It has been hypothesized that slow wave activity, a well established measure of sleep homeostasis that increases after waking and decreases after sleep, may reflect changes in cortical synaptic strength. If so, the amplitude of sensory evoked responses should also vary as a function of time awake and asleep in a way that reflects sleep homeostasis.
Using 256-channel, high-density electroencephalography (EEG) in 12 subjects, auditory evoked potentials (AEP) and spontaneous waking data were collected during wakefulness before and after sleep.
The amplitudes of the N1 and P2 waves of the AEP were reduced after a night of sleep. In addition, the decline in N1 amplitude correlated with low-frequency EEG power during non-rapid eye movement sleep and spontaneous wakefulness, both homeostatically regulated measures of sleep need.
The decline in AEP amplitude after a night of sleep may reflect a homeostatic reduction in synaptic strength.
These findings provide further evidence for a connection between synaptic plasticity and sleep homeostasis.
Auditory evoked potentials; sleep homeostasis; synaptic plasticity; slow wave sleep; N1 and P2; electroencephalogram
Sleep is regulated by a circadian clock that largely times sleep and wake to occur at specific times of day and a sleep homeostat that drives sleep as a function of duration of prior wakefulness. To better understand the role of the circadian clock in sleep regulation, we have been using the fruit fly Drosophila melanogaster. Fruit flies display all of the core behavioral features of sleep including relative immobility, elevated arousal thresholds and homeostatic regulation[2, 3]. We assessed sleep-wake modulation by a core set of 20 circadian pacemaker neurons that express the neuropeptide PDF. We find that PDF neuron ablation, loss of pdf or its receptor pdfr results in increased sleep during the late night in light:dark (LD) conditions and more prominent increases on the first subjective day of constant darkness (DD). Flies deploy similar genetic and neurotransmitter pathways to regulate sleep as their mammalian counterparts, including GABA. We find that RNAi-mediated knockdown of the GABAA receptor gene, Resistant to dieldrin (Rdl), in PDF neurons, reduced sleep consistent with a role for GABA in inhibiting PDF neuron function. Patch clamp electrophysiology reveals GABA-activated picrotoxin-sensitive chloride currents on PDF+ neurons. In addition, RDL is detectable most strongly on the large subset of PDF+ pacemaker neurons. These results suggest that GABAergic inhibition of arousal promoting PDF neurons is an important mode of sleep-wake regulation in vivo.
Starvation, which is common in the wild, appears to initiate a genetic program that allows fruitflies to remain awake without the sleepiness and cognitive impairments that typically follow sleep deprivation.
Extended periods of waking result in physiological impairments in humans, rats, and flies. Sleep homeostasis, the increase in sleep observed following sleep loss, is believed to counter the negative effects of prolonged waking by restoring vital biological processes that are degraded during sleep deprivation. Sleep homeostasis, as with other behaviors, is influenced by both genes and environment. We report here that during periods of starvation, flies remain spontaneously awake but, in contrast to sleep deprivation, do not accrue any of the negative consequences of prolonged waking. Specifically, the homeostatic response and learning impairments that are a characteristic of sleep loss are not observed following prolonged waking induced by starvation. Recently, two genes, brummer (bmm) and Lipid storage droplet 2 (Lsd2), have been shown to modulate the response to starvation. bmm mutants have excess fat and are resistant to starvation, whereas Lsd2 mutants are lean and sensitive to starvation. Thus, we hypothesized that bmm and Lsd2 may play a role in sleep regulation. Indeed, bmm mutant flies display a large homeostatic response following sleep deprivation. In contrast, Lsd2 mutant flies, which phenocopy aspects of starvation as measured by low triglyceride stores, do not exhibit a homeostatic response following sleep loss. Importantly, Lsd2 mutant flies are not learning impaired after sleep deprivation. These results provide the first genetic evidence, to our knowledge, that lipid metabolism plays an important role in regulating the homeostatic response and can protect against neuronal impairments induced by prolonged waking.
It is well established in humans that sleep deficits lead to adverse outcomes, including cognitive impairments and an increased risk for obesity. Given the relationship between sleep and lipid stores, we hypothesized that metabolic pathways play a role in sleep regulation and contribute to deficits induced by sleep loss. Since starvation has a large impact on metabolic pathways and is an environmental condition that is encountered by animals living in the wild, we examined its effects on sleep in the fruit fly Drosophila melanogaster. Interestingly, when flies are starved they display an immediate increase in waking. However, in contrast to sleep deprivation, waking induced by starvation does not result in increased sleepiness or impairments in short-term memory. To identify the mechanisms underlying these processes, we evaluated mutants for genes that have been shown to alter an animal's response to starvation. Interestingly, brummer mutants, which are fat, show an exaggerated response to sleep loss. In contrast, mutants for Lipid storage droplet 2 are lean and are able to stay awake without becoming sleepy or showing signs of cognitive impairment. These results indicate that while sleep loss can alter lipids, lipid enzymes may, in turn, play a role in regulating sleep and influence the response to sleep deprivation.
Sleep has been described as being of the brain, by the brain, and for the brain. This fundamental neurobiological behavior is controlled by homeostatic and circadian (24-hour) processes and is vital for normal brain function. This review will outline the normal sleep–wake cycle, the changes that occur during aging, and the specific patterns of sleep disturbance that occur in association with both mental health disorders and neurodegenerative disorders. The role of primary sleep disorders such as insomnia, obstructive sleep apnea, and REM sleep behavior disorder as potential causes or risk factors for particular mental health or neurodegenerative problems will also be discussed.
sleep; mental health; neurodegenerative disorders; cognition
The two-process model is a scheme for the timing of sleep that consists of homeostatic (Process S) and circadian (Process C) variables. The two-process model exhibits abnormal sleep patterns such as internal desynchronization or sleep fragmentation. Early infants with autism often experience sleep difficulties. Large day-by-day changes are found in the sleep onset and waking times in autistic children. Frequent night waking is a prominent property of their sleep. Further, the sleep duration of autistic children is often fragmented. These sleep patterns in infants with autism are not fully understood yet. In the present study, the sleep patterns in autistic children were reproduced by a modified two-process model using nonlinear analysis. A nap term was introduced into the original two-process model to reproduce the sleep patterns in early infants. The nap term and the time course of Process S are mentioned in the present study. Those parameters led to bifurcation of the sleep-wake cycle in the modified two-process model. In a certain range of these parameter sets, a small external noise was amplified, and an irregular sleep-wake cycle appeared. The short duration of sleep led to another irregular sleep onset or waking. Consequently, an irregular sleep-wake cycle appeared in early infantile autism.
Autism; Two-process model; Sleep cycle
The need to sleep grows with the duration of wakefulness and dissipates with time spent asleep, a process called sleep homeostasis. What are the consequences of staying awake on brain cells, and why is sleep needed? Surprisingly, we do not know whether the firing of cortical neurons is affected by how long an animal has been awake or asleep. Here we found that after sustained wakefulness cortical neurons fire at higher frequencies in all behavioral states. During early NREM sleep after sustained wakefulness, periods of population activity (ON) are short, frequent, and associated with synchronous firing, while periods of neuronal silence are long and frequent. After sustained sleep, firing rates and synchrony decrease, while the duration of ON periods increases. Changes in firing patterns in NREM sleep correlate with changes in slow-wave-activity, a marker of sleep homeostasis. Thus, the systematic increase of firing during wakefulness is counterbalanced by staying asleep.
slow wave sleep; slow oscillations; EEG; rat; cerebral cortex; multi-unit recording
Sleep is not just a passive process, but rather a highly dynamic process that is terminated by waking up. Throughout the night a specific number of sleep stages that are repeatedly changing in various periods of time take place. These specific time intervals and specific sleep stages are very important for the wake up event. It is far more difficult to wake up during the deep NREM (2–4) stage of sleep because the rest of the body is still sleeping. On the other hand if we wake up during the mild (REM, NREM1) sleep stage it is a much more pleasant experience for us and for our bodies. This problem led the authors to undertake this study and develop a Windows Mobile-based device application called wakeNsmile. The wakeNsmile application records and monitors the sleep stages for specific amounts of time before a desired alarm time set by users. It uses a built-in microphone and determines the optimal time to wake the user up. Hence, if the user sets an alarm in wakeNsmile to 7:00 and wakeNsmile detects that a more appropriate time to wake up (REM stage) is at 6:50, the alarm will start at 6:50. The current availability and low price of mobile devices is yet another reason to use and develop such an application that will hopefully help someone to wakeNsmile in the morning. So far, the wakeNsmile application has been tested on four individuals introduced in the final section.
sleep stages detection; hypnogram; Windows Mobile; FFT analysis
We take for granted the ability to fall asleep or to snap out of sleep into wakefulness, but these changes in behavioral state require specific switching mechanisms in the brain that allow well-defined state transitions. In this review, we examine the basic circuitry underlying the regulation of sleep and wakefulness, and discuss a theoretical framework wherein the interactions between reciprocal neuronal circuits enable relatively rapid and complete state transitions. We also review how homeostatic, circadian, and allostatic drives help regulate sleep state switching, and discuss how breakdown of the switching mechanism may contribute to sleep disorders such as narcolepsy.
Sleep is regulated by both a circadian and a homeostatic process. The homeostatic process reflects the duration of prior wakefulness: the longer one stays awake, the longer and/or more intense is subsequent sleep. In mammals, the best marker of the homeostatic sleep drive is slow wave activity (SWA), the electroencephalographic (EEG) power spectrum in the 0.5–4 Hz frequency range during non-rapid eye movement (NREM) sleep. In mammals, NREM sleep SWA is high at sleep onset, when sleep pressure is high, and decreases progressively to reach low levels in late sleep. Moreover, SWA increases further with sleep deprivation, when sleep also becomes less fragmented (the duration of sleep episodes increases, and the number of brief awakenings decreases). Although avian and mammalian sleep share several features, the evidence of a clear homeostatic response to sleep loss has been conflicting in the few avian species studied so far. The aim of the current study was therefore to ascertain whether established markers of sleep homeostasis in mammals are also present in the white-crowned sparrow (Zonotrichia leucophrys gambelii), a migratory songbird of the order Passeriformes. To accomplish this goal, we investigated amount of sleep, sleep time course, and measures of sleep intensity in 6 birds during baseline sleep and during recovery sleep following 6 hours of sleep deprivation.
Continuous (24 hours) EEG and video recordings were used to measure baseline sleep and recovery sleep following short-term sleep deprivation. Sleep stages were scored visually based on 4-sec epochs. EEG power spectra (0.5–25 Hz) were calculated on consecutive 4-sec epochs. Four vigilance states were reliably distinguished based on behavior, visual inspection of the EEG, and spectral EEG analysis: Wakefulness (W), Drowsiness (D), slow wave sleep (SWS) and rapid-eye movement (REM) sleep. During baseline, SWA during D, SWS, and NREM sleep (defined as D and SWS combined) was highest at the beginning of the major sleep period and declined thereafter. Moreover, peak SWA in both SWS and NREM sleep increased significantly immediately following sleep deprivation relative to baseline.
As in mammals, sleep deprivation in the white-crowned sparrow increases the intensity of sleep as measured by SWA.
The amount and timing of sleep and sleep architecture (sleep stages) are determined by several factors, important among which are the environment, circadian rhythms and time awake. Separating the roles played by these factors requires specific protocols, including the constant routine and altered sleep-wake schedules. Results from such protocols have led to the discovery of the factors that determine the amounts and distribution of slow wave and rapid eye movement sleep as well as to the development of models to determine the amount and timing of sleep. One successful model postulates two processes. The first is process S, which is due to sleep pressure (and increases with time awake) and is attributed to a 'sleep homeostat'. Process S reverses during slow wave sleep (when it is called process S'). The second is process C, which shows a daily rhythm that is parallel to the rhythm of core temperature. Processes S and C combine approximately additively to determine the times of sleep onset and waking. The model has proved useful in describing normal sleep in adults. Current work aims to identify the detailed nature of processes S and C. The model can also be applied to circumstances when the sleep-wake cycle is different from the norm in some way. These circumstances include: those who are poor sleepers or short sleepers; the role an individual's chronotype (a measure of how the timing of the individual's preferred sleep-wake cycle compares with the average for a population); and changes in the sleep-wake cycle with age, particularly in adolescence and aging, since individuals tend to prefer to go to sleep later during adolescence and earlier in old age. In all circumstances, the evidence that sleep times and architecture are altered and the possible causes of these changes (including altered S, S' and C processes) are examined.
Adolescence; chronotype; circadian rhythm; endogenous component; exogenous component; old age; sleep homeostat; time awake
Age-related changes in brain function include those affecting learning, memory, and sleep-wakefulness. Sleep-wakefulness is an essential behavior that results from the interaction of multiple brain regions, peptides and neurotransmitters. The biological function(s) of sleep, however, remains unknown, due to a paucity of information available at the cellular level. Aged rats exhibit alterations in the circadian and homeostatic influences associated with sleep-wake regulation. We recently showed that alterations in cortical profiles occur after timed bouts of spontaneous sleep in young rats. Examination of the cellular response to sleep-wake in old rats may thus provide insight(s) into the biological function(s) of sleep. To test this hypothesis, we monitored cortical profiles in the frontal cortex of young and old Sprague-Dawley rats after timed bouts of spontaneous sleep-wake behavior. Proteins were separated by two-dimensional electrophoresis (2-DE), visualized by fluorescent staining, imaged, and analyzed as a function of behavioral state and age. Old rats showed a 6-fold increase in total protein expression, independent of the behavioral state at sacrifice. When analyzed according to age and behavioral state, there was a decrease (~46%) in the number of phospho-spots present during SWS in aged animals. SWS-associated spots present only in old animals were associated with multiple functions including vesicular transport, cell signaling, oxidation state, cytoskeletal support, and energy metabolism. These data suggest that the intracellular response to the signaling associated with spontaneous sleep is affected by age and is consistent with the idea that the ability of sleep to fulfill its’ function(s) may become diminished with age.
two-dimensional electrophoresis (2DE); mass spectrometry; sleep-associated proteins; spontaneous sleep bouts; aging
The electrical activity of the brain does not only reflect the current level of arousal, ongoing behavior or involvement in a specific task, but is also influenced by what kind of activity, and how much sleep and waking occurred before. The best marker of sleep-wake history is the electroencephalogram (EEG) spectral power in slow frequencies (slow-wave activity, 0.5–4 Hz, SWA) during sleep, which is high after extended wakefulness and low after consolidated sleep. While sleep homeostasis has been well characterized in various species and experimental paradigms, the specific mechanisms underlying homeostatic changes in brain activity or their functional significance remain poorly understood. However, several recent studies in humans, rats and computer simulations shed light on the cortical mechanisms underlying sleep regulation. First, it was found that the homeostatic changes in SWA can be fully accounted for by the variations in amplitude and slope of EEG slow waves, which are in turn determined by the efficacy of cortico-cortical connectivity. Specifically, the slopes of sleep slow waves were steeper in early sleep compared to late sleep. Second, the slope of cortical evoked potentials, which is an established marker of synaptic strength, was steeper after waking and decreased after sleep. Furthermore, cortical long-term potentiation (LTP) was partially occluded if it was induced after a period of waking, but it could again be fully expressed after sleep. Finally, multiunit activity recordings during sleep revealed that cortical neurons fired more synchronously after waking, and less so after a period of consolidated sleep. The decline of all these electrophysiological measures - the slopes of slow waves and evoked potentials and neuronal synchrony – during sleep correlated with the decline of the traditional marker of sleep homeostasis, EEG SWA. Taken together, these data suggest that homeostatic changes in sleep EEG are the result of altered neuronal firing and synchrony, which in turn arise from changes in functional neuronal connectivity.
sleep homeostasis; synaptic homeostasis; multiunit activity; neurons; cortex
Sleep/wake and circadian rest-activity rhythms become irregular with age. Typical outcomes include fragmented sleep during the night, advanced sleep phase syndrome and increased daytime sleepiness. These changes lead to a reduction in the quality of life due to cognitive impairments and emotional stress. More importantly, severely disrupted sleep and circadian rhythms have been associated with an increase in disease susceptibility. Additionally, many of the same brain areas affected by neurodegenerative diseases include the sleep and wake promoting systems. Any advances in our knowledge of these sleep/wake and circadian networks are necessary to target neural areas or connections for therapy. This review will discuss research that uses molecular, behavioral, genetic and anatomical methods to further our understanding of the interaction of these systems.
aging; neurodegenerative; sleep; wake; circadian; disease
Human neonates spend the majority of their time sleeping. Despite the limited waking hours available for environmental exploration, the first few months of life are a time of rapid learning about the environment. The organization of neonate sleep differs qualitatively from adult sleep, and the unique characteristics of neonatal sleep may promote learning. Sleep contributes to infant learning in multiple ways. First, sleep facilitates neural maturation, thereby preparing infants to process and explore the environment in increasingly sophisticated ways. Second, sleep plays a role in memory consolidation of material presented while the infant was awake. Finally, emerging evidence indicates that infants process sensory stimuli and learn about contingencies in their environment even while asleep. As infants make the transition from reflexive to cortically mediated control, learned responses to physiological challenges during sleep may be critical adaptations to promote infant survival.
Sleep; Infant; Classical Conditioning; Associative Learning; Sleep States; SIDS
In near all animals, sleep is consistently concentrated to a specific time of the day. The timing and consolidation of sleep and wake bouts depend on the interplay between a homeostatic and a circadian processes of sleep regulation [1–3]. Sleep propensity rises as a homeostatic response to increasing wake time while a circadian clock determines the specific time when sleep will likely occur. This two-process regulation of sleep also determines which specific sleep stage will be manifested and specifically, the circadian process governs tightly the manifestation of rapid eye movement sleep (REMS) [1, 4]. The role of the hypothalamic suprachiasmatic nucleus (SCN) in the circadian gating of sleep and wakefulness has been unequivocally established by lesion studies  but its role in the timing of specific sleep stages has remained unknown. Using a forced desynchrony paradigm that induces the stable uncoupling of the ventrolateral (vl) and dorsomedial (dm) SCN, and a jetlag paradigm that induces a transient desynchronization between these SCN subregions we provide evidence that the SCN can time the occurrence of specific sleep stages. Specifically, the circadian regulation of REMS is associated with rhythmic clock gene expression within the dmSCN. Our results also provide the first neurophysiological model for the disruptions of sleep architecture that may result from temporal challenges such as rotational shift-work and transmeridional flights.
The regulation of sleep and wakefulness is well modeled with two underlying processes: a circadian and a homeostatic one. So far, the parameters and mechanisms of additional sleep-permissive and wake-promoting conditions have been largely overlooked. The present overview focuses on one of these conditions: the effect of skin temperature on the onset and maintenance of sleep, and alertness. Skin temperature is quite well suited to provide the brain with information on sleep-permissive and wake-promoting conditions because it changes with most if not all of them. Skin temperature changes with environmental heat and cold, but also with posture, environmental light, danger, nutritional status, pain, and stress. Its effect on the brain may thus moderate the efficacy by which the clock and homeostat manage to initiate or maintain sleep or wakefulness. The review provides a brief overview of the neuroanatomical pathways and physiological mechanisms by which skin temperature can affect the regulation of sleep and vigilance. In addition, current pitfalls and possibilities of practical applications for sleep enhancement are discussed, including the recent finding of impaired thermal comfort perception in insomniacs.
Sleep; Vigilance; Circadian rhythm; Homeostatic regulation; Thermoregulation; Thermosensitivity; Insomnia
Sleep complaints and poor sleep quality are common in the elderly population. The aim of this study was to determine factors associated with sleep complaints and poor sleep quality among older Mexican Americans over a 3-year period.
1085 non-institutionalized Mexican American aged 75 years and older. Sociodemographic characteristics, medical conditions, depressive symptoms, disability cognitive impairment, body mass index, sleep problems (trouble falling asleep, waking up several times per night, trouble staying asleep and awaking not rested) and overall sleep quality were obtained.
Of 1085 participants, 12.6% reported trouble falling asleep, 30% waking up several times per night, 11.4 % trouble staying asleep, 9.4% awaking not rested and 16.6% poor sleep quality. Depressive symptoms and heart attack predicted trouble falling asleep; diabetes, cancer and obesity predicted waking up several times per night; diabetes, hypertension, cancer and depressive symptoms predicted both trouble staying asleep and awaking not rested. Being female, married, heart attack and depressive symptoms were associated with poor quality sleep.
Different risk factors were associated with different aspects of sleep complaints. Since poor sleep has been linked to poor outcomes, a good understanding of these factors may help in designing interventions to improve sleep quality in this population.
Sleep; Quality; Older Adults; Mexican Americans
OBJECTIVES: Irregular working hours severely disturb sleep and wakefulness. This paper presents a modification of the quantitative (computerised) three process model of regulation of alertness to predict duration of sleep in connection with irregular sleep patterns. METHODS: The model uses a circadian "C" (sinusoidal) and homeostatic "S" (exponential) component (the duration of previous periods awake and asleep), which are summed to yield predicted alertness (on a scale of 1-16). It assumes that waking from sleep will occur at a given alertness level (S' + C') when recuperation is complete. Variables of electroencephalographic duration of sleep from two studies of irregular sleep were used to model the S and C variables in a regression approach to maximise prediction. The model performance was cross validated against published field and laboratory data. RESULTS: The model parameters were defined with a high degree of precision R2 = 0.99 and the validation yielded similar values R2 = 0.98-0.95, depending on the acrophase. The paper also describes a simplified graphical version of the computation model seen as a two dimensional duration of sleep nomogram. CONCLUSION: The model seems to predict group means for duration of sleep with high precision and may serve as a tool for evaluating work and rest schedules to reduce risks of sleep disturbances.
Increased attention to the prevalence of excessive sleepiness has led to a clear need to treat this symptom, thus reinforcing the need for a greater understanding of the neurobiology of sleep and wakefulness. Although the physiological mechanisms of sleep and wakefulness are highly interrelated, recent research reveals that there are distinct differences in the active brain processing and the specific neurochemical systems involved in the two states. In this review, we will examine the specific neuronal pathways, transmitters, and receptors composing the ascending arousal system that flow from the brainstem through the thalamus, hypothalamus, and basal forebrain to the cerebral cortex. We will also discuss the mutually inhibitory interaction between the core neuronal components of this arousal system and the sleep-active neurons in the ventrolateral preoptic nucleus, which serves as a brainstem-switch, regulating the stability of the sleep-wake states. In addition, we will review the role of homeostatic and circadian processes in the sleep-wake cycle, including the influence of the suprachiasmatic nucleus on coordination of sleep-wake systems. Finally, we will summarize how the above processes are reflected in disorders of sleep and wakefulness, including insomnia, narcolepsy, disorders associated with fragmented sleep, circadian rhythm sleep disorders, and primary neurological disorders such as Parkinson’s and Alzheimer’s diseases.
Excessive sleepiness; neurobiology; arousal system; sleep-wake states; circadian rhythm; sleep disorders.
Daily cycles of sleep/wake, hormones, and physiological processes are often misaligned with behavioral patterns during shift work, leading to an increased risk of developing cardiovascular/metabolic/gastrointestinal disorders, some types of cancer, and mental disorders including depression and anxiety. It is unclear how sleep timing, chronotype, and circadian clock gene variation contribute to adaptation to shift work.
Newly defined sleep strategies, chronotype, and genotype for polymorphisms in circadian clock genes were assessed in 388 hospital day- and night-shift nurses.
Night-shift nurses who used sleep deprivation as a means to switch to and from diurnal sleep on work days (∼25%) were the most poorly adapted to their work schedule. Chronotype also influenced efficacy of adaptation. In addition, polymorphisms in CLOCK, NPAS2, PER2, and PER3 were significantly associated with outcomes such as alcohol/caffeine consumption and sleepiness, as well as sleep phase, inertia and duration in both single- and multi-locus models. Many of these results were specific to shift type suggesting an interaction between genotype and environment (in this case, shift work).
Sleep strategy, chronotype, and genotype contribute to the adaptation of the circadian system to an environment that switches frequently and/or irregularly between different schedules of the light-dark cycle and social/workplace time. This study of shift work nurses illustrates how an environmental “stress” to the temporal organization of physiology and metabolism can have behavioral and health-related consequences. Because nurses are a key component of health care, these findings could have important implications for health-care policy.
Understanding the mechanisms that underlie the control of sleep and wakefulness is a major research area in neuroscience. This mini-symposium review highlights some recent developments at the gene, molecular, cellular, and systems level that have advanced this field. The studies discussed below utilize organisms ranging from flies to humans and focus on the interaction between the sleep homeostatic and circadian systems, the consequences of mutations in genes involved in the circadian clock on sleep timing, the effects of sleep deprivation on brain gene expression, the discovery of “sleep active” neurons in the cerebral cortex, the role of the hypocretin/orexin system in the maintenance of sleep and wakefulness, and the interaction between sleep and learning.
Skin potential levels and EEG changes were recorded in eight psychiatric patients during three nights of sleep. In a balanced design each patient took amylobarbitone sodium 200 mg, chlordiazepoxide 30 mg and placebo in turn. Skin potential did not distinguish between wakefulness and sleep as measured by the EEG nor did it clearly identify individual sleep stages. However, significant differences in skin potential were found between Awake and Stage I, between Awake and REM sleep and between REM sleep and Stage III/IV. The level was lowest during REM sleep but approached that of wakefulness during slow-wave sleep. These findings are discussed in terms of changes in arousal threshold during sleep. A cautious comment is made on the possible effects of psychiatric diagnoses and drugs.
Hypocretin-1 is a hypothalamic neuropeptide that is important in the regulation of wake and the lack of which results in the sleep disorder narcolepsy. Using a monkey that has consolidated wake akin to humans, we examined pharmacological manipulation of sleep and wake and its effects on hypocretin physiology. Monkeys were given the sleep-inducing gamma-hydroxybutyrate (GHB) and the wake-inducing modafinil both in the morning and in the evening. Cerebrospinal fluid (CSF) hypocretin-1 concentrations changed significantly in response to the drugs only when accompanied by a behavioral change (GHB-induced sleep in the morning or modafinil-induced wake in the evening). We also found that there was a large (180-fold) inter-individual variation in GHB pharmacokinetics that explains variability in sleep-induction in response to the drug. Our data indicate that the neurochemical concomitants of sleep and wake are capable of changing the physiological output of hypocretin neurons. Sleep independent of circadian timing is capable of decreasing CSF hypocretin-1 concentrations. Furthermore, hypocretin neurons do not appear to respond to an “effort” to remain awake, but rather keep track of time spent awake as a wake-promoting counterbalance to extended wakefulness.
orexin; hypocretin; sleep; pharmacology; modafinil; gamma-hydroxybutyrate
Sleep is regulated by circadian and homeostatic processes. Recent studies with mutant mice have indicated that circadian-related genes regulate sleep amount, as well as the timing of sleep. Thus a direct link between circadian and homeostatic regulation of sleep may exist, at least at the molecular level. Prokineticin 2 (PK2), which oscillates daily with high amplitude in the suprachiasmatic nuclei (SCN), has been postulated to be an SCN output molecule. In particular, mice lacking the PK2 gene (PK2−/−) have been shown to display significantly reduced rhythmicity for a variety of circadian physiological and behavioral parameters. We investigated the role of PK2 in sleep regulation.
EEG/EMG sleep-wake patterns were recorded in PK2−/− mice and their wild-type littermate controls under baseline and challenged conditions.
Measurements and Results
PK2−/− mice exhibited reduced total sleep time under entrained light-dark and constant darkness conditions. The reduced sleep time in PK2−/− mice occurred predominantly during the light period and was entirely due to a decrease in non-rapid eye movement (NREM) sleep time. However, PK2−/− mice showed increased rapid eye movement (REM) sleep time in both light and dark periods. After sleep deprivation, compensatory rebound in NREM sleep, REM sleep, and EEG delta power was attenuated in PK2−/− mice. In addition, PK2−/− mice had an impaired response to sleep disturbance caused by cage change in the light phase.
These results indicate that PK2 plays roles in both circadian and homeostatic regulation of sleep. PK2 may also be involved in maintaining the awake state in the presence of behavioral challenges.
Sleep; prokineticin 2; sleep homeostasis; circadian genes; EEG; behavioral challenge
There is a general consensus that sleep is strictly linked to memory, learning, and, in general, to the mechanisms of neural plasticity, and that this link may directly affect recovery processes. In fact, a coherent pattern of empirical findings points to beneficial effect of sleep on learning and plastic processes, and changes in synaptic plasticity during wakefulness induce coherent modifications in EEG slow wave cortical topography during subsequent sleep. However, the specific nature of the relation between sleep and synaptic plasticity is not clear yet. We reported findings in line with two models conflicting with respect to the underlying mechanisms, that is, the “synaptic homeostasis hypothesis” and the “consolidation” hypothesis, and some recent results that may reconcile them. Independently from the specific mechanisms involved, sleep loss is associated with detrimental effects on plastic processes at a molecular and electrophysiological level. Finally, we reviewed growing evidence supporting the notion that plasticity-dependent recovery could be improved managing sleep quality, while monitoring EEG during sleep may help to explain how specific rehabilitative paradigms work. We conclude that a better understanding of the sleep-plasticity link could be crucial from a rehabilitative point of view.