Sleep deprivation leads to a loss of functional connectivity in frontal brain regions

Abstract

BackgroundThe restorative effect of sleep on waking brain activity remains poorly understood. Previous studies have compared overall neural network characteristics after normal sleep and sleep deprivation. To study whether sleep and sleep deprivation might differentially affect subsequent connectivity characteristics in different brain regions, we performed a within-subject study of resting state brain activity using the graph theory framework adapted for the individual electrode level.In balanced order, we obtained high-density resting state electroencephalography (EEG) in 8 healthy participants, during a day following normal sleep and during a day following total sleep deprivation. We computed topographical maps of graph theoretical parameters describing local clustering and path length characteristics from functional connectivity matrices, based on synchronization likelihood, in five different frequency bands. A non-parametric permutation analysis with cluster correction for multiple comparisons was applied to assess significance of topographical changes in clustering coefficient and path length.ResultsSignificant changes in graph theoretical parameters were only found on the scalp overlying the prefrontal cortex, where the clustering coefficient (local integration) decreased in the alpha frequency band and the path length (global integration) increased in the theta frequency band. These changes occurred regardless, and independent of, changes in power due to the sleep deprivation procedure.ConclusionsThe findings indicate that sleep deprivation most strongly affects the functional connectivity of prefrontal cortical areas. The findings extend those of previous studies, which showed sleep deprivation to predominantly affect functions mediated by the prefrontal cortex, such as working memory. Together, these findings suggest that the restorative effect of sleep is especially relevant for the maintenance of functional connectivity of prefrontal brain regions.

Linking Sleep Disturbance and Maladaptive Repetitive Thought: The Role of Executive Function

“…These results are also consistent with existing (Van Dongen et al 2003). Recent research has found that sleep deprivation decreases activation of and functional connectivity in the prefrontal cortex, which may explain the specificity of cognitive deficits in higher-order processes, such as inhibition and attention, following sleep loss (Ma et al 2015;Verweij et al 2014). Furthermore, the latent executive function variable was also associated with the latent maladaptive repetitive thought variable.…”

“…In conjunction with extant research, these results suggest that sleep disturbance may impair executive function, which may then lead to increased engagement in maladaptive repetitive thought. It may be the case that the decreased activation of and functional connectivity within brain regions associated with executive function observed following sleep loss (Ma et al 2015;Verweij et al 2014) may contribute to a diminished ability to inhibit engagement in maladaptive repetitive .46…”

Computational cognitive modeling of the temporal dynamics of fatigue from sleep loss

“…Dynamic changes in drift ratio during sleep deprivation or night work are associated with reduced signal-to-noise ratio and, consequently, degraded quality of cognitive processing. This perspective is supported by neuroimaging data, which indicate that sleep deprivation is associated with a reduction in neuronal connectivity (Verweij et al, 2014) or available functional neuronal circuits, especially those that are most intensively used for the task at hand (Chee & Asplund, 2013). …”

Tracking brain arousal fluctuations with fMRI

“…Indeed, changes in vigilance and arousal (hereafter described jointly as "arousal"), which can be especially prevalent during the passive and uncontrolled resting state, result in fMRI signal variability that may confound the extraction of functional networks (5,19). For example, the amplitude and extent of correlations in restingstate fMRI data vary with EEG-and behaviorally defined indicators of drowsiness and light sleep (20)(21)(22)(23)(24)(25) and are altered by sleep deprivation (26)(27)(28) and caffeine-induced changes in arousal state (29). Distinct patterns of functional connectivity across multiple networks have been associated with distinct EEG-defined sleep stages (30,31) with sufficient reliability to enable the identification of sleep stages from fMRI data alone (30).…”