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Slow-wave sleep

About: Slow-wave sleep is a research topic. Over the lifetime, 6543 publications have been published within this topic receiving 320663 citations. The topic is also known as: deep sleep.


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Journal ArticleDOI
TL;DR: Results are consistent with a hypothesis that the activation of sleep-related warm-sensitive neurons and the deactivation of wake-related cold-sensitive neuron may play a key role in the onset and regulation of NREM sleep.
Abstract: Thermosensitive neurons of the preoptic/anterior hypothalamic area (POAH) have been implicated in the regulation of non-rapid eye movement (NREM) sleep. We attempted to identify those medial POAH thermosensitive neurons that may be involved in NREM sleep regulation. The thermosensitivity of medial POAH neurons was studied in five freely moving adult cats by local cooling or warming of the medial POAH with a water-perfused thermode. Of 308 neurons, 65 (21%) were classified as thermosensitive, including 31 (10%) warm-sensitive and 34 (11%) cold-sensitive neurons. The spontaneous discharge rates of 28 warm-sensitive, 34 cold-sensitive, and 115 randomly selected thermoinsensitive neurons were recorded through one to three sleep-waking cycles. Patterns of spontaneous activity for warm- and cold-sensitive neurons were different. Of 28 warm-sensitive neurons, 18 (64%) exhibited increased discharge rate during NREM sleep compared with waking (NREM/wake, > or = 1.2). This subpopulation of warm-sensitive neurons also exhibited significantly increased thermosensitivity when tested during NREM sleep. Of 34 cold-sensitive neurons, 25 (74%) discharged more slowly during NREM sleep compared with waking (NREM/wake, < or = 0.8). This subpopulation of cold-sensitive neurons exhibited decreased thermosensitivity during NREM sleep. These results are consistent with a hypothesis that the activation of sleep-related warm-sensitive neurons and the deactivation of wake-related cold-sensitive neurons may play a key role in the onset and regulation of NREM sleep.

132 citations

Journal ArticleDOI
01 Apr 2010-Sleep
TL;DR: Based on a recent thalamocortical computer model, these findings may indicate a greater synaptic strength of neurons involved in the generation of sleep slow waves in prepubertal children, compared with mature adolescents.
Abstract: THE MOST PROMINENT ELECTROENCEPHALOGRAPHIC (EEG) CHARACTERISTIC OF DEEP NON-RAPID EYE MOVEMENT (NREM) SLEEP IS SLOW WAVES. THE neuronal correlate of slow waves is the slow oscillation first described in detail by Steriade and coworkers, who showed that membrane potentials of cortical neurons alternate about every second between a depolarized upstate and a hyperpolarized downstate during slow oscillations.1 When these oscillations are near synchronous and involve the majority of the cortical neurons in a given region, they become visible in the surface EEG as slow waves of large amplitude. The alternation of upstates and downstates in cortical neurons is thought to be involved in memory consolidation,2,3 synaptic homeostasis,4 and the recuperative function of sleep.5 Slow waves in the sleep EEG undergo dramatic changes during brain maturation. As early as the 1980s, Feinberg and colleagues reported that the amplitude of slow waves increases until shortly before puberty and then shows a prominent decrease across adolescence.6 Sleep slow-wave activity (SWA, EEG spectral power between 0.5 and 4.5 Hz), a quantitative measure of the activity in the slow-wave frequency range reflecting the homeostatic regulation of sleep,5 follows a similar time course. SWA sharply declines across puberty,7–9 followed by a smaller decrease during the twenties.6,10 The brain undergoes striking morphologic and functional changes during early human development.11–13 For example, Huttenlocher and Dabholkar11 reported that maximum cortical synapse density is achieved shortly before puberty. Furthermore, the course of adolescence is accompanied by a reduction in density of synapses in the grey matter, a process termed pruning.14–17 Longitudinal neuroimaging findings of cortical maturation corroborate these findings and reveal concomitant changes in grey matter. For instance, grey-matter volume has been shown to be greatest in frontal regions of the cortex around early puberty and to decrease thereafter.18,19 With the exception of the temporal lobe, the majority of the other cortical areas show a similar time course.18 In view of the similar time course of cortical synapse density and the amplitude of sleep slow waves, some authors have proposed a link between the two.6,8,9 In fact, recent computer simulations of the thalamocortical system have provided evidence for an association of the number and strength of synapses involved in the generation of sleep slow waves and their amplitude.20 In this simulation, the morphology of sleep slow waves changed as a function of the level of synchronization of cortical neurons. The synchronization level, on the other hand, depended on synaptic strength and synaptic density. Thus, the stronger and denser synapses are on neurons of a certain population, the faster those neurons can synchronize their activity; the faster they show synchronized activity, the steeper is the resulting potential change within that population. It is those potential changes that are measured by EEG recordings.21 Therefore, this computer model implied that the slope of slow waves is a good measure of the synchronization level of the neurons in the cortex, i.e., the slope of slow waves may represent a direct electrophysiological measure of changes in synaptic strength or density.20 On the basis of this observation, we hypothesized that the higher slow-wave amplitude in prepubertal children, compared with mature adolescents, results from higher synaptic strength or density, which should also be seen as a steeper slope of sleep slow waves. Therefore, we compare the characteristics of sleep slow waves in prepubertal children and mature adolescents. With this study, we propose the analysis of slow-wave characteristics as a novel approach to assessing developmental differences in overall cortical structure with possible functional associations.

132 citations

Journal ArticleDOI
TL;DR: It is suggested that human sleep can be characterized by the coexistence of wake-like and sleep-like electroencephalographic patterns in different cortical areas, supporting the hypothesis that unusual phenomena, such as NREM parasomnias, could result from an imbalance of these two states.

132 citations

Journal ArticleDOI
TL;DR: The data indicate that in a task that allows separating the contribution of explicit and implicit memory, sleep particularly supports explicit memory formation and the mechanism of this effect appears to be linked to SWS.
Abstract: Recognition memory is considered to be supported by two different memory processes, i.e., the explicit recollection of information about a previous event and an implicit process of recognition based on an acontextual sense of familiarity. Both types of memory supposedly rely on distinct memory systems. Sleep is known to enhance the consolidation of memories, with the different sleep stages affecting different types of memory. In the present study, we used the process-dissociation procedure to compare the effects of sleep on estimates of explicit (recollection) and implicit (familiarity) memory formation on a word-list discrimination task. Subjects studied two lists of words before a 3-h retention interval of sleep or wakefulness, and recognition was tested afterward. The retention intervals were positioned either in the early night when sleep is dominated by slow-wave sleep (SWS), or in the late night, when sleep is dominated by REM sleep. Sleep enhanced explicit recognition memory, as compared with wakefulness (P < 0.05), whereas familiarity was not affected by sleep. Moreover, explicit recognition was particularly enhanced after sleep in the early-night retention interval, and especially when the words were presented with the same contextual features as during learning, i.e., in the same font (P < 0.05). The data indicate that in a task that allows separating the contribution of explicit and implicit memory, sleep particularly supports explicit memory formation. The mechanism of this effect appears to be linked to SWS.

132 citations

Journal ArticleDOI
TL;DR: This work investigated the dynamics of sleep stages over the night and of heart-rate variability during the different sleep stages to create a model for the temporal sequence ofSleep stages and wake states.

131 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202364
2022103
2021171
2020163
2019166
2018152