EEG slow waves and sleep spindles: windows on the sleeping brain

Threshold Values of Sleep Spindles Features in Healthy Adults Using Scalp-EEG and Associations With Sleep Parameters

OBJECTIVE

Sleep spindles are an electrophysiological fingerprint of the sleeping human brain. They can be described in terms of duration, frequency, amplitude, and density, and vary widely according to age and sex. Spindles play a role in sleep and wake functions and are altered in several neurological and psychiatric disorders. This study established the first threshold values for sleep spindles in healthy adults using scalp-EEG and explored their associations with other sleep parameters.

METHODS

This observational prospective study was conducted with 80 healthy participants stratified by age and sex (40.9 years, range 19-74, 50% females). All participants underwent in-laboratory polysomnography. Sleep spindles during N2 were analyzed using an automated procedure and categorized as fast (> 13 Hz) or slow (≤ 13 Hz).

RESULTS

For fast spindles, the threshold values were duration (0.80-1.11 s), frequency (13.4-14.3 Hz), amplitude (5.2-15.2 μV), and density (1.0-5.8 spindles/min). For slow spindles, the values were duration (0.79-1.17 s), frequency (12.3-12.9 Hz), amplitude (4.1-13.2 μV), and density (0.03-3.15 spindles/min). From age 40 onwards, the density, amplitude, and duration of both types of spindles decreased; the amplitudes of both types of spindles were higher in females. Higher amplitude in fast spindles was associated with increased excessive daytime sleepiness and an increased proportion of slow-wave sleep.

INTERPRETATION

This study provides the first threshold values for sleep spindle characteristics in healthy adults. The findings emphasize the importance of investigating spindles to develop innovative biomarkers for neurological and psychiatric disorders and to gain deeper insights into the functioning of the sleeping brain.

Using spectral continuity to extract breathing rate from heart rate and its applications in sleep physiology

Introduction: ECG Derived Respiration (EDR) are a set of methods used for extracting the breathing rate from the Electrocardiogram (ECG). Recent studies revealed a tight connection between breathing rate and more specifically the breathing patterns during sleep and several related pathologies. Yet, while breathing rate and more specifically the breathing pattern is recognised as a vital sign it is less employed than Electroencephalography (EEG) and heart rate in sleep and polysomnography studies. Methods: This study utilised open-access data from the ISRUC sleep database to test a novel spectral-based EDR technique (scEDR). In contrast to previous approaches, the novel method emphasizes spectral continuity and not only the power of the different spectral peaks. scEDR is then compared against a more widely used spectral EDR method that selects the frequency with the highest power as the respiratory frequency (Max Power EDR). Results: scEDR yielded improved performance against the more widely used Max Power EDR in terms of accuracy across all sleep stages and the whole sleep. This study further explores the breathing rate across sleep stages, providing evidence in support of a putative sleep stage "REM0" which was previously proposed based on analysis of the Heart Rate Variability (HRV) but not yet widely discussed. Most importantly, this study observes that the frequency distribution of the heart rate during REM0 is closer to REM than other NREM periods even though most of REM0 was previously classified as NREM sleep by sleep experts following either the original or revised sleep staging criteria. Discussion: Based on the results of the analysis, this study proposes scEDR as a potential low-cost and non-invasive method for extracting the breathing rate using the heart rate during sleep with further studies required to validate its accuracy in awake subjects. In this study, the autonomic balance across different sleep stages, including REM0, was examined using HRV as a metric. The results suggest that sympathetic activity decreases as sleep progresses to NREM3 until it reaches a level similar to the awake state in REM through a transition from REM0.

Spectral Slope and Lempel-Ziv Complexity as Robust Markers of Brain States during Sleep and Wakefulness

Nonoscillatory measures of brain activity such as the spectral slope and Lempel-Ziv complexity are affected by many neurological disorders and modulated by sleep. A multitude of frequency ranges, particularly a broadband (encompassing the full spectrum) and a narrowband approach, have been used especially for estimating the spectral slope. However, the effects of choosing different frequency ranges have not yet been explored in detail. Here, we evaluated the impact of sleep stage and task engagement (resting, attention, and memory) on slope and complexity in a narrowband (30-45 Hz) and broadband (1-45 Hz) frequency range in 28 healthy male human subjects (21.54 ± 1.90 years) using a within-subject design over 2 weeks with three recording nights and days per subject. We strived to determine how different brain states and frequency ranges affect slope and complexity and how the two measures perform in comparison. In the broadband range, the slope steepened, and complexity decreased continuously from wakefulness to N3 sleep. REM sleep, however, was best discriminated by the narrowband slope. Importantly, slope and complexity also differed between tasks during wakefulness. While narrowband complexity decreased with task engagement, the slope flattened in both frequency ranges. Interestingly, only the narrowband slope was positively correlated with task performance. Our results show that slope and complexity are sensitive indices of brain state variations during wakefulness and sleep. However, the spectral slope yields more information and could be used for a greater variety of research questions than Lempel-Ziv complexity, especially when a narrowband frequency range is used.

Maturational trend of daytime sleep propensity in adolescents

STUDY OBJECTIVES

The teenage increase in sleepiness is not simply a response to decreasing nighttime sleep duration. Daytime sleepiness increases across adolescence even when prior sleep duration is held constant. Here we determine the maturational trend in daytime sleep propensity assessed with the multiple sleep latency test (MSLT) and assess the trend's relation to pubertal maturation and changes in the sleep electroencephalogram. We also evaluate whether the relation of daytime sleep propensity to prior sleep duration changes between ages 10 and 23 years.

METHODS

Participants (n = 159) entered the study between ages 9.8 and 22.8 years and were studied annually for up to 3 years. Annually, participants kept each of three sleep schedules in their homes: 7, 8.5, and 10 hours in bed for 4 consecutive nights with polysomnography on nights 2 and 4. MSLT-measured daytime sleep propensity was assessed in the laboratory on the day following the fourth night.

RESULTS

A two-part linear spline model described the maturation of daytime sleep propensity. MSLT sleep likelihood increased steeply until age 14.3 years, after which it did not change significantly. The maturational trend was strongly associated with the adolescent decline in slow-wave (delta, 1-4 Hz) EEG power during NREM sleep and with pubertal maturation assessed with Tanner stage measurement of breast/genital development. The effect of prior sleep duration on sleep likelihood decreased with age.

CONCLUSIONS

Adolescent brain changes related to pubertal maturation and those reflected in the delta decline contribute to the adolescent increase in daytime sleep propensity.

Altered Sleep Oscillations as Neurophysiological Biomarkers of Schizophrenia

Sleep spindles and slow waves are the two main oscillatory activities occurring during nonrapid eye movement (NREM) sleep. Here, we will first describe the electrophysiological characteristics of these sleep oscillations along with the neurophysiological and molecular mechanisms underlying their generation and synchronization in the healthy brain. We will then review the extant evidence of deficits in sleep spindles and, to a lesser extent, slow waves, including in slow wave-spindle coupling, in patients with Schizophrenia (SCZ) across the course of the disorder, from at-risk to chronic stages. Next, we will discuss how these sleep oscillatory deficits point to defects in neuronal circuits within the thalamocortical network as well as to alterations in molecular neurotransmission implicating the GABAergic and glutamatergic systems in SCZ. Finally, after explaining how spindle and slow waves may represent neurophysiological biomarkers with predictive, diagnostic, and prognostic potential, we will present novel pharmacological and neuromodulatory interventions aimed at restoring sleep oscillatory deficits in SCZ, which in turn may serve as target engagement biomarkers to ameliorate the clinical symptoms and the quality of life of individuals affected by this devastating brain disorder.

Differences in generation and maintenance between ictal and interictal generalized spike-and-wave discharges in childhood absence epilepsy: A magnetoencephalography study

PURPOSE

Childhood absence epilepsy (CAE) is characterized by impaired consciousness and distinct electroencephalogram (EEG) patterns. However, interictal epileptiform discharges (IEDs) do not lead to noticeable symptoms. This study examines the disparity between ictal and interictal generalized spike-and-wave discharges (GSWDs) to determine the mechanisms behind CAE and consciousness.

METHODS

We enrolled 24 patients with ictal and interictal GSWDs in the study. The magnetoencephalography (MEG) data were recorded before and during GSWDs at a sampling rate of 6000 Hz and analyzed across six frequency bands. The absolute and relative spectral power were estimated with the Minimum Norm Estimate (MNE) combined with the Welch technique. All the statistical analyses were performed using paired-sample tests.

RESULTS

During GSWDs, the right lateral occipital cortex indicated a significant difference in the theta band (5-7 Hz) with stronger power (P = 0.027). The interictal group possessed stronger spectral power in the delta band (P < 0.01) and weaker power in the alpha band (P < 0.01) as early as 10 s before GSWDs in absolute and relative spectral power. Additionally, the ictal group revealed enhanced spectral power inside the occipital cortex in the alpha band and stronger spectral power in the right frontal regions within beta (15-29 Hz), gamma 1 (30-59 Hz), and gamma 2 (60-90 Hz) bands.

CONCLUSIONS

GSWDs seem to change gradually, with local neural activity changing even 10 s before discharge. During GSWDs, visual afferent stimulus insensitivity could be related to the impaired response state in CAE. The inhibitory signal in the low-frequency band can shorten GSWD duration, thereby achieving seizure control through inhibitory effect strengthening.

Nociception in Chicken Embryos, Part II: Embryonal Development of Electroencephalic Neuronal Activity In Ovo as a Prerequisite for Nociception

Chicken culling has been forbidden in Germany since 2022; male/female selection and male elimination must be brought to an embryonic status prior to the onset of nociception. The present study evaluated the ontogenetic point at which noxious stimuli could potentially be perceived/processed in the brain in ovo. EEG recordings from randomized hyperpallial brain sites were recorded in ovo and noxious stimuli were applied. Temporal and spectral analyses of the EEG were performed. The onset of physiological neuronal signals could be determined at developmental day 13. ERP/ERSP/ITC analysis did not reveal phase-locked nociceptive responses. Although no central nociceptive responses were documented, adequate EEG responses to noxious stimuli from other brain areas cannot be excluded. The extreme stress impact on the embryo during the recording may overwrite the perception of noniceptive stimuli. The results suggest developmental day 13 as the earliest embryonal stage being able to receive and process nociceptive stimuli.

Sleep spindles across youth affected by schizophrenia or anti-N-methyl-D-aspartate-receptor encephalitis

Background

Sleep disturbances are intertwined with the progression and pathophysiology of psychotic symptoms in schizophrenia. Reductions in sleep spindles, a major electrophysiological oscillation during non-rapid eye movement sleep, have been identified in patients with schizophrenia as a potential biomarker representing the impaired integrity of the thalamocortical network. Altered glutamatergic neurotransmission within this network via a hypofunction of the N-methyl-D-aspartate receptor (NMDAR) is one of the hypotheses at the heart of schizophrenia. This pathomechanism and the symptomatology are shared by anti-NMDAR encephalitis (NMDARE), where antibodies specific to the NMDAR induce a reduction of functional NMDAR. However, sleep spindle parameters have yet to be investigated in NMDARE and a comparison of these rare patients with young individuals with schizophrenia and healthy controls (HC) is lacking. This study aims to assess and compare sleep spindles across young patients affected by Childhood-Onset Schizophrenia (COS), Early-Onset Schizophrenia, (EOS), or NMDARE and HC. Further, the potential relationship between sleep spindle parameters in COS and EOS and the duration of the disease is examined.

Methods

Sleep EEG data of patients with COS (N = 17), EOS (N = 11), NMDARE (N = 8) aged 7-21 years old, and age- and sex-matched HC (N = 36) were assessed in 17 (COS, EOS) or 5 (NMDARE) electrodes. Sleep spindle parameters (sleep spindle density, maximum amplitude, and sigma power) were analyzed.

Results

Central sleep spindle density, maximum amplitude, and sigma power were reduced when comparing all patients with psychosis to all HC. Between patient group comparisons showed no differences in central spindle density but lower central maximum amplitude and sigma power in patients with COS compared to patients with EOS or NMDARE. Assessing the topography of spindle density, it was significantly reduced over 15/17 electrodes in COS, 3/17 in EOS, and 0/5 in NMDARE compared to HC. In the pooled sample of COS and EOS, a longer duration of illness was associated with lower central sigma power.

Conclusions

Patients with COS demonstrated more pronounced impairments of sleep spindles compared to patients with EOS and NMDARE. In this sample, there is no strong evidence that changes in NMDAR activity are related to spindle deficits.

Focal epilepsy disrupts spindle structure and function

Sleep spindles are the hallmark of N2 sleep and are attributed a key role in cognition. Little is known about the impact of epilepsy on sleep oscillations underlying sleep-related functions. This study assessed changes in the global spindle rate in patients with epilepsy, analysed the distribution of spindles in relation to the epileptic focus, and performed correlations with neurocognitive function. Twenty-one patients with drug-resistant focal epilepsy (12 females; mean age 32.6 ± 10.7 years [mean ± SD]) and 12 healthy controls (3 females; 24.5 ± 3.3 years) underwent combined whole-night high-density electroencephalography and polysomnography. Global spindle rates during N2 were lower in epilepsy patients compared to controls (mean = 5.78/min ± 0.72 vs. 6.49/min ± 0.71, p = 0.02, d =  − 0.70). Within epilepsy patients, spindle rates were lower in the region of the epileptic focus compared to the contralateral region (median = 4.77/min [range 2.53–6.18] vs. 5.26/min [2.53–6.56], p = 0.02, rank biserial correlation RC =  − 0.57). This decrease was driven by fast spindles (12–16 Hz) (1.50/min [0.62–4.08] vs. 1.65/min [0.51–4.28], p = 0.002, RC =  − 0.76). The focal reduction in spindles was negatively correlated with two scales of attention (r =  − 0.54, p = 0.01; r =  − 0.51, p = 0.025). Patients with focal epilepsy show a reduction in global and local spindle rates dependent on the region of the epileptic focus. This may play a role in impaired cognitive functioning. Future work will show if the local reduction in spindles can be used as potential marker of the epileptic focus.

Overnight Delta Dynamics Associated with Daytime Psychomotor Performance in Adults with Insomnia and Healthy Controls

PURPOSE

Sleep is vital to cognition, yet underlying mechanisms remain unclear. Although sleep duration and continuity are two well-established contributors, additional factors-including homeostatic sleep drive processes-may also underlie cognition-related sleep restoration. This study investigates the relative contributions of sleep EEG factors to psychomotor functioning in adults with insomnia and healthy controls (HC) to identify the most significant sleep factors supporting psychomotor functioning.

MATERIALS AND METHODS

Adults with insomnia (n = 37) and HC (n = 39) completed 3 nights of polysomnography and a complex psychomotor task (switching attention task; SAT). Univariate correlations identified the most significant predictors (traditional PSG, spectral EEG, initial delta peak, and overnight delta decline) of SAT performance, which were then entered into multivariable linear regressions examining whether predictors remained significant after accounting for shortened/fragmented sleep and whether relationships differed across groups.

RESULTS

In addition to greater wake after sleep onset (WASO; r = 0.33), a slower overnight delta decline (r = 0.50) and a lower initial delta peak (r = -0.38) were the most significant predictors of poorer SAT performance. Both overnight delta decline (F(7, 68) = 12.52, p < 0.001) and initial delta peak (F(7, 68) = 7.85, p = 0.007) remained significant predictors after controlling for demographics, total sleep time, and WASO. Relationships were analogous across subject groups.

CONCLUSION

Findings suggest that, in addition to sleep duration and continuity, processes related to recovery from and dissipation of homeostatic sleep drive may support psychomotor performance and broadly support daytime functioning in individuals with and without insomnia. Future research may examine overnight delta dynamics as transdiagnostic processes supporting cognition-related sleep restoration across a range of clinical populations.

Optimizing computation of overnight decline in delta power: Evidence for slower rate of decline in delta power in insomnia patients

OBJECTIVE

To determine the best of commonly used methods for computing the rate of decline in non-rapid eye movement (NREM) sleep EEG delta power overnight (Delta Decline) in terms of vulnerability to missing data and to evaluate whether this rate is slower in insomnia patients than healthy controls (HC).

METHODS

Fifty-one insomnia patients and 53 HC underwent 6 nights of polysomnography. Four methods for estimating Delta Decline were compared (exponential and linear best-fit functions using NREM (1) episode mean, (2) peak, and (3) total delta power and (4) delta power for all available NREM epochs). The best method was applied to compare groups on linear and exponential rates of Delta Decline.

RESULTS

Best-fit models using all available NREM epochs were significantly less vulnerable to deviation due to missing data than other methods. Insomnia patients displayed significantly slower linear and exponential Delta Decline than HC.

CONCLUSIONS

Computing Delta Decline using all available NREM epochs was the best of the methods studied for minimizing the effects of missing data. Insomnia patients display slower Delta Decline, which is not explained by differences in total sleep time or wake after sleep onset.

SIGNIFICANCE

This study supports using all available NREM epochs in Delta Decline computation and suggests a slower rate in insomnia.

The Effects of Transcranial Electrical Stimulation of the Brain on Sleep: A Systematic Review

Transcranial Electrical Stimulation (tES) is a promising non-invasive brain modulation tool. Over the past years, there have been several attempts to modulate sleep with tES-based approaches in both the healthy and pathological brains. However, data about the impact on measurable aspects of sleep remain scattered between studies, which prevent us from drawing firm conclusions. We conducted a systematic review of studies that explored the impact of tES on neurophysiological sleep oscillations, sleep patterns measured objectively with polysomnography, and subjective psychometric assessments of sleep in both healthy and clinical samples. We searched four main electronic databases to identify studies until February 2020. Forty studies were selected including 511 healthy participants and 452 patients. tES can modify endogenous brain oscillations during sleep. Results concerning changes in sleep patterns are conflicting, whereas subjective assessments show clear improvements after tES. Possible stimulation-induced mechanisms within specific cortico-subcortical sleep structures and networks are discussed. Although these findings cannot be directly transferred to the clinical practice and sleep-enhancing devices development for healthy populations, they might help to pave the way for future researches in these areas. PROSPERO registration number 178910.

Impact of menstrual cycle phase and oral contraceptives on sleep and overnight memory consolidation

Sleep spindles benefit declarative memory consolidation and are considered to be a biological marker for general cognitive abilities. However, the impact of sexual hormones and hormonal oral contraceptives (OCs) on these relationships are less clear. Thus, we here investigated the influence of endogenous progesterone levels of naturally cycling women and women using OCs on nocturnal sleep and overnight memory consolidation. Nineteen healthy women using OCs (M_Age = 21.4, SD = 2.1 years) were compared to 43 healthy women with a natural menstrual cycle (follicular phase: n = 16, M_Age = 21.4, SD = 3.1 years; luteal phase: n = 27, M_Age = 22.5, SD = 3.6 years). Sleep spindle density and salivary progesterone were measured during an adaptation and an experimental night. A word pair association task preceding the experimental night followed by two recalls (pre‐sleep and post‐sleep) was performed to test declarative memory performance. We found that memory performance improved overnight in all women. Interestingly, women using OCs (characterized by a low endogenous progesterone level but with very potent synthetic progestins) and naturally cycling women during the luteal phase (characterized by a high endogenous progesterone level) had a higher fast sleep spindle density compared to naturally cycling women during the follicular phase (characterized by a low endogenous progesterone level). Furthermore, we observed a positive correlation between endogenous progesterone level and fast spindle density in women during the luteal phase. Results suggest that the use of OCs and the menstrual cycle phase affects sleep spindles and therefore should be considered in further studies investigating sleep spindles and cognitive performance.

Reduced sleep spindle density in adolescent patients with early-onset schizophrenia compared to major depressive disorder and healthy controls

OBJECTIVES

During adolescence schizophrenia and major depressive disorder (MDD) increasingly emerge. Overlapping symptomatology during first presentation challenges the diagnostic process. Reduced sleep spindle density (SSD) was suggested as a biomarker in adults, discerning patients with schizophrenia from patients with depression or healthy controls (HC). We aimed to compare SSD in early-onset schizophrenia (EOS), with MDD, and HC, and to analyse associations of SSD with symptomatology and neurocognitive measures.

METHODS

Automatic sleep spindle detection was performed on all-night high-density EEG (128 electrodes) data of 12 EOS, 19 MDD, and 57 HC (age range 9.8-19), allowing an age- and sex-matching of 1:2 (patients vs. HC). Severity of current symptoms and neurocognitive variables were assessed in all patients.

RESULTS

SSD was defined between 13.75 and 14.50 Hz as within this frequency range SSD differed between EOS vs. HC in bin by bin analyses (12-15 Hz). In EOS, SSD was lower over 27 centro-temporal electrodes compared to HC and over 9 central electrodes compared to MDD. Reduced SSD in EOS compared to MDD and HC was accompanied by a high variability of SSD in all adolescents. SSD did not differ between MDD and HC. In the pooled sample of patients, lower SSD was associated with more severe Positive and Negative Symptoms Scale total score, more impaired memory consolidation and processing speed.

CONCLUSION

A high variability of SSD in all adolescents may reflect the evolving character of SSD. The association of reduced SSD with the symptom dimension of impaired cognition cuts across diagnostical entities.

High-voltage, diffuse delta rhythms coincide with wakeful consciousness and complexity in Angelman syndrome

Abundant evidence from slow wave sleep, anesthesia, coma, and epileptic seizures links high-voltage, slow electroencephalogram (EEG) activity to loss of consciousness. This well-established correlation is challenged by the observation that children with Angelman syndrome (AS), while fully awake and displaying volitional behavior, display a hypersynchronous delta (1–4 Hz) frequency EEG phenotype typical of unconsciousness. Because the trough of the delta oscillation is associated with down-states in which cortical neurons are silenced, the presence of volitional behavior and wakefulness in AS amidst diffuse delta rhythms presents a paradox. Moreover, high-voltage, slow EEG activity is generally assumed to lack complexity, yet many theories view functional brain complexity as necessary for consciousness. Here, we use abnormal cortical dynamics in AS to assess whether EEG complexity may scale with the relative level of consciousness despite a background of hypersynchronous delta activity. As characterized by multiscale metrics, EEGs from 35 children with AS feature significantly greater complexity during wakefulness compared with sleep, even when comparing the most pathological segments of wakeful EEG to the segments of sleep EEG least likely to contain conscious mentation and when factoring out delta power differences across states. These findings (i) warn against reverse inferring an absence of consciousness solely on the basis of high-amplitude EEG delta oscillations, (ii) corroborate rare observations of preserved consciousness under hypersynchronization in other conditions, (iii) identify biomarkers of consciousness that have been validated under conditions of abnormal cortical dynamics, and (iv) lend credence to theories linking consciousness with complexity.

Sleep Time in the European Starling Is Strongly Affected by Night Length and Moon Phase

Sleep is considered to be of crucial importance for performance and health, yet much of what we know about sleep is based on studies in a few mammalian model species under strictly controlled laboratory conditions. Data on sleep in different species under more natural conditions may yield new insights in the regulation and functions of sleep. We therefore performed a study with miniature electroencephalogram (EEG) data loggers in starlings under semi-natural conditions, group housed in a large outdoor enclosure with natural temperature and light. The birds showed a striking 5-h difference in the daily amount of non-rapid-eye-movement (NREM) sleep between winter and summer. This variation in the amount of NREM sleep was best explained by night length. Most sleep occurred during the night, but when summer nights became short, the animals displayed mid-day naps. The decay of NREM sleep spectral power in the slow-wave range (1.1-4.3 Hz) was steeper in the short nights than in the longer nights, which suggests that birds in summer have higher sleep pressure. Additionally, sleep was affected by moon phase, with 2 h of NREM sleep less during full moon. The starlings displayed very little rapid-eye-movement (REM) sleep, adding up to 1.3% of total sleep time. In conclusion, this study demonstrates a pronounced phenotypical flexibility in sleep in starlings under semi-natural conditions and shows that environmental factors have a major impact on the organization of sleep and wakefulness.

Objective measurement of sleep in mild cognitive impairment: A systematic review and meta-analysis

Older adults with mild cognitive impairment (MCI) are at-risk of developing dementia, particularly Alzheimer's disease. While some research suggests that alterations in sleep architecture may mediate cognitive decline, the nature and magnitude of changes to sleep macro- (sleep stages) and micro-architecture (electroencephalography (EEG) oscillations) in MCI is not yet clear. This study aimed to systematically review and meta-analyse case-control studies objectively measuring sleep in MCI. A systematic search was conducted using PubMed, Scopus, Web of Science, Embase and Psycinfo databases and after review, a total of 10 studies met inclusion criteria. Of these, all reported sleep macro-architecture and four reported micro-architecture outcomes. A combined total of 430 participants (209 with and 221 without MCI) underwent objective sleep assessments in the included full text articles. Findings show that compared to healthy controls, those with MCI have pronounced changes in sleep macro-architecture with greater wake after sleep onset, reduced total sleep time, lower sleep efficiency, longer sleep onset latency, longer rapid eye movement sleep (REM) latency, reduced REM sleep, greater N1 sleep, and worse severity of hypoxemia. Pooling of sleep micro-architecture EEG measures was not possible due to limited studies, however reduced spindles in non-REM sleep and greater EEG slowing in REM sleep were reported.

Sleep Spindles: Mechanisms and Functions

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

A preliminary investigation of the role of slow-wave activity in modulating waking EEG theta as a marker of sleep propensity in major depressive disorder

BACKGROUND

Both EEG slow-wave activity (SWA) during sleep and EEG theta activity during waking have been shown to increase with extended waking, and decrease following sleep, suggesting that both are markers of sleep propensity. In individuals with major depressive disorder (MDD), however, altered patterns of SWA have been noted, suggesting that sleep homeostasis is dysregulated. This study aimed to examine if slow-wave disruption would alter sleep propensity differently in healthy controls (HC) and those with MDD.

METHODS

25 individuals (13 diagnosed with MDD and 12 HC) participated. Following one night of adaptation sleep, participants underwent one night of baseline sleep, and one night of selective slow-wave disruption by auditory stimuli. In the evening, before sleep, and in the morning following sleep, waking EEG was recorded from participants in an upright position, with eyes open.

RESULTS

Repeated measures ANOVA revealed a significant three-way interaction, such that AM theta activity was significantly lower following slow-wave disruption in those with MDD, but not in HC. Additionally, SWA was not correlated with theta activity in MDD.

LIMITATIONS

These data are based on a relatively small sample size of unmedicated individuals with MDD.

CONCLUSIONS

These data may suggest that SWA plays a differential role in the homeostatic regulation of sleep in HC, and in MDD, and provide additional evidence that the presence of SWA may be maladaptive in MDD.

A hypothesis regarding how sleep can calibrate neuronal excitability in the central nervous system and thereby offer stability, sensitivity and the best possible cognitive function

The function of sleep in mammal and other vertebrates is one of the great mysteries of biology. Many hypotheses have been proposed, but few of these have made even the slightest attempt to explain the essence of sleep - the uncompromising need for reversible unconsciousness. During sleep, epiphenomena - often of a somatic character - occur, but these cannot explain the core function of sleep. One answer could be hidden in the observations made for long periods of time of the function of the central nervous system (CNS). The CNS is faced with conflicting requirements on stability and excitability. A high level of excitability is desirable, and is also a prerequisite for sensitivity and quick reaction times; however, it can also lead to instability and the risk of feedback, with life-threatening epileptic seizures. Activity-dependent negative feedback in neuronal excitability improves stability in the short term, but not to the degree that is required. A hypothesis is presented here demonstrating how calibration of individual neurons - an activity which occurs only during sleep - can establish the balanced and highest possible excitability while also preserving stability in the CNS. One example of a possible mechanism is the observation of slow oscillations in EEGs made on birds and mammals during slow wave sleep. Calibration to a genetically determined level of excitability could take place in individual neurons during the slow oscillation. This is only possible offline, which explains the need for sleep. The hypothesis can explain phenomena such as the need for unconsciousness during sleep, with the disconnection of sensory stimuli, slow EEG oscillations, the relationship of sleep and epilepsy, age, the effects of sleep on neuronal firing rate and the effects of sleep deprivation and sleep homeostasis. This is with regard primarily to mammals, including humans, but also all other vertebrates.

Association of electroencephalogram trajectories during emergence from anaesthesia with delirium in the postanaesthesia care unit: an early sign of postoperative complications

BACKGROUND

Postoperative delirium is associated with an increased risk of morbidity and mortality, especially in the elderly. Delirium in the postanaesthesia care unit (PACU) could predict adverse clinical outcomes.

METHODS

We investigated a potential link between intraoperative EEG patterns and PACU delirium as well as an association of PACU delirium with perioperative outcomes, readmission and length of hospital stay. The risk factors for PACU delirium were also explored. Data were collected from 626 patients receiving general anaesthesia for procedures that would not interfere with frontal EEG recording.

RESULTS

Of the 626 subjects enrolled, 125 tested positive for PACU delirium. Whilst age, renal failure, and pre-existing neurological disease were associated with PACU delirium in the univariable analysis, the multivariable analysis revealed the importance of information derived from the EEG, anaesthetic technique, anaesthesia duration, and history of stroke or neurodegenerative disease. The occurrence of EEG burst suppression during maintenance [odds ratio (OR)=1.86 (1.13-3.05)] and the type of EEG emergence trajectory may be predictive of PACU delirium. Specifically, EEG emergence trajectories lacking significant spindle power were strongly associated with PACU delirium, especially in cases that involved ketamine or nitrous oxide [OR=6.51 (3.00-14.12)]. Additionally, subjects with PACU delirium were at an increased risk for readmission [OR=2.17 (1.13-4.17)] and twice as likely to stay >6 days in the hospital.

CONCLUSIONS

Specific EEG patterns were associated with PACU delirium. These findings provide valuable information regarding how the brain reacts to surgery and anaesthesia that may lead to strategies to predict PACU delirium and identify key areas of investigation for its prevention.

Absent sleep EEG spindle activity in GluA1 (Gria1) knockout mice: relevance to neuropsychiatric disorders

Sleep EEG spindles have been implicated in attention, sensory processing, synaptic plasticity and memory consolidation. In humans, deficits in sleep spindles have been reported in a wide range of neurological and psychiatric disorders, including schizophrenia. Genome-wide association studies have suggested a link between schizophrenia and genes associated with synaptic plasticity, including the Gria1 gene which codes for the GluA1 subunit of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor. Gria1^-/- mice exhibit a phenotype relevant for neuropsychiatric disorders, including reduced synaptic plasticity and, at the behavioural level, attentional deficits leading to aberrant salience. In this study we report a striking reduction of EEG power density including the spindle-frequency range (10-15 Hz) during sleep in Gria1^-/- mice. The reduction of spindle-activity in Gria1^-/- mice was accompanied by longer REM sleep episodes, increased EEG slow-wave activity in the occipital derivation during baseline sleep, and a reduced rate of decline of EEG slow wave activity (0.5-4 Hz) during NREM sleep after sleep deprivation. These data provide a novel link between glutamatergic dysfunction and sleep abnormalities in a schizophrenia-relevant mouse model.

Impact of sex steroids and reproductive stage on sleep-dependent memory consolidation in women

Age and sex are two of the three major risk factors for Alzheimer's disease (ApoE-e4 allele is the third), with women having a twofold greater risk for Alzheimer's disease after the age of 75 years. Sex differences have been shown across a wide range of cognitive skills in young and older adults, and evidence supports a role for sex steroids, especially estradiol, in protecting against the development of cognitive decline in women. Sleep may also be a protective factor against age-related cognitive decline, since specific electrophysiological sleep events (e.g. sleep spindle/slow oscillation coupling) are critical for offline memory consolidation. Furthermore, studies in young women have shown fluctuations in sleep events and sleep-dependent memory consolidation during different phases of the menstrual cycle that are associated with the levels of sex steroids. An under-appreciated possibility is that there may be an important interaction between these two protective factors (sex steroids and sleep) that may play a role in daily fluctuations in cognitive processing, in particular memory, across a woman's lifespan. Here, we summarize the current knowledge of sex steroid-dependent influences on sleep and cognition across the lifespan in women, with special emphasis on sleep-dependent memory processing. We further indicate gaps in knowledge that require further experimental examination in order to fully appreciate the complex and changing landscape of sex steroids and cognition. Lastly, we propose a series of testable predictions for how sex steroids impact sleep events and sleep-dependent cognition across the three major reproductive stages in women (reproductive years, menopause transition, and post-menopause).

Development of nap neurophysiology: preliminary insights into sleep regulation in early childhood

Although all young children nap, the neurophysiological features and associated developmental trajectories of daytime sleep remain largely unknown. Longitudinal studies of napping physiology are fundamental to understanding sleep regulation during early childhood, a sensitive period in brain and behaviour development and a time when children transition from a biphasic to a monophasic sleep-wakefulness pattern. We investigated daytime sleep in eight healthy children with sleep electroencephalography (EEG) assessments at three longitudinal points: 2 years (2.5-3.0 years), 3 years (3.5-4.0 years) and 5 years (5.5-6.0 years). At each age, we measured nap EEG during three randomized conditions: after 4 h (morning nap), 7 h (afternoon nap) and 10 h (evening nap) duration of prior wakefulness. Developmental changes in sleep were most prevalent in the afternoon nap (e.g. decrease in sleep duration by 30 min from 2 to 3 years and by 20 min from 3 to 5 years). In contrast, nap sleep architecture (% of sleep stages) remained unchanged across age. Maturational changes in non-rapid eye movement sleep EEG power were pronounced in the slow wave activity (SWA, 0.75-4.5 Hz), theta (4.75-7.75 Hz) and sigma (10-15 Hz) frequency ranges. These findings indicate that the primary marker of sleep depth, SWA, is less apparent in daytime naps as children mature. Moreover, our fundamental data provide insight into associations between sleep regulation and functional modifications in the central nervous system during early childhood.

Application of Transcranial Direct Current Stimulation in Neurorehabilitation: The Modulatory Effect of Sleep

The relationship between sleep disorders and neurological disorders is often reciprocal, such that sleep disorders are worsened by neurological symptoms and that neurological disorders are aggravated by poor sleep. Animal and human studies further suggest that sleep disruption not only worsens single neurological symptoms but may also lead to long-term negative outcomes. This suggests that sleep may play a fundamental role in neurorehabilitation and recovery. We further propose that sleep may not only alter the efficacy of behavioral treatments but also plasticity-enhancing adjunctive neurostimulation methods, such as transcranial direct current stimulation (tDCS). At present, sleep receives little attention in the fields of neurorehabilitation and neurostimulation. In this review, we draw together the strands of evidence from both fields of research to highlight the proposition that sleep is an important parameter to consider in the application of tDCS as a primary or adjunct rehabilitation intervention.

Spindle Oscillations in Sleep Disorders: A Systematic Review

Measurement of sleep microarchitecture and neural oscillations is an increasingly popular technique for quantifying EEG sleep activity. Many studies have examined sleep spindle oscillations in sleep-disordered adults; however reviews of this literature are scarce. As such, our overarching aim was to critically review experimental studies examining sleep spindle activity between adults with and without different sleep disorders. Articles were obtained using a systematic methodology with a priori criteria. Thirty-seven studies meeting final inclusion criteria were reviewed, with studies grouped across three categories: insomnia, hypersomnias, and sleep-related movement disorders (including parasomnias). Studies of patients with insomnia and sleep-disordered breathing were more abundant relative to other diagnoses. All studies were cross-sectional. Studies were largely inconsistent regarding spindle activity differences between clinical and nonclinical groups, with some reporting greater or less activity, while many others reported no group differences. Stark inconsistencies in sample characteristics (e.g., age range and diagnostic criteria) and methods of analysis (e.g., spindle bandwidth selection, visual detection versus digital filtering, absolute versus relative spectral power, and NREM2 versus NREM3) suggest a need for greater use of event-based detection methods and increased research standardization. Hypotheses regarding the clinical and empirical implications of these findings, and suggestions for potential future studies, are also discussed.

Circadian regulation of slow waves in human sleep: Topographical aspects

Slow waves (SWs, 0.5–4 Hz) in field potentials during sleep reflect synchronized alternations between bursts of action potentials and periods of membrane hyperpolarization of cortical neurons. SWs decline during sleep and this is thought to be related to a reduction of synaptic strength in cortical networks and to be central to sleep's role in maintaining brain function. A central assumption in current concepts of sleep function is that SWs during sleep, and associated recovery processes, are independent of circadian rhythmicity. We tested this hypothesis by quantifying all SWs from 12 EEG derivations in 34 participants in whom 231 sleep periods were scheduled across the circadian cycle in a 10-day forced-desynchrony protocol which allowed estimation of the separate circadian and sleep-dependent modulation of SWs. Circadian rhythmicity significantly modulated the incidence, amplitude, frequency and the slope of the SWs such that the peaks of the circadian rhythms in these slow-wave parameters were located during the biological day. Topographical analyses demonstrated that the sleep-dependent modulation of SW characteristics was most prominent in frontal brain areas whereas the circadian effect was similar to or greater than the sleep-dependent modulation over the central and posterior brain regions.

The data demonstrate that circadian rhythmicity directly modulates characteristics of SWs thought to be related to synaptic plasticity and that this modulation depends on topography. These findings have implications for the understanding of local sleep regulation and conditions such as ageing, depression, and neurodegeneration which are associated with changes in SWs, neural plasticity and circadian rhythmicity.

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Slow waves (SWs) are thought essential for sleep-dependent recovery processes.

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Their amplitude, incidence, frequency and slope reflect synaptic strength.

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Their regulation has been postulated to be independent of circadian phase.

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We report that all characteristics of SWs depend on circadian phase.

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The strength of sleep dependent and circadian modulation depends on topography.

Sustained sleep fragmentation induces sleep homeostasis in mice

STUDY OBJECTIVES

Sleep fragmentation (SF) is an integral feature of sleep apnea and other prevalent sleep disorders. Although the effect of repetitive arousals on cognitive performance is well documented, the effects of long-term SF on electroencephalography (EEG) and molecular markers of sleep homeostasis remain poorly investigated. To address this question, we developed a mouse model of chronic SF and characterized its effect on EEG spectral frequencies and the expression of genes previously linked to sleep homeostasis including clock genes, heat shock proteins, and plasticity-related genes.

DESIGN

N/A.

SETTING

Animal sleep research laboratory.

PARTICIPANTS

Sixty-six C57BL6/J adult mice.

INTERVENTIONS

Instrumental sleep disruption at a rate of 60/h during 14 days.

MEASUREMENTS AND RESULTS

Locomotor activity and EEG were recorded during 14 days of SF followed by recovery for 2 days. Despite a dramatic number of arousals and decreased sleep bout duration, SF minimally reduced total quantity of sleep and did not significantly alter its circadian distribution. Spectral analysis during SF revealed a homeostatic drive for slow wave activity (SWA; 1-4 Hz) and other frequencies as well (4-40 Hz). Recordings during recovery revealed slow wave sleep consolidation and a transient rebound in SWA, and paradoxical sleep duration. The expression of selected genes was not induced following chronic SF.

CONCLUSIONS

Chronic SF increased sleep pressure confirming that altered quality with preserved quantity triggers core sleep homeostasis mechanisms. However, it did not induce the expression of genes induced by sleep loss, suggesting that these molecular pathways are not sustainably activated in chronic diseases involving SF.

NREM and REM Sleep: Complementary Roles in Recovery after Wakefulness

The overall function of sleep is hypothesized to provide "recovery" after preceding waking activities, thereby ensuring optimal functioning during subsequent wakefulness. However, the functional significance of the temporal dynamics of sleep, manifested in the slow homeostatic process and the alternation between non-rapid eye movement (NREM) and REM sleep remains unclear. We propose that NREM and REM sleep have distinct and complementary contributions to the overall function of sleep. Specifically, we suggest that cortical slow oscillations, occurring within specific functionally interconnected neuronal networks during NREM sleep, enable information processing, synaptic plasticity, and prophylactic cellular maintenance ("recovery process"). In turn, periodic excursions into an activated brain state-REM sleep-appear to be ideally placed to perform "selection" of brain networks, which have benefited from the process of "recovery," based on their offline performance. Such two-stage modus operandi of the sleep process would ensure that its functions are fulfilled according to the current need and in the shortest time possible. Our hypothesis accounts for the overall architecture of normal sleep and opens up new perspectives for understanding pathological conditions associated with abnormal sleep patterns.

Optogenetically induced sleep spindle rhythms alter sleep architectures in mice

Sleep spindles are rhythmic patterns of neuronal activity generated within the thalamocortical circuit. Although spindles have been hypothesized to protect sleep by reducing the influence of external stimuli, it remains to be confirmed experimentally whether there is a direct relationship between sleep spindles and the stability of sleep. We have addressed this issue by using in vivo photostimulation of the thalamic reticular nucleus of mice to generate spindle oscillations that are structurally and functionally similar to spontaneous sleep spindles. Such optogenetic generation of sleep spindles increased the duration of non-rapid eye movement (NREM) sleep. Furthermore, the density of sleep spindles was correlated with the amount of NREM sleep. These findings establish a causal relationship between sleep spindles and the stability of NREM sleep, strongly supporting a role for the thalamocortical circuit in sleep regulation.

Sleep slow-wave activity regulates cerebral glycolytic metabolism

Non-rapid eye movement sleep (NREMS) onset is characterized by a reduction in cerebral metabolism and an increase in slow waves, 1-4-Hz oscillations between relatively depolarized and hyperpolarized states in the cerebral cortex. The metabolic consequences of slow-wave activity (SWA) at the cellular level remain uncertain. We sought to determine whether SWA modulates the rate of glycolysis within the cerebral cortex. The real-time measurement of lactate concentration in the mouse cerebral cortex demonstrates that it increases during enforced wakefulness. In spontaneous sleep/wake cycles, lactate concentration builds during wakefulness and rapid eye movement sleep and declines during NREMS. The rate at which lactate concentration declines during NREMS is proportional to the magnitude of electroencephalographic (EEG) activity at frequencies of <10 Hz. The induction of 1-Hz oscillations, but not 10-Hz oscillations, in the electroencephalogram by optogenetic stimulation of cortical pyramidal cells during wakefulness triggers a decline in lactate concentration. We conclude that cerebral SWA promotes a decline in the rate of glycolysis in the cerebral cortex. These results demonstrate a cellular energetic function for sleep SWA, which may contribute to its restorative effects on brain function.

Behavioural evidence for a sleep-like quiescent state in a pulmonate mollusc, Lymnaea stagnalis (Linnaeus)

The objective of this study was to determine whether the great pond snail, Lymnaea stagnalis, expresses a sleep-like behavioural state. We found that snails spontaneously enter a relatively brief (22±1 min) quiescent state characterized by postural relaxation of the foot, mantle and tentacles, and cessation of radula rasping. Quiescence was reversed ('aroused') by appetitive (sucrose solution) and aversive (tactile) stimuli. Responsiveness to both stimuli was significantly lower in quiescent snails than in active snails. However, tactile stimuli evoked a more sustained defensive response in quiescent snails. Quiescence bouts were consolidated into 'clusters' over an infradian timescale and were only weakly affected by time of day. Clusters contained 7±0.5 bouts, lasted 13±1 h and were separated by long (37±4 h) intervals of almost continuous activity. Analysis of Kaplan-Meier survival curves revealed that the quiescent bout duration was described by an exponential probability distribution (time constant 15±1 min). Active bout duration was described by a bi-exponential probability distribution (time constants 62±4 and 592±48 min). We found no evidence for a 'sleep rebound' mechanism and quiescence expression appeared to be regulated through stochastic processes causing state transitions to resemble a Markovian random walk. We conclude that Lymnaea is a potentially valuable model system for studies of cellular function in sleep.

Atypical sleep architecture and altered EEG spectra in Williams syndrome

BACKGROUND

Williams syndrome (WS) is a neurodevelopmental genetic disorder characterised by physical abnormalities and a distinctive cognitive profile with intellectual disabilities (IDs) and learning difficulties.

METHODS

In our study, nine adolescents and young adults with WS and 9 age- and sex-matched typically developing (TD) participants underwent polysomnography. We examined sleep architecture, leg movements and the electroencephalogram (EEG) spectra of specific frequency bands at different scalp locations.

RESULTS

We found an atypical, WS characteristic sleep pattern with decreased sleep time, decreased sleep efficiency, increased wake time after sleep onset, increased non-rapid eye movement percentage, increased slow wave sleep, decreased rapid eye movement sleep percentage, increased number of leg movements and irregular sleep cycles. Patients with WS showed an increased delta and slow wave activity and decreased alpha and sigma activity in the spectral analysis of the EEG.

CONCLUSIONS

Sleep maintenance and organisation are significantly affected in WS, while EEG spectra suggest increases in sleep pressure.

Functional neuroimaging insights into the physiology of human sleep

Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep.

Characteristics of sleep EEG power spectra in healthy infants in the first two years of life

OBJECTIVE

This study characterises and describes the maturational evolution of the healthy infant sleep electroencephalogram (EEG) longitudinally from 2 weeks to 24 months of age, by means of power spectral analysis.

METHODS

A prospective cohort of 34 healthy infants underwent overnight polysomnography (PSG) at 2 weeks, and at 3, 6, 12 and 24 months of age. Sleep epochs were scored as Active Sleep (AS) and Quiet Sleep (QS) at 2 weeks of age and as Rapid Eye Movement (REM) and Non-REM (NREM) stages from 3 months onwards. Representative epochs were used to generate the EEG power spectra, from the central C3 derivation. These were analysed visually and quantitatively in AS/REM and QS/NREM sleep in the following bandwidths: delta (0.5-4 Hz); theta (4-8 Hz); alpha (8-11 Hz); sigma (11-15 Hz) and 0.5-25 Hz.

RESULTS

Sleep EEG (central derivation) power spectra changed significantly in the different bandwidths as the infants matured. The emergence of a peak in the sigma bandwidth in NREM N2 sleep corresponded with the development of sleep spindles. Maturational changes were also seen in NREM N3 and in theta and alpha bandwidths in both AS/REM and QS/NREM.

CONCLUSIONS

Sleep EEG power spectra characteristics in healthy infants evolve in keeping with maturation and neurodevelopmental milestones.

SIGNIFICANCE

This study provides an atlas of healthy infant sleep EEG in the early years of life, providing a basis for association with other neurodevelopmental measures and a normative dataset on which disease may be discriminated.

Topographical frequency dynamics within EEG and MEG sleep spindles

OBJECTIVE

Spindles are rhythmic bursts of 10-16 Hz activity, lasting ∼1 s, occur during normal stage 2 sleep. Spindles are slower in frontal EEG and possibly MEG. The posterior-fast EEG pattern may predominate early in the spindle, and the anterior-slow pattern late. We aimed to determine the proportion of spindles showing this spatio-spectro-temporal interaction for EEG, and whether it occurs in MEG.

METHODS

We recorded high density EEG and MEG from seven healthy subjects during normal stage 2 sleep. High vs. low frequency (12 vs. 14 Hz) power was measured early vs. late (25th-45th vs. 55th-75th duration percentile) in 183 spindle discharges.

RESULTS

The predicted spatio-spectro-temporal interaction was shown by 48% of EEG and 34% of MEG spindles (chance=25%). Topographically, high frequency EEG power was greatest at midline central contacts, and low frequency power at midline frontal. This frequency-specific topography was fixed over the course of the spindle.

CONCLUSIONS

An evolution from posterior-fast to anterior-slow generators commonly occurs during spindles, and this is visible with EEG and to a lesser extent, MEG.

SIGNIFICANCE

The spatio-spectral-temporal evolution of spindles may reflect their possible involvement in coordinating cortical activity during consolidation.

Slow-wave sleep deficiency and enhancement: implications for insomnia and its management

In humans, slow-wave sleep (SWS) consists of stages 3 and 4 of non rapid eye movement (nonREM) sleep. The low-frequency, high-amplitude slow waves that dominate the electroencephalogram (EEG) during SWS can be quantified as slow-wave activity (SWA). SWS and SWA are regulated very accurately in response to variations in the duration and intensity of wakefulness and sleep. SWA declines more or less independently of circadian phase during the course of a sleep episode, indicating that it is primarily under homeostatic rather than circadian control. An age-related decline in SWS and SWA is well established. In some studies, apprehension, depression and insomnia have been associated with reductions in SWS and SWA. Experimental reductions of SWS through SWS deprivation (without altering total sleep time or REM duration) have been reported to lead to an increase in daytime sleep propensity and reductions in performance. SWS and SWA are therefore thought to contribute to the recovery processes that occur during sleep. Most currently prescribed hypnotics, such as the benzodiazepines and Z-drugs, suppress SWA. Some compounds have been shown to enhance SWS and SWA in healthy volunteers through GAT-1 inhibition, GABA-A modulation, GABA-B modulation, and 5HT2(A) antagonism. Pharmacological enhancement of SWS has also been observed in insomnia. The effects of SWS enhancement on other sleep parameters will be discussed.

Sleep and Infant Learning

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.

Time-frequency analysis methods to quantify the time-varying microstructure of sleep EEG spindles: possibility for dementia biomarkers?

The time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies and can be quantified with a number of techniques. In this paper, real and simulated sleep spindles were regarded as AM/FM signals modeled by six parameters that define the instantaneous envelope (IE) and instantaneous frequency (IF) waveforms for a sleep spindle. These parameters were estimated using four different methods, namely the Hilbert transform (HT), complex demodulation (CD), matching pursuit (MP) and wavelet transform (WT). The average error in estimating these parameters was lowest for HT, higher but still less than 10% for CD and MP, and highest (greater than 10%) for WT. The signal distortion induced by the use of a given method was greatest in the case of HT and MP. These two techniques would necessitate the removal of about 0.4s from the spindle data, which is an important limitation for the case of spindles with duration less than 1s. Although the CD method may lead to a higher error than HT and MP, it requires a removal of only about 0.23s of data. An application of this sleep spindle parameterization via the CD method is proposed, in search of efficient EEG-based biomarkers in dementia. Preliminary results indicate that the proposed parameterization may be promising, since it can quantify specific differences in IE and IF characteristics between sleep spindles from dementia subjects and those from aged controls.

Dex/CRH-test response and sleep in depressed patients and healthy controls with and without vulnerability for affective disorders

Sleep electroencephalographic (EEG) abnormalities and increased hypothalamo-pituitary-adrenal (HPA) axis activity are the most prominent neurobiological findings in depression and were suggested as potential biomarker for depression. In particular, increased rapid eye movement sleep (REM) density, deficit in slow wave sleep and excessive stress hormone response are associated with an unfavorable long-term outcome of depression. Recent studies indicate that the sleep and endocrine parameters are related to each other. This study investigated the association of sleep structure including a quantitative EEG analysis with the results of the combined dexamethasone (Dex)/corticotropin-releasing hormone (CRH)-test in 14 patients with a severe major depression, 21 healthy probands with a positive family history of depression (HRPs) and 12 healthy control subjects without personal and family history for psychiatric disorders. As expected patients with depression showed an overactivity of the HPA axis, disturbed sleep continuity and prolonged latency until slow wave sleep in the first sleep cycle. Differences in microarchitecture of sleep were less prominent and restricted to a higher NonREM sigma power in the HRP group. Dexamethasone suppressed cortisol levels were positively associated with higher NonREM sigma power after merging the three groups. We also observed an inverse association between the ACTH response to the Dex/CRH-test and rapid eye movement sleep (REM) density in HRPs, with suggestive evidence also in patients, but not in controls. This contra-intuitive finding might be a result of the subject selection (unaffected HRPs, severely depressed patients) and the complementarity of the two markers. HRPs and patients with high disease vulnerability, indicated by an elevated REM density, seem to have a lower threshold until an actual disease process affecting the HPA axis translates into depression, and vice versa. To summarize, our findings provide further evidence that the HPA axis is involved in the sleep regulation in depression. These associations, however, are not unidimensional, but dependent on the kind of sleep parameters as well as on the selection of the subjects.

The Munich vulnerability study on affective disorders: microstructure of sleep in high-risk subjects

Vulnerability markers for affective disorders have focused on stress hormone regulation and sleep. Among rapid eye movement (REM) sleep, increased REM pressure and elevated REM density are promising candidates for vulnerability markers. Regarding nonREM sleep, a deficit in amount of and latency until slow wave sleep during the first half of the night is a characteristic for depression. To further elucidate whether changes in the microstructure of sleep may serve as vulnerability markers we investigated the premorbid sleep composition in 21 healthy high-risk proband (HRPs) with a positive family history for affective disorders and compared HRPs with a control group of healthy subjects (HCs) without personal and family history for psychiatric disorders. The sleep electroencephalogram (EEG) was conventionally scored and submitted to a quantitative EEG analysis. The main difference in sleep characteristics between HRPs and HCs was an abnormally increased REM density. Differences in the spectral composition of sleep EEG were restricted to an increased power in the sigma frequency range. Since the HRP group comprised six unrelated and 15 related subjects we controlled for sibling effects. We could replicate the increased REM density in the group of HRPs whereas elevated power in the low sigma frequencies persisted only with approaching significance. The present study further supports elevated REM density as putative vulnerability marker for affective disorders. However, sleep EEG in our group of HRPs did not show slow wave sleep abnormalities. Ongoing follow up investigations of HRPs will clarify whether the observed increase in sigma EEG activity during nonREM sleep is of clinical relevance with respect to the likelihood to develop an affective disorder.

Sleep quality and the sleep electroencephalogram in women with severe premenstrual syndrome

STUDY OBJECTIVES

Women with severe premenstrual syndrome (PMS) or premenstrual dysphoric disorder (PMDD) commonly report sleep disturbances, but the few studies using conventional polysomnographic measures have produced conflicting results. We investigated sleep quality and sleep composition using conventional and quantitative electroencephalographic analyses in women with severe PMS, as compared with that of controls.

DESIGN AND PARTICIPANTS

Women (aged 18-40 years) were screened to ensure that their PMS symptoms were severe and that they had ovulatory menstrual cycles. Nine women with PMS or PMDD and 12 asymptomatic control subjects then had laboratory-based polysomnographic recordings at 2 phases of the menstrual cycle: follicular phase and late luteal (premenstrual) phase.

RESULTS

Women with severe PMS reported a significantly poorer subjective sleep quality during the late luteal phase (P = 0.02), but there was no evidence of disturbed sleep based on the polysomnogram specific to premenstrual symptom expression: both groups of women had increased wakefulness after sleep onset (P = 0.02) and increased sigma power (P < 0.01), especially in the 14-to 15-Hz band during non-rapid eye movement sleep, in the late luteal phase compared with the follicular phase. There were, however, some group differences in electroencephalographic measures regardless of menstrual phase, including decreased delta incidence (P = 0.02) and increased theta incidence and amplitude (P < 0.05) in women with PMS, suggesting the possibility of sleep electroencephalogram trait markers in women with PMS.

CONCLUSION

Perceived poor quality sleep is a characteristic of severe PMS, but sleep composition based on polysomnographic measures and quantitative electroencephalographic analysis does not differ in association with premenstrual symptom expression in the late luteal phase.

HPA axis and sleep: identifying subtypes of major depression

It is increasingly acknowledged that the diagnosis of major depression encompasses patients who do not necessarily share the same disease biology. Though the diagnostic criteria allow the specification of different subtypes, e.g. melancholic and atypical features, a consensus still has to be reached with regard to the clinical symptoms that clearly delineate these subtypes. Beside clinical characteristics, biological markers may help to further improve identification of biologically distinct endophenotypes and, ultimately, to devise more specific treatment strategies. Alterations of the hypothalamus-pituitary-adrenal (HPA) axis and sleep architecture are not only commonly observed in patients with major depression, but the nature and extent of these alterations can help to identify distinct subtypes. Thus, a HPA overdrive, due to enhanced secretion of corticotropin-releasing hormone (CRH) and an impaired negative feedback via glucocorticoid receptors, seems to be most consistently observed in patients with melancholic features. These patients also show the clearest sleep-electroencephalogram (EEG) alterations, including disrupted sleep, low amounts of slow wave sleep (SWS), a short rapid eye movement (REM) latency and a high REM density. In contrast, patients with atypical features are characterized by reduced activity of the HPA axis and ascending noradrenergic neurons in the locus coeruleus. Though sleep-EEG alterations have been less thoroughly examined in these patients, there are data to suggest that SWS is not reduced and that REM sleep parameters are not consistently altered. While the atypical and melancholic subtypes of major depression may represent the extremes of a spectrum, the distinct clinical features provide an opportunity to further explore biological markers, as well as environmental factors, contributing to these clinical phenotypes. Moreover, dysregulations of the HPA axis and sleep-EEG alterations can also be induced in rodents, thereby allowing alignment of critical biological aspects of a human disease subtype with an animal model. Such "Translational Research" efforts should help to develop targeted therapies for distinct patient populations.

Anteroposterior Difference in EEG Sleep Depth Measure is Reduced in Apnea Patients

In the present work, mean frequencies of FFT amplitude spectra from six EEG derivations were used to provide a frontopolar, a central and an occipital sleep depth measure. Parameters quantifying the anteroposterior differences in these three sleep depth measures during the night were also developed. The method was applied to analysis of 30 all-night recordings from 15 healthy control subjects and 15 apnea patients. Control subjects showed larger differences in sleep depth between frontopolar and central positions than the apnea patients. The relatively reduced frontal sleep depth in apnea patients might reflect the disruption of the dynamic sleep process caused by apneas.

Sleep spindle detection using artificial neural networks trained with filtered time-domain EEG: a feasibility study

An artificial neural network (ANN) based on the Multi-Layer Perceptron (MLP) architecture is used for detecting sleep spindles in band-pass filtered electroencephalograms (EEG), without feature extraction. Following optimum classification schemes, the sensitivity of the network ranges from 79.2% to 87.5%, while the false positive rate ranges from 3.8% to 15.5%. Furthermore, due to the operation of the ANN on time-domain EEG data, there is agreement with visual assessment concerning temporal resolution. Specifically, the total inter-spindle interval duration and the total duration of spindles are calculated with 99% and 92% accuracy, respectively. Therefore, the present method may be suitable for investigations of the dynamics among successive inter-spindle intervals, which could provide information on the role of spindles in the sleep process, and for studies of pharmacological effects on sleep structure, as revealed by the modification of total spindle duration.

Toward an integrative theory of sleep and dreaming

Non-rapid-eye-movement sleep (NREMS) is triggered by the accumulation of adenosine, as a result of the perceptual overload of the brain cortex. NREMS starts in the most burdened regions of the cortex first and then eventually, after the released adenosine has reached the ventrolateral pre-optic nucleus area of the hypothalamus, triggers the "general NREMS pattern". This is accompanied by the usual familiar changes in the thalamocortical system. When NREMS reaches the slow-wave sleep (SWS) phase, with its predominant delta activity, brain metabolism drops significantly with the brain temperature, and this is recognized by the alarm system in the pre-optic anterior hypothalamus and/or the other thermostat circuit in the brainstem as a life-threatening situation. This alarm system triggers a reaction similar to abortive or partial awakening called rapid-eye-movement sleep (REMS), which is aimed at restoring the optimal body-core temperature. As soon as this restoration is accomplished by the activation of the brainstem-to-cortex ascending pathways, NREMS may continue, as may the interchange of the two sleep phases during the entire sleep period. During both NREMS and REMS, the same essential pattern occurs in the cortex: the loops "used" during the previous waking period, now deprived of external input, replay their waking activity at a lower frequency, one which enables them to restore the membrane's potential (possibly by means of LTD). During REMS, however, the cholinergic flood originating in the LTD/PPT nuclei of the pons tegmentum, increases in the basal forebrain and, provoking theta activity in the medial septum is extended to the hippocampus, causing the circuits that are active at that particular moment in the cortex, to store the information they carry as memory. This is the explanation of both the memory improvement known to be related to REMS and of dreams. Both phenomena are clearly side effects of REMS.

The Role of Neural Synchronization in the Emergence of Cognition Across the Wake-Sleep Cycle

Searching for the neural code underlying consciousness and cognition is one of the most important activities in contemporary neuroscience. Research with neuronal oscillations at the level of single-neuron, local cell assemblies, and network system have provided invaluable insights into different mechanisms of synaptic interactions involved in the emergence of cognitive acts. A cognitive neuroscience of conscious experience is gradually emerging from behavioral and neuroimaging studies, which can be successfully complemented with the quantitative EEG findings discussed here. This review is an attempt to highlight the value of state-dependent changes in human neurophysiology for a better understanding of the neurobiological substrate underlying those aspects of cognition drastically affected by sleep states. Recent advances related to synchronization mechanisms potentially involved in brain integration processes are discussed, emphasizing the value of scalp and intracranial EEG recordings at determining local and large-scale dynamics in the human brain. Evidence supporting the critical role of state-dependent synchrony in brain integration comes mainly from studies on the theta and gamma oscillations across the wake-sleep continuum, as revealed by human intracranial recordings. This review blends results from different levels of analysis with the firm conviction that state-dependent brain dynamics at different levels of neural integration can provide a deeper understanding of neurobiological correlates of consciousness and sleep functions.