According to the two-process model of sleep regulation, the timing and structure of sleep are determined by the interaction of a homeostatic and a circadian process. The original qualitative model was elaborated to quantitative versions that included the ultradian dynamics of sleep in relation to the non-REM-REM sleep cycle. The time course of EEG slow-wave activity, the major marker of non-REM sleep homeostasis, as well as daytime alertness were simulated successfully for a considerable number of experimental protocols. They include sleep after partial sleep deprivation and daytime napping, sleep in habitual short and long sleepers, and alertness in a forced desynchrony protocol or during an extended photoperiod. Simulations revealed that internal desynchronization can be obtained for different shapes of the thresholds. New developments include the analysis of the waking EEG to delineate homeostatic and circadian processes, studies of REM sleep homeostasis, and recent evidence for local, use-dependent sleep processes. Moreover, nonlinear interactions between homeostatic and circadian processes were identified. In the past two decades, models have contributed considerably to conceptualizing and analyzing the major processes underlying sleep regulation, and they are likely to play an important role in future advances in the field.

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Sleep homeostasis and models of sleep regulation

Delta power, a measure of EEG activity in the 1-4 Hz range, in slow-wave sleep (SWS) is in a quantitative and predictive relationship with prior wakefulness. Thus, sleep loss evokes a proportional increase in delta power, and excess sleep a decrease. Therefore, delta power is thought to reflect SWS need and its underlying homeostatically regulated recovery process. The neurophysiological substrate of this process is unknown and forward genetics might help elucidate the nature of what is depleted during wakefulness and recovered during SWS. We applied a mathematical method that quantifies the relationship between the sleep-wake distribution and delta power to sleep data of six inbred mouse strains. The results demonstrated that the rate at which SWS need accumulated varied greatly with genotype. This conclusion was confirmed in a "dose-response" study of sleep loss and changes in delta power; delta power strongly depended on both the duration of prior wakefulness and genotype. We followed the segregation of the rebound of delta power after sleep deprivation in 25 BXD recombinant inbred strains by quantitative trait loci (QTL) analysis. One "significant" QTL was identified on chromosome 13 that accounted for 49% of the genetic variance in this trait. Interestingly, the rate at which SWS need decreases did not vary with genotype in any of the 31 inbred strains studied. These results demonstrate, for the first time, that the increase of SWS need is under a strong genetic control, and they provide a basis for identifying genes underlying SWS homeostasis.

https://www.jneurosci.org/content/jneuro/21/8/2610.full.pdf

The Homeostatic Regulation of Sleep Need Is under Genetic Control

The aim of this study was to compare the effects of total sleep deprivation (TSD), rapid eye movement (REM) sleep and slow wave sleep (SWS) interruption and sleep recovery on mechanical and thermal pain sensitivity in healthy adults. Nine healthy male volunteers (age 26--43 years) were randomly assigned in this double blind and crossover study to undergo either REM sleep or SWS interruption. Periods of 6 consecutive laboratory nights separated by at least 2 weeks were designed as follows: N1 Adaptation night; N2 Baseline night; N3 Total sleep deprivation (40 h); N4 and N5 SWS or REM sleep interruption; N6 Recovery. Sleep was recorded and scored using standard methods. Tolerance thresholds to mechanical and thermal pain were assessed using an electronic pressure dolorimeter and a thermode operating on a Peltier principle. Relative to baseline levels, TSD decreased significantly mechanical pain thresholds (-8%). Both REM sleep and SWS interruption tended to decrease mechanical pain thresholds. Recovery sleep, after SWS interruption produced a significant increase in mechanical pain thresholds (+ 15%). Recovery sleep after REM sleep interruption did not significantly increase mechanical pain thresholds. No significant differences in thermal pain thresholds were detected between and within periods. In conclusion this experimental study in healthy adult volunteers has demonstrated an hyperalgesic effect related to 40 h TSD and an analgesic effect related to SWS recovery. The analgesic effect of SWS recovery is apparently greater than the analgesia induced by level I (World Health Organization) analgesic compounds in mechanical pain experiments in healthy volunteers.

https://onlinelibrary.wiley.com/doi/pdf/10.1046/j.1365-2869.2001.00240.x

The effects of total sleep deprivation, selective sleep interruption and sleep recovery on pain tolerance thresholds in healthy subjects.

Several theories claim that dreaming is a random by-product of REM sleep physiology and that it does not serve any natural function. Phenomenal dream content, however, is not as disorganized as such views imply. The form and content of dreams is not random but organized and selective: during dreaming, the brain constructs a complex model of the world in which certain types of elements, when compared to waking life, are underrepresented whereas others are over represented. Furthermore, dream content is consistently and powerfully modulated by certain types of waking experiences. On the basis of this evidence, I put forward the hypothesis that the biological function of dreaming is to simulate threatening events, and to rehearse threat perception and threat avoidance. To evaluate this hypothesis, we need to consider the original evolutionary context of dreaming and the possible traces it has left in the dream content of the present human population. In the ancestral environment human life was short and full of threats. Any behavioral advantage in dealing with highly dangerous events would have increased the probability of reproductive success. A dream-production mechanism that tends to select threatening waking events and simulate them over and over again in various combinations would have been valuable for the development and maintenance of threat-avoidance skills. Empirical evidence from normative dream content, children's dreams, recurrent dreams, nightmares, post traumatic dreams, and the dreams of hunter-gatherers indicates that our dream-production mechanisms are in fact specialized in the simulation of threatening events, and thus provides support to the threat simulation hypothesis of the function of dreaming.

https://www.unil.ch/files/live/sites/ln/files/shared/Revonsuo_1.pdf

The reinterpretation of dreams: An evolutionary hypothesis of the function of dreaming

STUDY OBJECTIVES: 

To examine the effects of total sleep deprivation on adolescent sleep and the sleep electroencephalogram (EEG) and to study aspects of sleep homeostasis.

DESIGN: Subjects were studied during baseline and recovery sleep after 36 hours of wakefulness.

SETTING: Four-bed sleep research laboratory.

PARTICIPANTS: Seven prepubertal or early pubertal children (pubertal stage Tanner 1 or 2 = Tanner 1/2; mean age 11.9 years, SD +/- 0.8, 2 boys) and 6 mature adolescents (Tanner 5; 14.2 years, +/- 1.4, 2 boys).

INTERVENTIONS: Thirty-six hours of sleep deprivation.

MEASUREMENTS: All-night polysomnography was performed. EEG power spectra (C3/A2) were calculated using a Fast Fourier transform routine.

RESULTS: 

In both groups, sleep latency was shorter, sleep efficiency was higher, non-rapid eye movement (NREM) sleep stage 4 was increased, and waking after sleep onset was reduced in recovery relative to baseline sleep. Spectral power of the NREM sleep EEG was enhanced after sleep deprivation in the low-frequency range (1.6-3.6 Hz in Tanner 1/2; 0.8-6.0 Hz in Tanner 5) and reduced in the sigma range (11-15 Hz). Sleep deprivation resulted in a stronger increase of slow-wave activity (EEG power 0.6-4.6 Hz, marker for sleep homeostatic pressure) in Tanner 5 (39% above baseline) than in Tanner 1/2 adolescents (18% above baseline). Sleep homeostasis was modeled according to the two-process model of sleep regulation. The build-up of homeostatic sleep pressure during wakefulness was slower in Tanner 5 adolescents (time constant of exponential saturating function 15.4 +/- 2.5 hours) compared with Tanner 1/2 children (8.9 +/- 1.2 hours). In contrast, the decline of the homeostatic process was similar in both groups.

CONCLUSION: 

Maturational changes of homeostatic sleep regulation are permissive of the sleep phase delay in the course of adolescence.

/pdf/homeostatic-sleep-regulation-in-adolescents-4wtrtjb1az.pdf

Homeostatic sleep regulation in adolescents.

To investigate rapid eye movement (REM) sleep regulation, eight healthy young men were deprived of REM sleep for three consecutive nights. In a three-night control sleep deprivation (CD) session 2 wk later, the subjects were repeatedly awakened from non-REM sleep in an attempt to match the awakenings during the REM sleep deprivation (RD) nights. During the RD nights the number of sleep interruptions required to prevent REM sleep increased within and across consecutive nights. REM sleep was reduced to 9.2% of baseline (CD nights: 80.7%) and rose to 140.1% in the first recovery night. RD gave rise to changes in the EEG power spectra of REM sleep. Power in the 8.25- to 11-Hz range was reduced in the first recovery night, an effect that gradually subsided but was still present in the third recovery night. The rising REM sleep propensity, as reflected by the increase of interventions within and across RD nights, and the moderate REM sleep rebound during recovery can be accounted for by a compensatory response that serves REM sleep homeostasis. The changes in the electroencephalogram power spectra, which were observed during enhanced REM sleep propensity, may be a sign of an altered quality of REM sleep.

Selective REM sleep deprivation in humans: effects on sleep and sleep EEG

Although sleep deprivation is known to exert an antidepressant effect in depressed patients, the involvement of sleep regulation is still unknown. Selective sleep deprivation experiments were performed in the rat to investigate the interactions between non-REM sleep (NREMS) and REM sleep (REMS) in an animal model. A12-h total sleep deprivation (TD) period ending at lights on was followed by one of the following protocols: (1) recovery sleep (TD12); (2) 4-h total sleep deprivation (TD16); (3) 4-h slow-wave deprivation (SWD); (4) 4-h REMS deprivation (RD). In the SWD protocol, the reduction of EEG slow-wave activity (SWA; power density in the 0.75-4.0 Hz band) was obtained by curtailing NREMS episodes to 20 s. During RD the number of interventions required to prevent REMS increased during the first 2 h and then remained constant. While RD caused only a minor reduction of NREMS, it increasingly suppressed SWA in NREMS. The rebound of SWA occurred later and was less prominent after RD than after SWD. Whereas an REMS rebound occurred after all three 4-h sleep deprivation protocols, a persistent increase in the dark period was present only after TD16. It is concluded that (a) SWA in NREMS is inhibited by an increased level of REMS propensity; (b) the hypothesis that REMS propensity increases only during NREMS is not supported; and (c) the results are compatible with the hypothesis that the suppression of NREMS intensity is the common denominator of different antidepressive sleep manipulations in depressive patients.

Selective and total sleep deprivation: effect on the sleep EEG in the rat

In the framework of a selective sleep deprivation study, eight young men were repeatedly awakened during 3 nights from nonREM sleep (nonREMS). The mean number of awakenings per night was 27.4, 29.5 and 32.8. In order to avoid excessive suppression of slow wave sleep, no awakening occurred in the first nonREMS episode. Compared to baseline, cycle 2 was significantly prolonged in all 3 nights, and cycle 3 in night 3 only. However, after subtracting the waking intervals, the differences from baseline was eliminated. The results show that the mechanisms underlying sleep cycle control keep track of sleep time and disregard epochs of waking.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1440-1819.1998.tb00988.x

Takuro Endo

Papers

Selective REM sleep deprivation in humans: effects on sleep and sleep EEG

Selective and total sleep deprivation: effect on the sleep EEG in the rat

Effect of frequent brief awakenings from nonREM sleep on the nonREM-REM sleep cycle.