Sleep and EEG spectra in the rabbit under baseline conditions and following sleep deprivation

Tobler, Irene; Franken, Paul; Scherschlicht, R.

doi:10.1016/0031-9384(90)90272-6

Cited by 43 publications

(28 citation statements)

References 33 publications

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“…Prominent delta band activity, such as slow waves (∼1 Hz) and wide-band delta (1-4 Hz) normally occur in NREM sleep but was also reported in REM sleep after acute sleep deprivation (20,28), similar to our finding on SR1, linking them to homeostatic processes. "Pure", narrow-band oscillations were also reported in the delta band during waking, at 3 Hz in motor cortex during isometric tracking (29) and in PFC at 2 Hz and 4 Hz, associated with specific cognitive tasks (17) and stimulation of brainstem arousal pathways (30).…”

Section: The Pattern Of Rem Sleep Rebound Is Mirrored In Eeg Slowsupporting

confidence: 77%

“…Slow oscillations (<15 Hz) repeated the behavioral pattern of REM sleep alterations (i.e., a persistent increase throughout SR1 to SR5, whereas high-frequency oscillations showed progressive increases over the course of CSR). CFC of slow and fast oscillations during REM sleep were preserved or even enhanced in CSR with a matching topography [i.e., a prominent (8-10 Hz) theta2-gamma2 (70-90 Hz)] nesting was detected in the areas overlaying the hippocampus, narrow-band delta range oscillations (2 and 4 Hz) were modulating gamma1 (35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45) in the PFC and a weaker slow (∼1 Hz) modulation of beta2 (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) was observed in the sensory-motor area. Collectively, these findings suggest that in REM sleep, slow oscillations closely following the behavioral pattern imposed by REM sleep regulation may serve to translate this top-down homeostatic control to a wide range of cortical networks whereas fast oscillations escaping this control might serve as an instrument granting relative independence for local ensembles to synchronize on shorter spatiotemporal scales.…”

Section: Discussionmentioning

confidence: 99%

“…Beta power (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). Overall, beta activity after SR1 was similar to BL but then gradually increased in subsequent days in the somatosensory cortex (not significant on SR1 and SR3; P = 0.009 on SR5; Table S3).…”

Section: Persistent Increase In Rem Sleep Time Rebounds After Repetitivementioning

confidence: 90%

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Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation

Kim

Kocsis

Hwang

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Homeostatic rebound in rapid eye movement (REM) sleep normally occurs after acute sleep deprivation, but REM sleep rebound settles on a persistently elevated level despite continued accumulation of REM sleep debt during chronic sleep restriction (CSR). Using highdensity EEG in mice, we studied how this pattern of global regulation is implemented in cortical regions with different functions and network architectures. We found that across all areas, slow oscillations repeated the behavioral pattern of persistent enhancement during CSR, whereas high-frequency oscillations showed progressive increases. This pattern followed a common rule despite marked topographic differences. The findings suggest that REM sleep slow oscillations may translate top-down homeostatic control to widely separated brain regions whereas fast oscillations synchronizing local neuronal ensembles escape this global command. These patterns of EEG oscillation changes are interpreted to reconcile two prevailing theories of the function of sleep, synaptic homeostasis and sleep dependent memory consolidation. There has been substantial recent progress in understanding the neuronal mechanisms of two seemingly unrelated but, more likely, complementary functions of sleep. The first, conceptualized as the synaptic homeostasis theory (1), produced experimental evidence for a global downscaling of synaptic strength during sleep to offset the unsustainable upscaling associated with neuronal activation during the preceding period of wakefulness (2). The second line of research keeps accumulating data to support an active role of sleep in offline memory processing (3) and argues that certain synapses not only escape global downscaling in sleep but instead are potentiated; firing rate and synchrony in select neuronal ensembles representing newly acquired and deemed relevant information are increased. The mechanisms of how these two proposed functions of sleep are reconciled on the network or ensemble level are poorly understood.From the very beginning, both processes were linked to specific oscillatory patterns of neuronal activity. The synaptic homeostasis hypothesis, and sleep homeostatic regulation in general, was correlated with EEG delta power (4) and memory consolidation was associated with episodic fast oscillations during non-REM (NREM) sleep (5). Recent evidence from network level investigations concur. On the one hand, different measures of homeostatic downscaling on the neuronal level (synaptic depotentiation, decrease in firing rate, decreased synchrony, etc.) were shown to correlate with the global decrease in delta power (6). On the other hand, reactivation of memory traces primarily occur during spindle-ripple events (7) and requires the temporal organization provided by local fast oscillations for coordination of firing within local neuronal ensembles.Slow and fast oscillations, respectively, support global and local processing, not only in NREM sleep but also in any brain state, in general. Slow oscillations (delta, theta, alpha, beta1) all...

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Section: The Pattern Of Rem Sleep Rebound Is Mirrored In Eeg Slowsupporting

confidence: 77%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation

Kim

Kocsis

Hwang

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…However, during REM, it occurs at higher frequencies (7-8 Hz) (Harper, 1971;Tobler et al, 1990) than during awake vigilance. Notably, the 5-7 Hz hippocampal theta activity that we used to define the 5 s alert periods just before transitions to nonalert periods showed, for all of the neurons studied here, peak frequencies of 5.25-6.25 Hz (Fig.…”

Section: Methodsmentioning

confidence: 99%

Getting Drowsy? Alert/Nonalert Transitions and Visual Thalamocortical Network Dynamics

Bereshpolova¹,

Stoelzel²,

Zhuang³

et al. 2011

J. Neurosci.

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The effects of different EEG brain states on spontaneous firing of cortical populations are not well understood. Such state shifts may occur frequently under natural conditions, and baseline firing patterns can impact neural coding (e.g., signal-to-noise ratios, sparseness of coding). Here, we examine the effects of spontaneous transitions from alert to nonalert awake EEG states in the rabbit visual cortex (5 s before and after the state-shifts). In layer 4, we examined putative spiny neurons and fast-spike GABAergic interneurons; in layer 5, we examined corticotectal neurons. We also examined the behavior of retinotopically aligned dorsal lateral geniculate nucleus (LGNd) neurons, usually recorded simultaneously with the above cortical populations. Despite markedly reduced firing and sharply increased bursting in the LGNd neurons following the transition to the nonalert state, little change occurred in the spiny neurons of layer 4. However, fast-spike neurons of layer 4 showed a paradoxical increase in firing rates as thalamic drive decreased in the nonalert state, even though some of these cells received potent monosynaptic input from the same LGNd neurons whose rates were reduced. The firing rates of corticotectal neurons of layer 5, similarly to spiny cells of layer 4, were not state-dependent, but these cells did become more bursty in the nonalert state, as did the fast-spike cells. These results show that spontaneous firing rates of midlayer spiny populations are remarkably conserved following the shift from alert to nonalert states, despite marked reductions in excitatory thalamic drive and increased activity in local fast-spike inhibitory interneurons.

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“…For example, the nocturnal Syrian hamster (Mesocricetus auratus) spends about 78% of the light period and 51% of the dark period sleeping (Tobler and Jaggi 1987), and Sprague-Dawley rats (an outbred strain from Rattus norvegicus) sleep during about 69% of the light period and 27% of the dark period (Franken et al 1991). The rabbit (family Leporidae) spends 55% of the light period and 40% of the dark period sleeping (Tobler et al 1990b), whereas the diurnal Siberian chipmunk (Tamias sibericus) sleeps during only 27.5% of the light period but spends 74% of the dark period sleeping (Dijk and Daan 1989). Guinea pigs (Cavia porcellus) seem to have little phase preference, spending 30% of the dark phase and 35% of the light phase asleep (Tobler et al 1993).…”

Section: Monophasic Versus Polyphasic Sleepmentioning

confidence: 99%

Biological Rhythms Workshop IC: Sleep and Rhythms

Münch

Cain²,

Duffy

2007

Cold Spring Harbor Symposia on Quantitative Biology

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Rhythms of sleep and wakefulness (typically measured as rest/activity rhythms) are among the most prominent of biological rhythms and therefore were among the first to be recorded in early chronobiological studies. These rhythms can provide useful information about the central biological clock, although an appreciation of the problems associated with using rest/activity to infer central clock function is important in the design and interpretation of chronobiological experiments in both animals and humans. Here, we review the anatomical and neurophysiologic bases of sleep regulation in mammals as well as similarities and differences between the sleep of humans and that of other organisms. We outline how human sleep is measured, the role of the circadian system in models of human sleep regulation, and human circadian rhythm sleep disorders. Although the function of sleep is still not completely understood, sleep has a critical role for human health, and we have attempted to outline the role that the circadian timing system has in regulating human sleep and in contributing to sleep disorders. Triple-plotted activity/rest record from a C57B6 mouse studied in DD. As is typical in mice, activity onset is earlier each day than the previous day, indicating a period shorter than 24 hours. (Upper half) Activity recordings are from a running wheel; (lower half) animal's running wheel was locked and the activity is from drinking at the water spout. The period was shorter when the animal was able to run in the wheel (23.05 hours vs. 23.50 hours), indicating that running-wheel activity was affecting the observed circadian period.ken by the chirping of early-rising diurnal birds or kept awake by noisy neighbors! The timing of a circadian-clock-controlled physiological or behavioral rhythm with respect to the LD cycle is referred to as the "phase angle of entrainment." One such example of a phase angle is the time of activity onset relative to dawn in diurnal animals. In the natural environment, this phase angle of entrainment is determined by the endogenous period of the clock and its sensitivity to the phase-shifting effects of light. Given that both the endogenous period and light sensitivity are not static, nor is the day-to-day exposure to environmental light, phase angle can take on very different values among species, among individuals within a species, and even within a single individual.

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Sleep and EEG spectra in the rabbit under baseline conditions and following sleep deprivation

Cited by 43 publications

References 33 publications

Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation

Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation

Getting Drowsy? Alert/Nonalert Transitions and Visual Thalamocortical Network Dynamics

Biological Rhythms Workshop IC: Sleep and Rhythms

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