:0000 0004 1936 7486) 
 University of Birmingham, Centre for Systems Modelling and Quantitative Biomedicine, Birmingham, UK (GRID:grid.6572.6) (ISNI:0000 0004 1936 7486); Neuronostics Limited, Engine Shed, Station Approach, Bristol, UK (GRID:grid.6572.6) 
 Monash University, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Clayton, Australia (GRID:grid.1002.3) (ISNI:0000 0004 1936 7857) 
 University of Birmingham, Centre for Human Brain Health, College of Life and Environmental Sciences, Birmingham, UK (GRID:grid.6572.6) (ISNI:0000 0004 1936 7486); Monash University, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Clayton, Australia (GRID:grid.1002.3) (ISNI:0000 0004 1936 7857) 
 University of Birmingham, Centre for Human Brain Health, College of Life and Environmental Sciences, Birmingham, UK (GRID:grid.6572.6) (ISNI:0000 0004 1936 7486) 
Pages
27999
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3128469255
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.