Resisting Sleep Pressure: Impact on Resting State Functional Network Connectivity
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In today’s 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased ‘time awake’. All other FNCs became more anti-correlated with increased ‘time awake’. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of ‘time awake’. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs.
KeywordsBOLD Pseudo BOLD Arterial spin labeling Cerebral blood flow Time awake Independent component analysis Vigilance Imaging modality
This study was supported by the Swiss National Science Foundation grant CRSII3_136249. We thank Drs. Andrea Federspiel, Philipp Stämpfli, Roger Lüchinger, Kay Jann, Roland Dürr, Thomas Rusterholz for technical support and Drs. Thomas Koenig, Mara Kottlow, Lars Michels and Leila Tarokh for fruitful discussions. We also would like to thank Ximena Omlin, Angela Aeschbach, Claudia Aschmann, Daniela Buser, Angela Escobar, Lukas Fürer, Jolanda Müller, Johanna Scherer, Nina Schumacher, Michelle Steinemann, Sarah Untersander and Katharina Wellstein for help with the data acquisition.
This work was supported by the Swiss National Science Foundation Sinergia grant #136249.
LT, AS, DB, ROT and PA designed the experiment. LT and AS performed the experiment. LT, JB and PA analyzed the data. LT and PA wrote the manuscript. All authors approved the final version.
Compliance with Ethical Standards
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
- Allen EA et al (2011a) A baseline for the multivariate comparison of resting-state networks Frontiers in Systems. Neuroscience 5:1–23Google Scholar
- Buxton RB (2002) Introduction to Functional Magnetic Resonance Imaging: Principles and Techniques. Cambridge University Press, Cambridge, NYGoogle Scholar
- Czisch M, Wehrle R, Harsay H, Wetter TC, Holsboer F, Sämann PG, Drummond SPA (2012) On the need of objective vigilance monitoring: effects of sleep loss on target detection and task-negative activity using combined EEG/fMRI. Front Neurol 3:67. doi: 10.3389/fneur.2012.00067 CrossRefPubMedPubMedCentralGoogle Scholar
- Hjelmervik H, Hausmann M, Osnes B, Westerhausen R, Specht K (2014) Resting states are resting traits—an fMRI Study of sex differences and menstrual cycle effects in resting state cognitive control networks. PLoS ONE 9:e103492. doi: 10.1371/journal.pone.0103492 CrossRefPubMedPubMedCentralGoogle Scholar
- Iber C, Ancoli-Israel S, Chesson Jr AL, Quan SF (2007) The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications, 1st edn. American Academy of Sleep Medicine, WestchesterGoogle Scholar
- Kaplan GB, Greenblatt DJ, Ehrenberg BL, Goddard JE, Cotreau MM, Harmatz JS, Shader RI (1997) Dose-dependent pharmacokinetics and psychomotor effects of caffeine in humans. Pharmcokinetics Pharmacodyn 37:693–703Google Scholar
- Rechtschaffen A, Kales A (1968) A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. U. S. Department of Health, Education. and Welfare, Public Health Service - National Institutes of Health, National Institute of Neurological Diseases and Blindness, Neurological Information Network, Bethesda, Maryland 20014Google Scholar