Showing papers on "Slow-wave sleep published in 2008"

Slow-wave sleep and the risk of type 2 diabetes in humans

Abstract: There is convincing evidence that, in humans, discrete sleep stages are important for daytime brain function, but whether any particular sleep stage has functional significance for the rest of the body is not known. Deep non-rapid eye movement (NREM) sleep, also known as slow-wave sleep (SWS), is thought to be the most “restorative” sleep stage, but beneficial effects of SWS for physical well being have not been demonstrated. The initiation of SWS coincides with hormonal changes that affect glucose regulation, suggesting that SWS may be important for normal glucose tolerance. If this were so, selective suppression of SWS should adversely affect glucose homeostasis and increase the risk of type 2 diabetes. Here we show that, in young healthy adults, all-night selective suppression of SWS, without any change in total sleep time, results in marked decreases in insulin sensitivity without adequate compensatory increase in insulin release, leading to reduced glucose tolerance and increased diabetes risk. SWS suppression reduced delta spectral power, the dominant EEG frequency range in SWS, and left other EEG frequency bands unchanged. Importantly, the magnitude of the decrease in insulin sensitivity was strongly correlated with the magnitude of the reduction in SWS. These findings demonstrate a clear role for SWS in the maintenance of normal glucose homeostasis. Furthermore, our data suggest that reduced sleep quality with low levels of SWS, as occurs in aging and in many obese individuals, may contribute to increase the risk of type 2 diabetes.

Sleep disturbances in patients with schizophrenia : impact and effect of antipsychotics.

Abstract: Difficulties initiating or maintaining sleep are frequently encountered in patients with schizophrenia. Disturbed sleep can be found in 30–80% of schizophrenic patients, depending on the degree of psychotic symptomatology. Measured by polysomnography, reduced sleep efficiency and total sleep time, as well as increased sleep latency, are found in most patients with schizophrenia and appear to be an important part of the pathophysiology of this disorder. Some studies also reported alterations of stage 2 sleep, slow-wave sleep (SWS) and rapid eye movement (REM) sleep variables, i.e. reduced REM latency and REM density. A number of sleep parameters, such as the amount of SWS and the REM latency, are significantly correlated to clinical variables, including severity of illness, positive symptoms, negative symptoms, outcome, neurocognitive impairment and brain structure. Concerning specific sleep disorders, there is some evidence that schizophrenic patients carry a higher risk of experiencing a sleep-related breathing disorder, especially those demonstrating the known risk factors, including being overweight but also long-term use of antipsychotics. However, it is still unclear whether periodic leg movements in sleep or restless legs syndrome (RLS) are found with a higher or lower prevalence in schizophrenic patients than in healthy controls. There are no consistent effects of first-generation antipsychotics on measuresof sleep continuity and sleep structure, including the percentage of sleep stages or sleep and REM latency in healthy controls. In contrast to first-generation antipsychotics, the studied atypical antipsychotics (clozapine, olanzapine, quetiapine, risperidone, ziprasidone and paliperidone) demonstrate a relatively consistent effect on measures of sleep continuity, with an increase in either total sleep time (TST) or sleep efficiency, and individually varying effects on other sleep parameters, such as an increase in REM latency observed for olanzapine, quetiapine and ziprasidone, and an increase in SWS documented for olanzapine and ziprasidone in healthy subjects. The treatment of schizophrenic patients with first-generation antipsychotics is consistently associated with an increase in TST and sleep efficiency, and mostly an increase in REM latency, whereas the influence on specific sleep stages is more variable. On the other hand, withdrawal of such treatment is followed by a change in sleep structure mainly in the opposite direction, indicating a deterioration of sleep quality. On the background of the rather inconsistent effects of first-generation antipsychotics observed in healthy subjects, it appears possible that the high-potency drugs exert their effects on sleep in schizophrenic patients, for the most part, in an indirect way by suppressing stressful psychotic symptomatology. In contrast, the available data concerning second-generation antipsychotics (clozapine, olanzapine, risperidone and paliperidone) demonstrate a relatively consistent effect on measures of sleep continuity in patients and healthy subjects, with an increase in TST and sleep efficiency or a decrease in wakefulness. Additionally, clozapine and olanzapine demonstrate comparable influences on other sleep variables, such as SWS or REM density, in controls and schizophrenic patients. Possibly, the effects of second-generation antipsychotics observed on sleep in healthy subjects and schizophrenic patients might involve the action of these drugs on symptomatology, such as depression, cognitive impairment, and negative and positive symptoms. Specific sleep disorders, such as RLS, sleep-related breathing disorders, night-eating syndrome, somnambulism and rhythm disorders have been described as possible adverse effects of antipsychotics and should be considered in the differential diagnosis of disturbed or unrestful sleep in this population.

Spontaneous neural activity during human slow wave sleep

Abstract: Slow wave sleep (SWS) is associated with spontaneous brain oscillations that are thought to participate in sleep homeostasis and to support the processing of information related to the experiences of the previous awake period. At the cellular level, during SWS, a slow oscillation ( 140 μV) and delta waves (75–140 μV) during SWS in 14 non-sleep-deprived normal human volunteers. Significant increases in activity were associated with these waves in several cortical areas, including the inferior frontal, medial prefrontal, precuneus, and posterior cingulate areas. Compared with baseline activity, slow waves are associated with significant activity in the parahippocampal gyrus, cerebellum, and brainstem, whereas delta waves are related to frontal responses. No decrease in activity was observed. This study demonstrates that SWS is not a state of brain quiescence, but rather is an active state during which brain activity is consistently synchronized to the slow oscillation in specific cerebral regions. The partial overlap between the response pattern related to SWS waves and the waking default mode network is consistent with the fascinating hypothesis that brain responses synchronized by the slow oscillation restore microwake-like activity patterns that facilitate neuronal interactions.

The subjective meaning of sleep quality: a comparison of individuals with and without insomnia.

Abstract: GOOD SLEEP QUALITY IS ASSOCIATED WITH A WIDE RANGE OF POSITIVE OUTCOMES SUCH AS BETTER HEALTH, LESS DAYTIME SLEEPINESS, GREATER well-being and better psychological functioning.1 Poor sleep quality is one of the defining features of chronic insomnia.2 Although the construct of sleep quality is widely used, a review of the empirical literature suggests that it is not yet fully understood. Indeed, Akerstedt, Hume, Minors, and Waterhouse3 noted that “there seems to be very little systematic knowledge as to what actually constitutes subjectively good sleep and how this should be measured” and Buysse et al.4 referred to sleep quality as a “complex phenomenon that is difficult to define and measure objectively.” Indeed, the empirical results highlight the complexity of sleep quality, particularly as it relates to patients with insomnia. Research studies have reported that “a history of chronic insomnia does not predict poor EEG sleep.”5 Similarly, sleep quality is not directly associated with sleep quantity. For example, a common finding in the literature is that self-reported sleep does not correlate well with PSG defined sleep.6 Indeed, Edinger and colleagues7 distinguished between two groups: a subjective insomnia group who met criteria for insomnia but had normal/nondisturbed sleep on PSG and a subjective normal sleeper group who met criteria for a “normal sleeper” but had objectively disturbed sleep. Psychological variables were found to distinguish between these two groups: the subjective insomnia group exhibited more depressed mood, anxiety and they held more dysfunctional beliefs about sleep, relative to the subjective normal sleeper. These findings highlight the complexity of sleep quality and the importance of understanding the subjective meaning of sleep quality. Accordingly, the broad aim of the present study was to contribute new data to improving understanding of the subjective meaning of sleep quality. The primary focus of previous research has been to identify correlates of sleep quality. A wide range of factors have been investigated that, for ease of description, can be grouped into three clusters. First, there have been a handful of investigations of the correlation between perceived sleep quality and PSG-measured sleep parameters. These studies have included older female normal sleepers,8 older adults with insomnia,9 young adult good and poor sleepers,10 and individuals with unipolar depression.11 The consensus to emerge is that poor sleep quality estimates are associated with reduced Stage 1 sleep and more Stages 3 and 4 sleep. Second, other studies have investigated the association between sleep quality and the subjective perception of sleep parameters. The results suggest that sleep quality is associated with subjective estimates of the ease of sleep onset,12 sleep maintenance,13–15 total sleep time,14 and early awakening.13,15 In addition, restlessness during the night,3,13,16 movement during sleep,15,17 and anxiety, tension, or calmness when trying to sleep15 have also been reported to be associated with sleep quality. Moreover, perceived depth of sleep is important with less perceived light sleep and more perceived deep sleep being associated with higher sleep quality.18 Finally, several studies have examined correlations between sleep quality and how the individual feels immediately on waking and during the day. The results indicate that sleep quality is associated with ease of waking,19 tiredness, sense of balance and coordination,19 clear-headedness,18 how rested, restored and refreshed one feels,13 and mood and physical feelings15 on waking. During the day, feelings of tiredness predicted poorer sleep quality and alertness predicted better sleep quality.19 Taken together, although some consensus has emerged from studies of PSG-measured sleep parameters, there have been few consistent results from the studies that have focused on subjectively estimated aspects of sleep. The variability in the results obtained to date may be attributable to differences across studies in (1) the list of potential correlates evaluated, (2) the vague use of terminology, with some studies using terms like “sleep satisfaction” or “depth of sleep” and others referring to “sleep quality” and (3) the samples employed; the majority of previous studies have recruited good or normal sleepers, with only a handful based on poor sleepers or individuals with insomnia. Gaining an improved understanding of the subjective meaning of sleep quality among individuals with insomnia is important. For example, although differences in Rechtschaffen and Kales scored EEG sleep may not always be evident in patients with insomnia, relative to normal sleepers,5 it is possible that a more sophisticated understanding of the subjective meaning of sleep quality may produce a better measure of sleep quality, which may correlate better with EEG sleep. Alternatively, objective and subjective assessments of sleep quality may reflect different processes and not be directly related.19 In addition, understanding the meaning of sleep quality for individuals with insomnia may turn out to be important for a full recovery from insomnia. This suggestion is made based on cognitive theories which highlight the importance of the perception of or meaning or interpretation attached an event as the critical cause of distress, as opposed to the event itself.20 To summarize, the broad aim of the present study was to conduct a detailed and systematic investigation of the subjective meaning of sleep quality among individuals who meet diagnostic criteria for insomnia compared with a group of normal sleepers. We sought (1) to determine which sleep quality variables are judged to be most important, (2) to use a qualitative approach to determine whether there are important variables influencing perception of sleep quality not covered in the existing research literature, and (3) to compare the insomnia and normal sleeper groups on the meaning of sleep quality. Three different but complementary empirical approaches were employed to index the meaning of sleep quality: (1) a “Speak Freely” procedure in which participants were asked to describe a night of good and a night of poor quality sleep, (2) a “Sleep Quality Interview” in which participants rated the importance of variables included in previous research on sleep quality, and (3) sleep diaries in which participants also answered questions about their sleep quality over seven consecutive nights. These methods were selected to give a varied view of the meaning of sleep quality from both retrospective and prospective viewpoints and to capitalize on the advantages of procedures that require participants to endorse items versus procedures that require responses to be generated.

The roles of dopamine and serotonin, and of their receptors, in regulating sleep and waking

Abstract: Based on electrophysiological, neurochemical and neuropharmacological approaches, it is currently accepted that serotonin (5-HT) and dopamine (DA) function to promote waking (W) and to inhibit slow wave sleep (SWS) and/or rapid-eye-movement sleep (REMS) Serotonergic neurons of the dorsal raphe nucleus (DRN) fire at a steady rate during W, decrease their firing during SWS and virtually cease activity during REMS On the other hand, DA cells in the ventral tegmental area (VTA) and the substantia nigra pars compacta (SNc) do not change their mean firing rate across the sleep–wake cycle It has been proposed that DA cells in the midbrain show a change in temporal pattern rather than firing rate during the sleep–wake cycle Available evidence tends to indicate that during W and REMS an increase of burst firing activity of DA neurons occurs together with an enhanced release of DA in the VTA, the nucleus accumbens and several forebrain structures Recently, DA neurons were characterised in the ventral periaqueductal grey matter (VPAG) that express Fos protein during W Lesioning of these cells resulted in an increase of SWS and REMS, which led to the proposal that VPAG DA neurons may play a role in the promotion of W Systemic injection of full agonists at postsynaptic 5-HT1A (8-OH-DPAT, flesinoxan), 5-HT1B (CGS 12066B, CP-94,253), 5-HT2A/2C (DOI, DOM) and 5-HT3 (m-chlorophenylbiguanide) receptors increases W and reduces SWS and REMS On the other hand, microdialysis perfusion or direct infusion of 8-OH-DPAT or flesinoxan into the DRN, where somatodendritic 5-HT1A receptors are located, significantly increases REMS Systemic administration of the selective DA D1 receptor agonist SKF 38393 induces behavioural arousal together with an increase of W and a reduction of sleep On the other hand, injection of a DA D2 receptor agonist (apomorphine, bromocriptine, quinpirole) gives rise to biphasic effects, such that low doses reduce W and augment SWS and REMS whereas large doses induce the opposite effects Not much is known about dopamine–serotonin interaction in the regulation of sleep and W It has been shown that VTA and SNc DA neurons and DRN 5-HT neurons influence each other Thus, depending on the receptor subtype involved, 5-HT either facilitates or inhibits the functioning of DA cells On the other hand, activation of DA D2-like receptors in the DRN increases the activity of 5-HT neurons Thus, it can be speculated that local microinjection of DA and 5-HT ligands into the DRN and the VTA/SNc, respectively, would affect the actions of the corresponding neurons on sleep and W

An ultra short episode of sleep is sufficient to promote declarative memory performance.

Abstract: Summary Various studies have demonstrated that a night of sleep has a beneficial effect on the retention of previously acquired declarative material. In two experiments, we addressed the question of whether this effect extends to daytime naps. In the first experiment we assessed free recall of a list of 30 words after a 60 min retention interval that was either filled with daytime napping or waking activity. Memory performance was significantly enhanced after napping as opposed to waking but was not correlated with time spent in slow wave sleep or total sleep time within the napping condition. The second experiment was designed to clarify the role of total sleep time and therefore included an additional third group, which was allowed to nap for no longer than 6 min on average. In comparing word recall after conditions of no napping (waking), short napping, and long napping, we found superior recall for both nap conditions in contrast to waking as well as for long naps in contrast to short naps. These results demonstrate that even an ultra short period of sleep is sufficient to enhance memory processing. We suggest that the mere onset of sleep may initiate active processes of consolidation which – once triggered – remain effective even if sleep is terminated shortly thereafter.

Motor sequence learning increases sleep spindles and fast frequencies in post-training sleep

Abstract: THE BENEFICIAL ROLE OF SLEEP IN MOTOR MEMORY CONSOLIDATION IS NOW WELL DOCUMENTED FOR EXAMPLE, AMPLE EVIDENCE INDICATES THAT consolidation of a newly learned sequence of movements, defined as a spontaneous (offline) improvement in performance that emerges in the absence of any further practice, is sleep dependent1–3 Indeed, our group4 and others have demonstrated that delayed gains on a sequential finger-tapping task are triggered only after a night of sleep, whereas a comparable interval without sleep provides no additional benefit Despite the accumulating evidence in support of sleep-dependent motor skill consolidation, there is still no consensus with respect to the sleep stages that are preferentially involved in this memory phase5 Several studies support the hypothesis that post-training REM sleep is required for efficient motor skill consolidation1,7–10 Yet other recent investigations have emphasized the importance of NREM sleep, including delta11 and stage 2 sleep12 For example, Huber and colleagues11 have shown that slow wave activity (< 4 Hz) in the right parietal area during post-training sleep increases following practice on a visuomotor adaptation task, while others have reported that memory on a simple motor skill (ie, the rotary pursuit task) is vulnerable to stage 2 sleep deprivation but not to REM sleep loss13 Finally, Walker and colleagues3 demonstrated that improved overnight performance on a motor sequence learning task is associated with the amount of stage 2 sleep in the last quarter of the night There has been increasing attention to the possible contribution of sleep spindles to memory processes14 Spindles are an essential feature of stage 2 sleep that also appear throughout the depolarizing phase of slow wave sleep oscillation (<1 Hz) Generated by reticular thalamic neurons, they constitute synchronous waveforms between 12–16 Hz that propagate in the thalamocortical loop20 They are therefore thought to provide proper conditions for synaptic changes21 and to elicit long-term potentiation,22 a cellular mechanism known to be involved in learning23 Recently, in a study on motor procedural learning, increased density of sleep spindles and duration of stage 2 sleep following intensive training on several motor skills (including ball-n-cup, rotor pursuit, direct tracing, and logic operation game) were reported24 Interestingly, the authors found a correlation between increased spindle density and overall task performance improvement Despite these findings, however, sleep spindle activity could not be related to the nighttime offline consolidation process per se, because the training and retest sessions were conducted one week apart Moreover, as no motor control condition was presented, changes in sleep architecture following motor skills acquisition could be associated with nonspecific motor activity generated by the tasks themselves In summary, the electroencephalographic (EEG) characteristics of post-training NREM sleep involved in sleep-dependent motor consolidation remain largely unknown Thus, the present study aimed to identify the sleep characteristics underlying offline motor memory consolidation In particular, we sought to compare NREM sleep—including sleep spindles and spectral power activity—following a motor sequence learning task known to result in significant overnight delayed gains4 and after training on a motor control task involving equivalent motor activity but with no expected learning or consolidation We predicted that sleep following motor sequence learning (MSL) would show higher spectral activity—especially in δ (< 4 Hz) and σ frequency bins (12–15 Hz)—and greater number of sleep spindles than in sleep after the motor control task (CTRL)

Rapid eye movement sleep disturbances in Huntington disease.

Abstract: Background Sleep disorders including insomnia, movements during sleep, and daytime sleepiness are common but poorly studied in Huntington disease (HD). Objective To evaluate the HD sleep-wake phenotype (including abnormal motor activity during sleep) in patients with various HD stages and the length of CAG repeats. Because a mild hypocretin deficiency has been found in the brains of some patients with HD (hereinafter referred to as HD patients), we also tested the HD patients for narcolepsy. Design and Patients Twenty-five HD patients (including 2 premanifest carriers) underwent clinical interview, nighttime video and sleep monitoring, and daytime multiple sleep latency tests. Their results were compared with those of patients with narcolepsy and control patients. Results The HD patients had frequent insomnia, earlier sleep onset, lower sleep efficiency, increased stage 1 sleep, delayed and shortened rapid eye movement (REM) sleep, and increased periodic leg movements. Three HD patients (12%) had REM sleep behavior disorders. No sleep abnormality correlated with CAG repeat length. Reduced REM sleep duration (but not REM sleep behavior disorders) was present in premanifest carriers and patients with very mild HD and worsened with disease severity. In contrast to narcoleptic patients, HD patients had no cataplexy, hypnagogic hallucinations, or sleep paralysis. Four HD patients had abnormally low ( Conclusions The sleep phenotype of HD includes insomnia, advanced sleep phase, periodic leg movements, REM sleep behavior disorders, and reduced REM sleep but not narcolepsy. Reduced REM sleep may precede chorea. Mutant huntingtin may exert an effect on REM sleep and motor control during sleep.

Does REM sleep contribute to subjective wake time in primary insomnia? A comparison of polysomnographic and subjective sleep in 100 patients

Abstract: Primary insomnia (PI) is characterized by low subjective sleep quality which cannot always be verified using polysomnography (PSG). To shed light on this discrepancy, subjective estimates of sleep and PSG variables were compared in patients with PI and good sleeper controls (GSC). 100 patients with PI (age: 42.57 +/- 12.50 years, medication free for at least 14 days) and 100 GSC (41.12 +/- 13.99 years) with a sex distribution of 46 men and 54 women in each group were included. Both PSG and questionnaire variables showed clear impairments of sleep quality in PI compared with GSC. The arousal index within total sleep time was increased, which was mainly because of a strong increase within rapid eye movement (REM) sleep. Subjectively, more PI than GSC subjects estimated wake times longer than obtained from PSG. Linear modeling analysis of subjective wake time in terms of PSG parameters revealed that in addition to PSG defined wake time, REM sleep time contributed significantly to subjective wake time. This REM sleep contribution was larger for PI than for GSC subjects. The findings suggest that REM sleep-related processes might contribute to subjectively disturbed sleep and the perception of waking time in patients with PI.

Enhancement of declarative memory performance following a daytime nap is contingent on strength of initial task acquisition.

Abstract: IT IS BECOMING INCREASINGLY CLEAR THAT NREM SLEEP, ESPECIALLY SLOW WAVE SLEEP (SWS), IS IMPORTANT FOR THE PROCESSING OF HIPPOCAMPUS-dependent declarative memories,1–6 with SWS hypothesized to provide the optimal electrophysiological and biochemical state for this type of processing.7,8 When sleep occurs in the form of a short daytime nap, it is very common to obtain only NREM sleep, without entering REM sleep, which would usually occur at least 90 minutes into the sleep period. The few studies examining the effect of daytime naps on memory have made use of this knowledge, demonstrating that daytime naps containing only NREM sleep (including SWS) facilitate verbal declarative memory (semantically related paired associates),9 with one study showing that paired associates improvement is contingent on whether subjects obtained SWS during the nap.10 These findings represent a first step forward in our understanding of how daytime naps benefit declarative memory processing. However, there are many questions still to be explored. To this end, the present study examines the benefits of a daytime NREM nap on a spectrum of declarative memory tasks, and begins to assess the importance of factors related to task acquisition and their potential to modulate sleep-related memory processing. To more broadly assess the declarative memory benefits of NREM sleep obtained during a daytime nap, subjects were trained on 3 well-known declarative (hippocampus-dependent) memory tasks. The first task was an unrelated paired associates task, a more difficult counterpart to the commonly used related paired associates task.3,4 The task comprises pairs of common words that lack an inherent semantic relationship (e.g., shirt–paper). Two nonverbal declarative memory tasks that do not rely strongly on previously learned concepts were also evaluated: the Rey-Osterrieth complex figure test (ROCFT; a measure of visuospatial declarative memory) and a maze learning task adapted from the task used by Brenda Milner on a large sample of hippocampal lesion patients including HM.11 Both of these tasks are void of semantically charged landmarks, objects, or verbal material that would have been previously learned by subjects. To date, no studies have used this particular maze learning task, and only 2 have examined the effect of sleep on memory using the ROCFT. In epileptic patients it was shown that performance on the ROCFT correlated positively with low frequency EEG spectral power (<1.25 Hz) overnight,12 and in schizophrenic patients the amount of SWS correlated positively with overnight ROCFT performance.13 In the present study we also explored the extent to which different methods of information encoding modulate the effect of sleep on memory. The impetus for exploring encoding factors was based on two studies by Smith, et al.14,15 who found that only when rats successfully acquired an operant conditioning or passive avoidance task was there an increase in subsequent paradoxical sleep. These findings suggested for the first time that the extent of task acquisition may be an important modulator of the effect of sleep on memory processing. Support for this general finding comes from a recent PET study demonstrating that the strength of acquisition of a serial reaction time task is correlated with increased brain activation (regional cerebral blood flow) during post-acquisition REM sleep.16 Similarly, it was shown that stronger acquisition of a motor adaptation task not only correlates with an increase in slow wave activity (SWA) during subsequent sleep, but this increase in SWA is correlated with enhanced performance following sleep.17 Given these findings, it becomes clear that the individual's success in acquiring a task may be an important factor in understanding how sleep facilitates memory formation. In addition to the assessment of individual differences in acquisition, the level of task acquisition can be experimentally manipulated to assess the preferential effect of sleep for information that is more strongly acquired. A recent study by Schmidt et al.18 has shown that not only does spindle density increase significantly during a daytime nap following the encoding of a difficult (but not an easy) paired associates task, but that this increase in spindle density correlates with improvement in paired associates recall. To assess the importance of task acquisition in modulating sleep-related memory processing, we created 2 encoding conditions within the paired associates task. To date, almost all sleep-dependent consolidation studies have employed a “study-test” paradigm,19 whereby subjects learn a list of word pairs, and then perform cued recall tests until a specified performance criterion is met (e.g., 60% correct or one perfect recall trial2,3,20). However, it is still unclear whether immediate testing leads to enhanced paired associates encoding, which in turn allows sleep to more strongly facilitate memory processing, or whether sleep imparts the same performance benefits to subjects that simply learn the word pairs without immediate testing. Interestingly, in a recent study that did not examine sleep/wake differences it was shown that when subjects were tested immediately after learning declarative information (a text passage), recall after one week was superior to recall of subjects that underwent multiple study sessions without being tested.19 To add to our understanding of the nature of task acquisition and its potential to modulate the effects of sleep on memory, subjects in the present study were immediately tested on a subset of the word pairs during the training session (referred to as “tested” word pairs), while the remaining word pairs were studied without immediate test (referred to as “untested” word pairs). In the present study, performance on all 3 declarative tasks was assessed following a 3.5-h training-retest interval that included a daytime NREM nap or no nap. To test the extent to which task acquisition factors modulate sleep-related memory processing, subjects were not only exposed to 2 modes of paired associates encoding, but for each task subjects were also divided post hoc into high and low performers based on training performance (i.e., those performing in the top and bottom half of the sample based on a median split). This allowed for an analysis of the effect of the subjects' ability to acquire each of the 3 tasks as well as the effect of 2 different modes of paired associates acquisition (tested vs. untested) on sleep-related memory processing.

EEG Spectral Analysis in Primary Insomnia: NREM Period Effects and Sex Differences

Abstract: THE ETIOLOGY AND PATHOPHYSIOLOGY OF INSOMNIA ARE UNKNOWN, BUT IT IS OFTEN CONSIDERED TO BE A DISORDER OF INCREASED PHYSIOLOGICAL and cognitive arousal.1–3 Evidence for physiological arousal includes elevated resting metabolic rate,4,5 increased heart rate and sympathovagal tone as indicated by heart rate variability (HRV),6,7 increased cortisol secretion in the evening and early sleep hours,8,9 increased beta EEG activity during NREM sleep,10–14 and increased glucose metabolic rate during NREM sleep.15 Evidence for increased arousal defined in cognitive terms is found in the pre-sleep thoughts of insomnia patients compared to good sleepers,16–19 which are often described as “racing,” unstoppable, and sleep-focused. Contemporary models of the pathophysiology of insomnia suggest that, in individuals predisposed on the basis of genetic or affective factors, the acute experience of sleep difficulty leads to a positive feedback loop of selective attention, conditioned arousal, poor sleep, and impaired waking function.20–23 Of the various indicators of hyperarousal in insomnia, quantitative EEG characteristics have been studied most carefully, usually through the use of power spectral analysis of the sleep EEG. Particular attention has been focused on high frequency activity in the range of 16–32 Hz, or “beta activity,” which is thought to reflect a form of cortical activation. This interpretation is based on waking EEG studies in healthy adults, where even higher frequency EEG activity (in the “gamma” range of 30–100 Hz) is thought to represent an analog of sensory processing, focused attention, learning, or memory.13,24–26 Most insomnia studies have focused on quantitative EEG obtained during NREM sleep, as opposed to REM sleep, in part because phasic eye movements and muscle activity can lead to EEG artifacts during REM, and in part because there is little specific evidence to implicate disturbances of REM sleep in chronic insomnia. Although increased fast frequency EEG activity during NREM sleep has been demonstrated in several samples of insomnia subjects relative to controls, methodologies have varied widely among these studies. For instance, increased beta activity in one study was observed in subjects with “sleep state misperception” (paradoxical insomnia), but not psychophysiological insomnia, relative to controls.14 Another study showed increased beta in primary insomnia relative to insomnia with comorbid depression and controls.12 In addition to examining high-frequency EEG activity as an indicator of hyperarousal, some studies have also used quantitative EEG to measure delta EEG activity (0.5–4 Hz) as an indicator of homeostatic sleep drive in insomnia. These studies have also yielded variable results, with some showing reduced delta activity,11 but others showing no difference between insomnia and control samples,12,27 or a reduction only in “subjective” insomnia, but not “objective” insomnia.14 Although it may appear logical that EEG correlates of hyperarousal and homeostatic drive would inversely correlate in PI, previous published reports have presented only qualitative evidence to support this hypothesis.11,27 Most studies showing insomnia-control differences have focused on all-night NREM EEG activity, but others have focused on the sleep-onset interval.10,28 Some studies have also examined the time course of EEG power in different bands across successive NREM periods,11,27 generally finding stable differences across the night. However, other types of physiological data, such as plasma cortisol levels, suggest that individuals with PI may have particular evidence of hyperarousal in the first part of the night.8,9 Sex differences in quantitative EEG during sleep have also been identified in healthy individuals from adolescence to older adulthood,29–32 and among individuals with conditions such as major depressive disorder.33–35 However, sex differences have not been extensively examined in chronic insomnia. One study found higher relative beta EEG power in men than women among an older adult sample of insomnia and control subjects,14 but several other studies did not specifically examine sex differences. Likewise, the relationship between quantitative EEG characteristics and subjective sleep characteristics has received little attention. If high-frequency EEG activity were indeed a correlate of hyperarousal, one might expect that this variable would correlate with insomnia severity or sleep self-reports. Krystal and colleagues14 found that delta and beta power differed between subjective insomnia subjects and controls regardless of the degree of subjective underestimation of sleep, but that subjective ratings of sleep quality, restedness, and sleep efficiency were related only to delta power, and only among subjective insomnia subjects. Perlis and colleagues12 found that subjective underestimation of sleep time was related to higher beta activity in a sample that included PI, GSC, and depressed subjects. Thus, whether quantitative EEG characteristics are related to overall insomnia severity or to specific features remains an unresolved issue. In summary, previous findings regarding quantitative EEG characteristics of insomnia have provided inconsistent results, particularly regarding differences across NREM periods, sex effects, and clinical correlations. Therefore, the goals of the present analysis were: (1) to compare EEG power across successive NREM periods in well-characterized samples of primary insomnia (PI) and good sleeper controls (GSC); (2) to compare these findings for men and women separately; and (3) to examine relationships between quantitative EEG characteristics, baseline characteristics of insomnia, and self-reports of sleep.

Sleep disturbance in heavy marijuana users.

Abstract: PEOPLE WITH SUBSTANCE-RELATED DISORDERS OFTEN EXPERIENCE SLEEP PROBLEMS THAT PERSIST FOR MONTHS AFTER CESSATION OF DRUG USE.1,2 These sleep disturbances could precipitate relapse in recently abstinent substance users as they attempt to improve their sleep quality. Eleven million Americans use marijuana (MJ) either alone, or in conjunction with other illicit drugs, and this number is increasing. Increases in the numbers of MJ users, coupled with increases in potency over recent years have resulted in a higher prevalence of MJ use disorders.3 Except for alcohol, MJ use accounted for the largest percent of drug abuse treatment admissions (15.9%) in 2004. A major problem in the treatment of MJ users is that up to 76% of those who abruptly stop using MJ report disturbed sleep (strange dreams, insomnia, poor sleep quality), possibly increasing the risk of relapse.4 Aside from self-reports of sleep disturbance by recently abstinent MJ users, there are only a handful of studies that have recorded polysomnography (PSG) in MJ users in the past 20 years.5–8 After oral administration of a high dose of MJ extract, REM sleep decreased and slow wave sleep (SWS) increased.5,6 Following one day of no MJ use, REM sleep increased and SWS decreased. In another study, 3 MJ-dependent men (mean age 40 yr) were studied during 3 days of abstinence.7 Over the 3 days, sleep efficiency (total sleep time [TST]/time in bed [TIB] and initial REM latency decreased, while percent REM of TST, SWS (% TST), ratings of MJ craving, and irritability increased. These 2 studies showed contradictory results with respect to SWS, which could be related to differences in the demographic characteristics of the MJ users (e.g., amount of MJ use) or the timing of the PSG in relationship to the number of days of abstinence. Although the numbers of studies are few, these results show robust sleep abnormalities after MJ discontinuation and underscore the need to further investigate sleep disturbance in recently abstinent MJ users. Sleep disturbance in MJ users has important basic science and clinical implications. Furthering our understanding of how sleep is affected in MJ users could provide insights not only into the process of addiction but also into the functioning of the endogenous cannabinoid system, since this system plays a role in sleep promotion.9 In addition, a better understanding of sleep disturbance in recently abstinent MJ users has potential implications for understanding relapse and guiding treatment interventions. The aim of this study was to determine if MJ users self-reporting sleep disturbance when discontinuing MJ use in the past show objective PSG findings that are different from a drug-free control group. Based on previous subjective reports of sleep disturbance and limited objective PSG findings, we hypothesized that abstinent MJ users would show longer time to sleep onset and more difficulty with sleep maintenance than a drug-free control group. Since we have repeatedly found dose-related associations between the amount and duration of MJ drug use and measures of brain function,10,11 we explored also whether there was an association between the amount and duration of MJ use and the severity of sleep disturbance.

An endogenous circadian rhythm in sleep inertia results in greatest cognitive impairment upon awakening during the biological night

Abstract: Sleep inertia is the impaired cognitive performance immediately upon awakening, which decays over tens of minutes. This phenomenon has relevance to people who need to make important decisions soon after awakening, such as on-call emergency workers. Such awakenings can occur at varied times of day or night, so the objective of the study was to determine whether or not the magnitude of sleep inertia varies according to the phase of the endogenous circadian cycle. Twelve adults (mean, 24 years; 7 men) with no medical disorders other than mild asthma were studied. Following 2 baseline days and nights, subjects underwent a forced desynchrony protocol composed of seven 28-h sleep/wake cycles, while maintaining a sleep/wakefulness ratio of 1:2 throughout. Subjects were awakened by a standardized auditory stimulus 3 times each sleep period for sleep inertia assessments. The magnitude of sleep inertia was quantified as the change in cognitive performance (number of correct additions in a 2-min serial addition test) across the first 20 min of wakefulness. Circadian phase was estimated from core body temperature (fitted temperature minimum assigned 0°). Data were segregated according to: (1) circadian phase (60° bins); (2) sleep stage; and (3) 3rd of the night after which awakenings occurred (i.e., tertiary 1, 2, or 3). To control for any effect of sleep stage, the circadian rhythm of sleep inertia was initially assessed following awakenings from Stage 2 (62% of awakening occurred from this stage; n = 110). This revealed a significant circadian rhythm in the sleep inertia of cognitive performance (p = 0.007), which was 3.6 times larger during the biological night (circadian bin 300°, ~2300–0300 h in these subjects) than during the biological day (bin 180°, ~1500–1900 h). The circadian rhythm in sleep inertia was still present when awakenings from all sleep stages were included (p = 0.004), and this rhythm could not be explained by changes in underlying sleep drive prior to awakening (changes in sleep efficiency across circadian phase or across the tertiaries), or by the proportion of the varied sleep stages prior to awakenings. This robust endogenous circadian rhythm in sleep inertia may have important implications for people who need to be alert soon after awakening.

Learning-Dependent, Transient Increase of Activity in Noradrenergic Neurons of Locus Coeruleus during Slow Wave Sleep in the Rat: Brain Stem–Cortex Interplay for Memory Consolidation?

Abstract: Memory consolidation during sleep is regaining attention due to a wave of recent reports of memory improvements after sleep or deficits after sleep disturbance. Neuromodulators have been proposed as possible players in this putative off-line memory processing, without much experimental evidence. We recorded neuronal activity in the rat noradrenergic nucleus locus coeruleus (LC) using chronically implanted movable microelectrodes while monitoring the behavioral state via electrocorticogram and online video recording. Extracellular recordings of physiologically identified noradrenergic neurons of LC were made in freely behaving rats for 3 h before and after olfactory discrimination learning. On subsequent days, if LC recording remained stable, additional learning sessions were made within the olfactory discrimination protocol, including extinction, reversals, learning new odors. Contrary to the long-standing dogma about the quiescence of noradrenergic neurons of LC, we found a transient increase in LC activity in trained rats during slow wave sleep (SWS) 2 h after learning. The discovery of learning-dependent engagement of LC neurons during SWS encourages exploration of brain stem-cortical interaction during this delayed phase of memory consolidation and should bring new insights into mechanisms underlying memory formation.

Memory consolidation during sleep: interactive effects of sleep stages and HPA regulation.

Abstract: Sleep is critically involved in the consolidation of previously acquired memory traces. However, nocturnal sleep is not uniform but is subject to distinct changes in electrophysiological and neuroendocrine activity. Specifically, the first half of the night is dominated by slow wave sleep (SWS), whereas rapid eye movement (REM) sleep prevails in the second half. Concomitantly, hypothalamo-pituitary-adrenal (HPA) activity as indicated by cortisol release is suppressed to a minimum during early sleep, while drastically increasing during late sleep. We have shown that the different sleep stages and the concomitant glucocorticoid release are interactively involved in the consolidation of different types of memories. SWS-rich early sleep has been demonstrated to benefit mainly the consolidation of hippocampus-dependent declarative memories (i.e. facts and episodes). In contrast, REM sleep-rich late sleep was shown to improve in particular emotional memories involving amygdalar function, as well as procedural memories (for skills) not depending on hippocampal or amygdalar function. Enhancing plasma glucocorticoid concentrations during SWS-rich early sleep counteracted hippocampus-dependent declarative memory consolidation, but did not affect hippocampus-independent procedural memory. Preventing the increase in cortisol during late REM sleep-rich sleep by administration of metyrapone impaired hippocampus-dependent declarative memory but enhanced amygdala-dependent emotional aspects of memory. The data underscore the importance of pituitary-adrenal inhibition during early SWS-rich sleep for efficient consolidation of declarative memory. The increase in cortisol release during late REM sleep-rich sleep may counteract an overshooting consolidation of emotional memories.

The microstructure of active and quiet sleep as cortical delta activity emerges in infant rats.

Abstract: SLEEP AND WAKEFULNESS ARE BEHAVIORAL STATES COMPRISING TONIC AND PHASIC CHANGES IN MUSCLE AND BRAIN ACTIVITY. TRADITIONALLY, THESE states are identified by monitoring muscle tone, (electromyogram [EMG]), eye movements, (electrooculogram [EOG]), and neocortical activity (electroencephalogram [EEG]).1 In infant rats, state-dependent EEG activity—in the form of 1- to 4-Hz delta waves—does not emerge until around postnatal day (P)11.2–5 Nonetheless, nuchal EMG and EOG activity reliably mirror behavioral assessments of state, including quiet sleep (QS) and active sleep (AS), as early as P2-3,6,7 and is sufficient for demonstrating state-dependent neural activity within the brainstem as early as P8.8,9 Thus, significant progress has been made in our understanding of sleep development at ages during which EEG measures are unavailable. Nonetheless, rightly or not, for many the EEG remains the gold standard of sleep measurement. This emphasis on the EEG has engendered some confusion concerning the definition, quantity, and structure of infant sleep before and after the emergence of delta activity. For example, Jouvet-Mounier et al5 reported that AS is prominent soon after birth but that the quantity of QS is negligible during the early postnatal period and increases explosively with the emergence of delta activity at P11. This observation suggested to them that the brain mechanisms needed to express QS develop later than those needed to express AS. Furthermore, Jouvet-Mounier et al5 reported that, in the days after their emergence, bouts of delta activity are often intermixed with AS-related myoclonic twitching, which they designated as “half-activated” AS. Subsequent investigators have reported similar results.3,10,11 The presence of such ambiguous sleep states provided a foundation for Frank and Heller's “presleep hypothesis.”3,12 In contrast, in a previous study, we found no evidence for half-activated AS in P14 rats.7 Nonetheless, because we did not examine younger infants as delta activity was emerging, it remained unclear how delta integrates with already-existing QS and AS at the very earliest moments of its developmental expression. Therefore, here we provide a detailed analysis of sleep-state organization in P9, P11, and P13 rats, that is, during the 5-day period surrounding the emergence of delta activity. At all ages, nuchal EMG and behavioral criteria were used to identify bouts of QS and AS, and, for comparison, these criteria were supplemented with EEG activity at P11 and P13. We found no evidence of disorganization (i.e., half-activated AS) or reorganization (i.e., explosive increase in QS) of sleep structure across the emergence of delta activity. All together, these results reveal general principles of state organization that hold true across an important developmental transition.

Increased EEG spectral power density during sleep following short-term sleep deprivation in pigeons (Columba livia): evidence for avian sleep homeostasis.

Abstract: Summary Birds provide a unique opportunity to evaluate current theories for the function of sleep. Like mammalian sleep, avian sleep is composed of two states, slow-wave sleep (SWS) and rapid eye-movement (REM) sleep that apparently evolved independently in mammals and birds. Despite this resemblance, however, it has been unclear whether avian SWS shows a compensatory response to sleep loss (i.e., homeostatic regulation), a fundamental aspect of mammalian sleep potentially linked to the function of SWS. Here, we prevented pigeons (Columba livia) from taking their normal naps during the last 8 h of the day. Although time spent in SWS did not change significantly following short-term sleep deprivation, electroencephalogram (EEG) slow-wave activity (SWA; i.e., 0.78–2.34 Hz power density) during SWS increased significantly during the first 3 h of the recovery night when compared with the undisturbed night, and progressively declined thereafter in a manner comparable to that observed in similarly sleep-deprived mammals. SWA was also elevated during REM sleep on the recovery night, a response that might reflect increased SWS pressure and the concomitant ‘spill-over’ of SWS-related EEG activity into short episodes of REM sleep. As in rodents, power density during SWS also increased in higher frequencies (9–25 Hz) in response to short-term sleep deprivation. Finally, time spent in REM sleep increased following sleep deprivation. The mammalian-like increase in EEG spectral power density across both low and high frequencies, and the increase in time spent in REM sleep following sleep deprivation suggest that some aspects of avian and mammalian sleep are regulated in a similar manner.

Mammalian-like features of sleep structure in zebra finches

Abstract: A suite of complex electroencephalographic patterns of sleep occurs in mammals. In sleeping zebra finches, we observed slow wave sleep (SWS), rapid eye movement (REM) sleep, an intermediate sleep (IS) stage commonly occurring in, but not limited to, transitions between other stages, and high amplitude transients reminiscent of K-complexes. SWS density decreased whereas REM density increased throughout the night, with late-night characterized by substantially more REM than SWS, and relatively long bouts of REM. Birds share many features of sleep in common with mammals, but this collective suite of characteristics had not been known in any one species outside of mammals. We hypothesize that shared, ancestral characteristics of sleep in amniotes evolved under selective pressures common to songbirds and mammals, resulting in convergent characteristics of sleep.

Using DTX and DRX in a wireless communication system

Abstract: Systems, methodologies, and devices are described that can facilitate reducing power consumption associated with mobile devices. A mobile device can utilize a sleep mode controller that can facilitate selecting and/or switching to a desired sleep mode based in part on predefined sleep mode criteria. The sleep modes can include a non-sleep mode, light sleep mode, and/or deep sleep mode. The mobile device can employ an analyzer to evaluate information related to explicit signals, implicit signals, and/or the current sleep mode to determine whether a condition is met based in part on the predefined sleep mode criteria such that a transition to a different sleep mode is to be performed. If such a condition is met, the sleep mode controller can facilitate transitioning from the current sleep mode to a different sleep mode to facilitate reducing power consumption by the mobile device.