Abstract

Sleep is crucial for daytime functioning, cognitive performance and general well-being. These aspects of daily life are known to be impaired after extended wake, yet, the underlying neuronal correlates have been difficult to identify. Accumulating evidence suggests that normal functioning of the brain is characterized by long-range temporal correlations (LRTCs) in cortex, which are supportive for decision-making and working memory tasks. Here we assess LRTCs in resting state human EEG data during a 40-hour sleep deprivation experiment by evaluating the decay in autocorrelation and the scaling exponent of the detrended fluctuation analysis from EEG amplitude fluctuations. We find with both measures that LRTCs decline as sleep deprivation progresses. This decline becomes evident when taking changes in signal power into appropriate consideration. In contrast, the presence of strong signal power increases in some frequency bands over the course of sleep deprivation may falsely indicate LRTC changes that do not reflect the underlying long-range temporal correlation structure. Our results demonstrate the importance of sleep to maintain LRTCs in the human brain. In complex networks, LRTCs naturally emerge in the vicinity of a critical state. The observation of declining LRTCs during wake thus provides additional support for our hypothesis that sleep reorganizes cortical networks towards critical dynamics for optimal functioning.

Highlights

  • Sleep is essential for daytime functioning and well-being

  • We started by thoroughly assessing signal power and its changes over the course of sleep deprivation, as this is of central importance for the following characterization of timescales and long-range temporal correlations (LRTCs)

  • We report the decline of long-range temporal correlations (LRTCs) in cortical activity during sustained wakefulness

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Summary

Introduction

Sleep is essential for daytime functioning and well-being. Without sleep optimal brain functioning such as responsiveness to stimuli, information processing, or learning is impaired[1,2,3,4]. The network dynamics typically observed with this ability are characterized by slowly decaying autocorrelation functions, or, in general, long-range temporal correlations (LRTCs). In a large body of EEG research, slow timescales associated with long-range temporal correlations have been observed and studied in the amplitude fluctuations of ongoing neuronal oscillations[13,14,15,16,17,18,19,20,21] Together, these studies provide strong support for the existence of slow timescales associated with LRTCs in cortical activity and their important role for the integration of information in brain networks. The results support a hypothesis on the network function of sleep, to re-organize cortical networks towards critical dynamics with long-range temporal correlations for optimal function during wake

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