347 research outputs found
REM sleep deprivation during 5 hours leads to an immediate REM sleep rebound and to suppression of non-REM sleep intensity
No full textNine healthy male subjects were deprived of REM sleep during the first 5 h after sleep onset. Afterwards recovery sleep was undisturbed. During the deprivation period the non-REM EEG power spectrum was reduced when compared to baseline for the frequencies up to 7 Hz, despite the fact that non-REM sleep was not experimentally disturbed. During the recovery interval a significant rebound of REM sleep was observed, which was only accompanied by a very slight increase of power in the lower non-REM EEG frequencies.
In order to control for intermittent wakefulness, the same subjects were subjected to non-REM sleep interruption during the first 5 h after sleep onset 2 weeks later. Again subsequent recovery sleep was undisturbed. The interventions resulted in a similar amount of wakefulness in both conditions. During the intervention period, the non-REM EEG power spectrum was only marginally reduced in the delta frequency range. REM sleep duration was only slightly reduced. During the recovery interval, however, a substantial increase in EEG power in the delta frequency range was noted, without notable changes in REM time.
It is concluded that an increased pressure for REM sleep results in longer REM episodes and a reduced intensity of non-REM sleep.
Correction: Melanopsin- and L-cone-induced pupil constriction is inhibited by S- and M-cones in humans (vol 115, pg 792, 2018)
No full textNEUROSCIENCE: Correction for "Melanopsin- and L-cone-induced pupil constriction is inhibited by S- and M-cones in humans," by Tom Woelders, Thomas Leenheers, Marijke C. M. Gordijn, Roelof A. Hut, Domien G. M. Beersma, and Emma J. Wams, which was first published January 8, 2018;10.1073/pnas.1716281115 (Proc Natl Acad Sci USA 115:792-797). The authors note that, due to a printer's error, three references were omitted from the references list in the article. Additionally, the original ref. 28 is identical to ref. 5. Therefore, original ref. 28 is removed and three references are added at the end of the complete references, which appear below.</p
Relations between depressed mood and vocal parameters before, during and after sleep deprivation: a circadian rhythm study
No full textThe mechanism underlying improvement after total sleep deprivation (TSD) was studied in 14 major depressed patients. The suggestions that (1) circadian processes and/or (2) dimensions of arousal may play a role in the response to TSD were investigated. Diurnal variation of depressed mood and of mood- and arousal-related vocal parameters was studied in relation to the effect of TSD on depressed mood and vocal parameters. During 3 baseline days, during TSD and 2 days after TSD vocal parameters and depressed mood were assessed 6 and 3 times daily respectively.
The mean fundamental frequency (frequency of vocal fold vibration, F0) (presumably reflecting aspects of arousal) as well as the range of the F0 (proposed to reflect sadness) showed a clear circadian pattern with a peak at about 4.00 p.m. TSD affected the circadian organization of the mean F0 and advanced the peak of the curve. After one night of subsequent sleep this effect disappeared. In addition, improvement after TSD coincided with an increase of the mean F0. The diurnal variation of mood before TSD predicted the mood response to TSD, whereas diurnal variation of vocal parameters did not. Moreover, circadian changes in vocal parameters were not related to changes in depressed mood. These findings suggest that the diurnal variations in mood and vocal parameters are regulated by different mechanisms. Data support the presumption that circadian as well as arousal processes are involved in the mood response to TSD. Circadian changes in vocal parameters due to TSD are not likely to reflect changes in the biological clock.
Sleep deprivation in bright and dim light: antidepressant effects on major depressive disorder
No full textTwenty-three patients with a major depressive disorder were deprived of a night’s sleep twice weekly, one week staying up in the dimly lit living room of the ward (< 60 lux), and one week in a brightly lit room (> 2000 lux). Immediate, but transient beneficial effects of sleep deprivation were observed primarily in eight patients (the ‘responders’). The immediate effects did not differ greatly for the two conditions, indicating that exposure to light at night is an implausible explanation for the antidepressant effects of total sleep deprivation. There was some evidence that the bright light condition led to a more prolonged improvement of the responders.
Total and Partial Sleep Deprivation in Clomipramine-Treated Endogenous Depressives
No full textImprovement in depression after total sleep deprivation (TSD) is, as a rule, followed by relapse after subsequent ad libitum sleep. This study is addressed to the question of how nocturnal partial sleep following TSD affects this relapse. Thirty endogenously depressed patients participated in the study. During the night after TSD, subjects were allowed sleep during one of three periods, i.e., unlimited sleep (11:00 p.m.-8:00 a.m.), early partial sleep (11:00 p.m.-3:00 a.m.), or late partial sleep (4:00 a.m.-8:00 a.m.). The hypothesis that partial sleep deprivation on the night following TSD prevents relapse has to be rejected. Relapse was inversely related to a drop in minimum rectal temperature during the night with unlimited or partial sleep, compared with minimum rectal temperature on the previous night.
Why and How Do We Model Circadian Rhythms?
No full textIn our attempts to understand the circadian system, we unavoidably rely on abstractions. Instead of describing the behavior of the circadian system in all its complexity, we try to derive basic features from which we form a global concept on how the system works. Such a basic concept is a model of reality. The author discusses why it is advantageous or even necessary to transform conceptual models into mathematical formulations. As examples to demonstrate those advantages, the author reviews 4 types of mathematical models: negative feedback models thought to operate within pacemaker cells, models on coupling between pacemaker cells to generate pacemaker output, oscillator models describing the behavior of the composite circadian pacemaker, and models describing how the circadian pacemaker influences behavior.
Erratum: Selective SWS suppression does not affect the time course of core body temperature in men (J. Sleep Res., Volume 1, Number 3, September 1992, pp. 201-204)
No full textDepression:The chronophysiological approach
No full textThe author discusses the different clinical phenomena which stimulate a chronophysiological approach; he illustrates in particular the role of sleep in depression. He then discusses the alternation between sleep and wakefulness and describes a model that has been proposed to explain its regulation.</p
Generation of activity-rest patterns by dual circadian pacemaker systems: a model
No full textActivity-rest patterns displayed by an animal under various circumstances are suggested to result from the combined influences of two virtually identical circadian pacemaker components. Increased output of each component proportionally increases the probability of activity of the animal. Such a dual circadian pacemaker model explains much of the phenomenology of activity-rest records. Under normal light-dark schedules, the two components of the model have a similar phase relationship to the Zeitgeber. Differential synchronization of the components to dawn and dusk is not assumed.
Changes of sleep EEG slow-wave activity in response to sleep manipulations: to what extent are they related to changes in REM sleep latency?
No full textSleep interventions may have direct effects on slow-wave activity (SWA, i.e. power of the sleep EEG signal in the 0.75-4.5 Hz range) as well as indirect ones caused by changes in REM sleep (REMS) latency. The effects of changes in REMS latency on SWA were investigated by analysing simulations with a mathematical model. Mean SWA in the first non-REMS episode shows an initial increase and a later decline as a function of REMS latency. In the second non-REMS episode, mean SWA decreases with increasing REMS latency. These results of the simulations were validated with experimental data.
In the evaluation of the effects of sleep interventions on SWA the effects of the timing of REMS have to be accounted for. The analysis of SWA over a sufficiently long constant amount of time spent in non-REMS proves to be relatively independent of REMS latency, which allows conclusions about the effects of sleep interventions on SWA per se.
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