Conscious experiences and high-density EEG patterns predicting subjective sleep depth.

What accounts for feeling deeply asleep? Standard sleep recordings only incompletely reflect subjective aspects of sleep and some individuals with so-called sleep misperception frequently feel awake although sleep recordings indicate clear-cut sleep. To identify the determinants of sleep perception, we performed 787 awakenings in 20 good sleepers and 10 individuals with sleep misperception and interviewed them about their subjective sleep depth while they underwent high-density EEG sleep recordings. Surprisingly, in good sleepers, sleep was subjectively lightest in the first 2 h of non-rapid eye movement (NREM) sleep, generally considered the deepest sleep, and deepest in rapid eye movement (REM) sleep. Compared to good sleepers, sleep misperceptors felt more frequently awake during sleep and reported lighter REM sleep. At the EEG level, spatially widespread high-frequency power was inversely related to subjective sleep depth in NREM sleep in both groups and in REM sleep in misperceptors. Subjective sleep depth positively correlated with dream-like qualities of reports of mental activity. These findings challenge the widely held notion that slow wave sleep best accounts for feeling deeply asleep. Instead, they indicate that subjective sleep depth is inversely related to a neurophysiological process that predominates in early NREM sleep, becomes quiescent in REM sleep, and is reflected in high-frequency EEG activity. In sleep misperceptors, this process is more frequently active, more spatially widespread, and abnormally persists into REM sleep. These findings help identify the neuromodulatory systems involved in subjective sleep depth and are relevant for studies aiming to improve subjective sleep quality.

Cortico-autonomic local arousals and heightened somatosensory arousability during NREMS of mice in neuropathic pain.

Frequent nightly arousals typical for sleep disorders cause daytime fatigue and present health risks. As such arousals are often short, partial, or occur locally within the brain, reliable characterization in rodent models of sleep disorders and in human patients is challenging. We found that the EEG spectral composition of non-rapid eye movement sleep (NREMS) in healthy mice shows an infraslow (~50 s) interval over which microarousals appear preferentially. NREMS could hence be vulnerable to abnormal arousals on this time scale. Chronic pain is well-known to disrupt sleep. In the spared nerve injury (SNI) mouse model of chronic neuropathic pain, we found more numerous local cortical arousals accompanied by heart rate increases in hindlimb primary somatosensory, but not in prelimbic, cortices, although sleep macroarchitecture appeared unaltered. Closed-loop mechanovibrational stimulation further revealed higher sensory arousability. Chronic pain thus preserved conventional sleep measures but resulted in elevated spontaneous and evoked arousability. We develop a novel moment-to-moment probing of NREMS vulnerability and propose that chronic pain-induced sleep complaints arise from perturbed arousability.

Electroencephalographic changes associated with subjective under- and overestimation of sleep duration.

Feeling awake although sleep recordings indicate clear-cut sleep sometimes occurs in good sleepers and to an extreme degree in patients with so-called paradoxical insomnia. It is unknown what underlies sleep misperception, as standard polysomnographic (PSG) parameters are often normal in these cases. Here we asked whether regional changes in brain activity could account for the mismatch between objective and subjective total sleep times (TST). To set cutoffs and define the norm, we first evaluated sleep perception in a population-based sample, consisting of 2,092 individuals who underwent a full PSG at home and estimated TST the next day. We then compared participants with a low mismatch (normoestimators, n = 1,147, ±0.5 SD of mean) with those who severely underestimated (n = 52, <2.5th percentile) or overestimated TST (n = 53, >97.5th percentile). Compared with normoestimators, underestimators displayed higher electroencephalographic (EEG) activation (beta/delta power ratio) in both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, while overestimators showed lower EEG activation (significant in REM sleep). To spatially map these changes, we performed a second experiment, in which 24 healthy subjects and 10 insomnia patients underwent high-density sleep EEG recordings. Similarly to underestimators, patients displayed increased EEG activation during NREM sleep, which we localized to central-posterior brain areas. Our results indicate that a relative shift from low- to high-frequency spectral power in central-posterior brain regions, not readily apparent in conventional PSG parameters, is associated with underestimation of sleep duration. This challenges the concept of sleep misperception, and suggests that instead of misperceiving sleep, insomnia patients may correctly perceive subtle shifts toward wake-like brain activity.

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice.

Three vigilance states dominate mammalian life: wakefulness, non-rapid eye movement (non-REM) sleep, and REM sleep. As more neural correlates of behavior are identified in freely moving animals, this three-fold subdivision becomes too simplistic. During wakefulness, ensembles of global and local cortical activities, together with peripheral parameters such as pupillary diameter and sympathovagal balance, define various degrees of arousal. It remains unclear the extent to which sleep also forms a continuum of brain states-within which the degree of resilience to sensory stimuli and arousability, and perhaps other sleep functions, vary gradually-and how peripheral physiological states co-vary. Research advancing the methods to monitor multiple parameters during sleep, as well as attributing to constellations of these functional attributes, is central to refining our understanding of sleep as a multifunctional process during which many beneficial effects must be executed. Identifying novel parameters characterizing sleep states will open opportunities for novel diagnostic avenues in sleep disorders. We present a procedure to describe dynamic variations of mouse non-REM sleep states via the combined monitoring and analysis of electroencephalogram (EEG)/electrocorticogram (ECoG), electromyogram (EMG), and electrocardiogram (ECG) signals using standard polysomnographic recording techniques. Using this approach, we found that mouse non-REM sleep is organized into cycles of coordinated neural and cardiac oscillations that generate successive 25-s intervals of high and low fragility to external stimuli. Therefore, central and autonomic nervous systems are coordinated to form behaviorally distinct sleep states during consolidated non-REM sleep. We present surgical manipulations for polysomnographic (i.e., EEG/EMG combined with ECG) monitoring to track these cycles in the freely sleeping mouse, the analysis to quantify their dynamics, and the acoustic stimulation protocols to assess their role in the likelihood of waking up. Our approach has already been extended to human sleep and promises to unravel common organizing principles of non-REM sleep states in mammals.

Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep.

Rodents sleep in bouts lasting minutes; humans sleep for hours. What are the universal needs served by sleep given such variability? In sleeping mice and humans, through monitoring neural and cardiac activity (combined with assessment of arousability and overnight memory consolidation, respectively), we find a previously unrecognized hallmark of sleep that balances two fundamental yet opposing needs: to maintain sensory reactivity to the environment while promoting recovery and memory consolidation. Coordinated 0.02-Hz oscillations of the sleep spindle band, hippocampal ripple activity, and heart rate sequentially divide non-rapid eye movement (non-REM) sleep into offline phases and phases of high susceptibility to external stimulation. A noise stimulus chosen such that sleeping mice woke up or slept through at comparable rates revealed that offline periods correspond to raising, whereas fragility periods correspond to declining portions of the 0.02-Hz oscillation in spindle activity. Oscillations were present throughout non-REM sleep in mice, yet confined to light non-REM sleep (stage 2) in humans. In both species, the 0.02-Hz oscillation predominated over posterior cortex. The strength of the 0.02-Hz oscillation predicted superior memory recall after sleep in a declarative memory task in humans. These oscillations point to a conserved function of mammalian non-REM sleep that cycles between environmental alertness and internal memory processing in 20- to 25-s intervals. Perturbed 0.02-Hz oscillations may cause memory impairment and ill-timed arousals in sleep disorders.

Suppression of Sleep Spindle Rhythmogenesis in Mice with Deletion of CaV3.2 and CaV3.3 T-type Ca(2+) Channels.

STUDY OBJECTIVES: Low-threshold voltage-gated T-type Ca(2+) channels (T-channels or CaV3 channels) sustain oscillatory discharges of thalamocortical (TC) and nucleus Reticularis thalami (nRt) cells. The CaV3.3 subtype dominates nRt rhythmic bursting and mediates a substantial fraction of spindle power in the NREM sleep EEG. CaV3.2 channels are also found in nRt, but whether these contribute to nRt-dependent spindle generation is unexplored. We investigated thalamic rhythmogenesis in mice lacking this subtype in isolation (CaV3.2KO mice) or in concomitance with CaV3.3 deletion (CaV3.double-knockout (DKO) mice). METHODS: We examined discharge characteristics of thalamic cells and intrathalamic evoked synaptic transmission in brain slices from wild-type, CaV3.2KO and CaV3.DKO mice through patch-clamp recordings. The sleep profile of freely behaving CaV3.2KO and CaV3.DKO mice was assessed by polysomnographic recordings. RESULTS: CaV3.2 channel deficiency left nRt discharge properties largely unaltered, but additional deletion of CaV3.3 channels fully abolished low-threshold whole-cell Ca(2+) currents and bursting, and suppressed burst-mediated inhibitory responses in TC cells. CaV3.DKO mice had more fragmented sleep, with shorter NREM sleep episodes and more frequent microarousals. The NREM sleep EEG power spectrum displayed a relative suppression of the σ frequency band (10-15 Hz), which was accompanied by an increase in the δ band (1-4 Hz). CONCLUSIONS: Consistent with previous findings, CaV3.3 channels dominate nRt rhythmogenesis, but the lack of CaV3.2 channels further aggravates neuronal, synaptic, and EEG deficits. Therefore, CaV3.2 channels can boost intrathalamic synaptic transmission, and might play a modulatory role adjusting the relative presence of NREM sleep EEG rhythms.

Phasic, nonsynaptic GABA-A receptor-mediated inhibition entrains thalamocortical oscillations.

GABA-A receptors (GABA-ARs) are typically expressed at synaptic or nonsynaptic sites mediating phasic and tonic inhibition, respectively. These two forms of inhibition conjointly control various network oscillations. To disentangle their roles in thalamocortical rhythms, we focally deleted synaptic, γ2 subunit-containing GABA-ARs in the thalamus using viral intervention in mice. After successful removal of γ2 subunit clusters, spontaneous and evoked GABAergic synaptic currents disappeared in thalamocortical cells when the presynaptic, reticular thalamic (nRT) neurons fired in tonic mode. However, when nRT cells fired in burst mode, slow phasic GABA-AR-mediated events persisted, indicating a dynamic, burst-specific recruitment of nonsynaptic GABA-ARs. In vivo, removal of synaptic GABA-ARs reduced the firing of individual thalamocortical cells but did not abolish slow oscillations or sleep spindles. We conclude that nonsynaptic GABA-ARs are recruited in a phasic manner specifically during burst firing of nRT cells and provide sufficient GABA-AR activation to control major thalamocortical oscillations.

As the world turns: short-term human spatial memory in egocentric and allocentric coordinates.

We aimed to determine whether human subjects' reliance on different sources of spatial information encoded in different frames of reference (i.e., egocentric versus allocentric) affects their performance, decision time and memory capacity in a short-term spatial memory task performed in the real world. Subjects were asked to play the Memory game (a.k.a. the Concentration game) without an opponent, in four different conditions that controlled for the subjects' reliance on egocentric and/or allocentric frames of reference for the elaboration of a spatial representation of the image locations enabling maximal efficiency. We report experimental data from young adult men and women, and describe a mathematical model to estimate human short-term spatial memory capacity. We found that short-term spatial memory capacity was greatest when an egocentric spatial frame of reference enabled subjects to encode and remember the image locations. However, when egocentric information was not reliable, short-term spatial memory capacity was greater and decision time shorter when an allocentric representation of the image locations with respect to distant objects in the surrounding environment was available, as compared to when only a spatial representation encoding the relationships between the individual images, independent of the surrounding environment, was available. Our findings thus further demonstrate that changes in viewpoint produced by the movement of images placed in front of a stationary subject is not equivalent to the movement of the subject around stationary images. We discuss possible limitations of classical neuropsychological and virtual reality experiments of spatial memory, which typically restrict the sensory information normally available to human subjects in the real world.