Interplay between spontaneous and induced brain activity during human non-rapid eye movement sleep

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When presented with an auditory sequence, the brain acts as a predictive-coding device that extracts regularities in the transition probabilities between sounds and detects unexpected deviations from these regularities. Does such prediction require conscious vigilance, or does it continue to unfold automatically in the sleeping brain? The mismatch negativity and P300 components of the auditory event-related potential, reflecting two steps of auditory novelty detection, have been inconsistently observed in the various sleep stages. To clarify whether these steps remain during sleep, we recorded simultaneous electroencephalographic and magnetoencephalographic signals during wakefulness and during sleep in normal subjects listening to a hierarchical auditory paradigm including short-term (local) and long-term (global) regularities. The global response, reflected in the P300, vanished during sleep, in line with the hypothesis that it is a correlate of high-level conscious error detection. The local mismatch response remained across all sleep stages (N1, N2, and REM sleep), but with an incomplete structure; compared with wakefulness, a specific peak reflecting prediction error vanished during sleep. Those results indicate that sleep leaves initial auditory processing and passive sensory response adaptation intact, but specifically disrupts both short-term and long-term auditory predictive coding. mismatch response | prediction | magnetoencephalography | MMN | P300

Section: Discussionsupporting

confidence: 76%

mentioning

confidence: 99%

Disruption of hierarchical predictive coding during sleep

Strauss

Sitt

et al. 2015

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207

“…The sleep-protecting function of sleep spindles is supported by a number of EEG and neuroimaging studies in humans; for example, brain responses to auditory stimulus are significantly reduced when a tone is delivered concurrently with sleep spindles (31). Other studies have demonstrated a positive correlation between SD and the duration or stability of sleep (12,17), suggesting that the amount of sleep spindles might signify the strength of the gatekeeping mechanism that the thalamus exerts during sleep.…”

Section: Discussionmentioning

confidence: 75%

Optogenetically induced sleep spindle rhythms alter sleep architectures in mice

Kim

Latchoumane

Lee

et al. 2012

Sleep spindles are rhythmic patterns of neuronal activity generated within the thalamocortical circuit. Although spindles have been hypothesized to protect sleep by reducing the influence of external stimuli, it remains to be confirmed experimentally whether there is a direct relationship between sleep spindles and the stability of sleep. We have addressed this issue by using in vivo photostimulation of the thalamic reticular nucleus of mice to generate spindle oscillations that are structurally and functionally similar to spontaneous sleep spindles. Such optogenetic generation of sleep spindles increased the duration of non-rapid eye movement (NREM) sleep. Furthermore, the density of sleep spindles was correlated with the amount of NREM sleep. These findings establish a causal relationship between sleep spindles and the stability of NREM sleep, strongly supporting a role for the thalamocortical circuit in sleep regulation.sleep rhythms | sleep protection S leep spindles are characteristic EEG rhythms observed during non-rapid eye movement (NREM) sleep. It is characterized by periodic waxing and waning and 7-to 15-Hz oscillations with durations ranging from 0.5 to 3 s (1-3), and is often used as an EEG marker of NREM sleep. Sleep spindles are hypothesized to originate from the thalamic reticular nucleus (TRN) (4, 5), where the rhythmic burst activity of TRN neurons could initiate spindle oscillations within the whole thalamocortical circuit. When it has been initiated, this oscillation is self-maintained by the reciprocal interactions among cortical, thalamocortical (TC), and TRN neurons during NREM sleep (4, 6, 7). Sleep spindles are of particular interest because they are known to be involved in several sleep-dependent physiological and cognitive processes, such as memory consolidation and neuronal plasticity (7-10). Moreover, a growing amount of evidence suggests that sleep spindles serve a sleep-protecting function by modulating the degree of sensory transmission through the thalamus (11). Patients with hypersomnia show increased spindle density (SD) compared with control (12), and KO mice whose sleep spindles are reduced as a result of impaired thalamocortical oscillations experience sleep disturbances during NREM sleep (13-16). Further, individuals with a higher spindle rate are more tolerant to noise that occurs during sleep (17). Despite considerable evidence hinting at the sleepprotecting function of sleep spindles, no experimental studies have yet demonstrated a direct causal relationship between sleep spindles and the stability of sleep. A recent study found that optogenetic stimulation of TRN induced burst firing in TC neurons, which were hypothesized to underlie the occurrence of neocortical sleep spindles (18). However, because sleep spindles also occur spontaneously, it was not clear whether sleep spindles were driven by optogenetic stimulation of the TRN.To experimentally examine the sleep-protecting function of sleep spindles, we used Channelrhodopsin2 (ChR2) transgenic (tg) mice to bilaterally ...

“…Importantly, we do not claim that NREM sleep is associated with a total obliteration of conscious mental representations. The brain remains responsive to external stimuli during NREM sleep (12,13) and dreams have been reported after NREM sleep awakenings (14). However, the aim of the current paper was not to characterize the neural correlates of these mental representations but rather to contrast brain function during normal wakefulness to that observed during a state of impoverished conscious content such as NREM sleep.…”

Section: Discussionmentioning

confidence: 97%

Hierarchical clustering of brain activity during human nonrapid eye movement sleep

Boly

Perlbarg

Marrelec

et al. 2012

Self Cite

175

199

Consciousness is reduced during nonrapid eye movement (NREM) sleep due to changes in brain function that are still poorly understood. Here, we tested the hypothesis that impaired consciousness during NREM sleep is associated with an increased modularity of brain activity. Cerebral connectivity was quantified in restingstate functional magnetic resonance imaging times series acquired in 13 healthy volunteers during wakefulness and NREM sleep. The analysis revealed a modification of the hierarchical organization of large-scale networks into smaller independent modules during NREM sleep, independently from EEG markers of the slow oscillation. Such modifications in brain connectivity, possibly driven by sleep ultraslow oscillations, could hinder the brain's ability to integrate information and account for decreased consciousness during NREM sleep.complexity | integration D uring nonrapid eye movement (NREM) sleep, we are less aware of ourselves and our environment and, if we awaken, are less able to recollect any mental representation than during full-blown wakefulness (1). The mechanisms underpinning the reduction in conscious content during NREM sleep are still uncertain. Consciousness has been associated with the ability of a system to integrate information (2), which could be altered during NREM sleep. Here, in contrast to previous work (3, 4), we quantified changes in information integration from wakefulness to NREM sleep in large-scale brain networks and computed both their total integration and their degree of functional clustering. Functional clustering estimates how integration is hierarchically organized within and across the constituent parts of a system. It has been proposed as an empirically tractable measure for complexity of brain integration (5), which is considered a better estimate of the capacity to integrate information than total integration (6).We assessed brain functional connectivity on functional MRI (fMRI) data, which reflect the slow dynamics of local field potentials rather than instantaneous neural activities (7). Data were collected in a single nocturnal session in 13 participants who maintained periods of steady NREM sleep. At awakening, none of the subjects could recall any mental conscious content since sleep onset. From this dataset, we extracted for each subject two subsets of consecutive volumes recorded, respectively, during wakefulness and NREM sleep. Six spatially independent patterns, which we refer to as networks (Fig. 1A), were identified at the group level on wakefulness data, using a data-driven method (independent component analysis). These networks [visual (VIS), motor (MOT), default mode (DM), dorsal attentional (dATT), executive control (EC), and salience (SAL)] were previously identified in many studies investigating restingstate fMRI correlations in the literature (8-10). Network composition was very similar in data obtained during NREM sleep compared with wakefulness, in terms of within-networks areas distribution and Euclidian distance between networks (SI Results ...