Homeostatic behavior of fast fourier transform power in very low frequency non-rapid eye movement human electroencephalogram

Louis EK, McCarter SJ, Bukartyk J, Przybelski SA, Kamykowski MG, Spychalla AJ, Machulda MM, Boeve BF, Petersen RC, Jack CR, Lowe VJ, Graff-Radford J, Worrell GA, Somers VK, Varga AW, Vemuri P. Non-rapid eye movement sleep slow-wave activity features are associated with amyloid accumulation in older adults with obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer's disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5-0.9 Hz) and delta (1-3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by -0.0082 (95% CI: -0.0143; -0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology.

Sleep Delta power, age, and sex effects in treatment-resistant depression

Electroencephalographic (EEG) deficits in slow wave activity or Delta power (0.5-4 Hz) indicate disturbed sleep homeostasis and are hallmarks of depression. Sleep homeostasis is linked to restorative sleep and potential antidepressant response via non-rapid eye movement (NREM) slow wave sleep (SWS) during which neurons undergo essential repair and rejuvenation. Decreased Low Delta power (0.5-2 Hz) was previously reported in individuals with depression. This study investigated power levels in the Low Delta (0.5-<2 Hz), High Delta (2-4 Hz), and Total Delta (0.5-4 Hz) bands and their association with age, sex, and disrupted sleep in treatment-resistant depression (TRD). Mann-Whitney U tests were used to compare the nightly progressions of Total Delta, Low Delta, and High Delta in 100 individuals with TRD and 24 healthy volunteers (HVs). Polysomnographic parameters were also examined, including Total Sleep Time (TST), Sleep Efficiency (SE), and Wake after Sleep Onset (WASO). Individuals with TRD had lower Delta power during the first NREM episode (NREM1) than HVs. The deficiency was observed in the Low Delta band versus High Delta. Females with TRD had higher Delta power than males during the first NREM1 episode, with the most noticeable sex difference observed in Low Delta. In individuals with TRD, Low Delta power correlated with WASO and SE, and High Delta correlated with WASO. Low Delta power deficits in NREM1 were observed in older males with TRD, but not females. These results provide compelling evidence for a link between age, sex, Low Delta power, sleep homeostasis, and non-restorative sleep in TRD.

Subjective sleep assessments are correlated with EEG-related sleep measurements of the first sleep cycle in healthy young adults

This study examined whether subjective and objective sleep parameters (sleep stage, electroencephalography [EEG] power, heart rate variability) are related to the progression of sleep cycles using differences in the variables between two nights. We hypothesized that the association between night-to-night differences between subjective and objective sleep variables reflect the difference in objective sleep variables in the first sleep cycle. Seventy-seven healthy adults (23.8 ± 2.2 years; 41 females) participated in polysomnographic recordings on two consecutive nights. To extract the variables that represent the difference between the nights, the sleep parameters of Night 1 were subtracted from those of Night 2. Spearman's rho was used to assess correlations between subjective sleep assessments and objective sleep parameters, with false discovery rate correction for multiple comparisons. Subjective sleep assessments were significantly correlated with whole-night sleep architecture and quantitative EEG activity, but not with heart rate variability during the night. Among sleep cycles, subjective sleep parameters were correlated with the objective sleep parameters in the first sleep cycle ("Ease of falling asleep" vs. waking after sleep onset [r = - 0.382], "Depth of sleep" vs. EEG theta power [r = 0.404], "Quality of sleep" vs. the percentage of stage N3 [r = 0.412] and EEG delta power [r = 0.458], all p < 0.05). These results suggest the importance of taking the difference among the nights into account when assessing subjective sleep quality. This study clarified that sleep in the first sleep cycle has a dominant influence on subjective sleep assessments.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00437-x.

Sleeping at the switch

Sleep slow waves are studied for their role in brain plasticity, homeostatic regulation, and their changes during aging. Here, we address the possibility that two types of slow waves co-exist in humans. Thirty young and 29 older adults underwent a night of polysomnographic recordings. Using the transition frequency, slow waves with a slow transition (slow switchers) and those with a fast transition (fast switchers) were discovered. Slow switchers had a high electroencephalography (EEG) connectivity along their depolarization transition while fast switchers had a lower connectivity dynamics and dissipated faster during the night. Aging was associated with lower temporal dissipation of sleep pressure in slow and fast switchers and lower EEG connectivity at the microscale of the oscillations, suggesting a decreased flexibility in the connectivity network of older individuals. Our findings show that two different types of slow waves with possible distinct underlying functions coexist in the slow wave spectrum.

Autonomic dysregulation and sleep homeostasis in insomnia

STUDY OBJECTIVES

Insomnia is common in older adults, and is associated with poor health, including cognitive impairment and cardio-metabolic disease. Although the mechanisms linking insomnia with these comorbidities remain unclear, age-related changes in sleep and autonomic nervous system (ANS) regulation might represent a shared mechanistic pathway. In this study, we assessed the relationship between ANS activity with indices of objective and subjective sleep quality in older adults with insomnia.

METHODS

Forty-three adults with chronic insomnia and 16 age-matched healthy sleeper controls were studied. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), objective sleep quality by electroencephalogram spectral components derived from polysomnography, and ANS activity by measuring 24-h plasma cortisol and norepinephrine (NE).

RESULTS

Sleep cycle analysis displayed lower slow oscillatory (SO: 0.5-1.25 Hz) activity in the first cycle in insomnia compared to controls. In insomnia, 24-h cortisol levels were higher and 24-h NE levels were lower than controls. In controls, but not in insomnia, there was a significant interaction between NE level during wake and SO activity levels across the sleep cycles, such that in controls but not in insomnia, NE level during wake was positively associated with the amount of SO activity in the first cycle. In insomnia, lower 24-h NE level and SO activity in the first sleep cycle were associated with poorer subjective sleep quality.

CONCLUSION

Dysregulation of autonomic activity may be an underlying mechanism that links objective and subjective measures of sleep quality in older adults with insomnia, and potentially contribute to adverse health outcomes.

Slow wave activity moderates the association between new learning and traumatic brain injury severity

STUDY OBJECTIVES

Sleep-wake complaints and difficulties in making new learning are among the most persistent and challenging long-term sequelea following moderate to severe traumatic brain injury (TBI). Yet, it is unclear whether, and to what extent, sleep characteristics during the chronic stage of TBI contribute to sleep-wake and cognitive complaints. We aimed to characterize sleep architecture in chronic moderate to severe TBI adults and assess whether non-rapid eye movement slow wave activity (SWA) is associated to next day performance in episodic memory tasks according to TBI severity.

METHODS

Forty-two moderate to severe TBI participants, 12-47 months post-injury, and 38 healthy controls were tested with one night of in-laboratory polysomnography, followed the next morning by questionnaires (sleep quality, fatigue, and sleepiness) and neuropsychological assessment. We used multiple regression analyses to assess the moderator effect of SWA power on TBI severity and next-day memory performance.

RESULTS

We found that TBI participants reported worse sleep quality and fatigue, and had worse cognitive performance than controls. No between group differences were found on macro- and micro-architecture of sleep. However, SWA significantly interacted with TBI severity to explain next-day memory performance: higher SWA was more strongly associated to better memory performance in more severe TBI compared to milder TBI.

CONCLUSIONS

This study provides evidence that the injured brain is able to produce macro- and micro-architecture of sleep comparable to what is seen in healthy controls. However, with increasing TBI severity, lower non-rapid eye movement SWA power is associated with reduced ability to learn and memorise new information the following day.

Effects of manipulating body temperature on sleep in postmenopausal women

STUDY OBJECTIVES

A decline in sleep quality, slow wave sleep (SWS) and slow wave activity (SWA) are common in older adults. Prior studies have shown that manipulating body temperature during sleep can increase SWS/SWA. The aim of this study was to determine the effects of manipulation of body temperatures during sleep, using a high heat capacity mattress, on SWS/SWA and heart rate in post-menopausal women.

METHODS

Twenty-four healthy postmenopausal women between 40 and 75 years of age (mean age 62.4 ± 8.2 years, mean BMI 25.4 ± 3.5 kg/m²) were randomized in a single-blind, counterbalanced, cross-over manner to sleep on either a high heat capacity mattress (HHCM) or a low heat capacity mattress (LHCM) a week apart. Sleep was recorded using polysomnography during an 8-h sleep opportunity. Core and peripheral temperature were recorded using an ingestible capsule and thermochron respectively.

RESULTS

In comparison to the LHCM, sleep on HHCM exhibited a selective increase in SWS (average increase in Stage N3 of 9.6 min (2.1%), p = 0.04) and in slow oscillatory (SO) activity (0.5-1 Hz) in the first NREM/REM cycle (p = 0.04). In addition, the HHCM induced a greater reduction in core body temperature (p = 0.002). The reduction in core body temperature (first 180 min after lights out) from LHCM to HHCM was associated (r = 0.5, p = 0.012) with the increase in SO activity (SO cycle 1 and 2/cycle 3 and 4). Average heart rate was 1.6 beats/minute lower across the night on the HHCM compared to the LHCM (p = 0.001).

CONCLUSIONS

The results of this study indicate that manipulation of body temperature during sleep may be a useful approach to enhance SWS sleep in postmenopausal women.

Sleep slow oscillations favour local cortical plasticity underlying the consolidation of reinforced procedural learning in human sleep

We investigated changes of slow-wave activity and sleep slow oscillations in the night following procedural learning boosted by reinforcement learning, and how these changes correlate with behavioural output. In the Task session, participants had to reach a visual target adapting cursor's movements to compensate an angular deviation introduced experimentally, while in the Control session no deviation was applied. The task was repeated at 13:00 hours, 17:00 hours and 23:00 hours before sleep, and at 08:00 hours after sleep. The deviation angle was set at 15° (13:00 hours and 17:00 hours) and increased to 45° (reinforcement) at 23:00 hours and 08:00 hours. Both for Task and Control nights, high-density electroencephalogram sleep recordings were carried out (23:30-19:30 hours). The Task night as compared with the Control night showed increases of: (a) slow-wave activity (absolute power) over the whole scalp; (b) slow-wave activity (relative power) in left centro-parietal areas; (c) sleep slow oscillations rate in sensorimotor and premotor areas; (d) amplitude of pre-down and up states in premotor regions, left sensorimotor and right parietal regions; (e) sigma crowning the up state in right parietal regions. After Task night, we found an improvement of task performance showing correlations with sleep slow oscillations rate in right premotor, sensorimotor and parietal regions. These findings suggest a key role of sleep slow oscillations in procedural memories consolidation. The diverse components of sleep slow oscillations selectively reflect the network activations related to the reinforced learning of a procedural visuomotor task. Indeed, areas specifically involved in the task stand out as those with a significant association between sleep slow oscillations rate and overnight improvement in task performance.

Local and Widespread Slow Waves in Stable NREM Sleep: Evidence for Distinct Regulation Mechanisms

Previous work showed that two types of slow waves are temporally dissociated during the transition to sleep: widespread, large and steep slow waves predominate early in the falling asleep period (type I), while smaller, more circumscribed slow waves become more prevalent later (type II). Here, we studied the possible occurrence of these two types of slow waves in stable non-REM (NREM) sleep and explored potential differences in their regulation. A heuristic approach based on slow wave synchronization efficiency was developed and applied to high-density electroencephalographic (EEG) recordings collected during consolidated NREM sleep to identify the potential type I and type II slow waves. Slow waves with characteristics compatible with those previously described for type I and type II were identified in stable NREM sleep. Importantly, these slow waves underwent opposite changes across the night, with only type II slow waves displaying a clear homeostatic regulation. In addition, we showed that the occurrence of type I slow waves was often followed by larger type II slow waves, whereas the occurrence of type II slow waves was usually followed by smaller type I waves. Finally, type II slow waves were associated with a relative increase in spindle activity, while type I slow waves triggered periods of high-frequency activity. Our results provide evidence for the existence of two distinct slow wave synchronization processes that underlie two different types of slow waves. These slow waves may have different functional roles and mark partially distinct “micro-states” of the sleeping brain.

Transdermal Nicotine Patch Effects on EEG Power Spectra and Heart Rate Variability During Sleep of Healthy Male Adults

OBJECTIVE

The effect of transdermal nicotine patch on sleep physiology is not well established. The current study aimed to examine the influence of nicotine patch on homeostatic sleep propensity and autonomic nervous system.

METHODS

We studied 16 non-smoking young healthy volunteers with nocturnal polysomnography in a double blind crossover design between sleep with and without nicotine patch. We compared the sleep variables, sleep EEG power spectra, and heart rate variability.

RESULTS

The night with nicotine patch showed significant increase in sleep latency, wake after sleep onset, and stage 1 sleep; and decrease in total sleep time, sleep efficiency, and percentage of REM sleep. Also, spectral analysis of the sleep EEG in the night with nicotine patch revealed decreased slow wave activity in stage 2 and REM sleep and increased alpha activity in the first NREM-REM sleep cycle. Heart rate variability showed no differences between the 2 nights, but the low to high ratio (a parameter indicative of sympathetic nervous system activity) positively correlated with wake after sleep onset in night with nicotine patch.

CONCLUSION

Transdermal nicotine patch significantly disrupts sleep continuity, sleep architecture, and homeostatic sleep propensity. The overactivation of the sympathetic nervous system may be responsible for these changes.

Sleep loss and recovery after administration of drugs related to different arousal systems in rats

Sleep is homeostatically regulated suggesting a restorative function. Sleep deprivation is compensated by an increase in length and intensity of sleep. In this study, suppression of sleep was induced pharmacologically by drugs related to different arousal systems. All drugs caused non-rapid eye movement (NREM) sleep loss followed by different compensatory processes. Apomorphine caused a strong suppression of sleep followed by an intense recovery. In the case of fluoxetine and eserine, recovery of NREM sleep was completed by the end of the light phase due to the biphasic pattern demonstrated for these drugs first in the present experiments. Yohimbine caused a long-lasting suppression of NREM sleep, indicating that either the noradrenergic system has the utmost strength among the examined systems, or that restorative functions occurring normally during NREM sleep were not blocked. Arousal systems are involved in the regulation of various wakefulness-related functions, such as locomotion and food intake. Therefore, it can be hypothesized that activation of the different systems results in qualitatively different waking states which might affect subsequent sleep differently. These differences might give some insight into the homeostatic function of sleep in which the dopaminergic and noradrenergic systems may play a more important role than previously suggested.

Prediction Accuracy in Multivariate Repeated-Measures Bayesian Forecasting Models with Examples Drawn from Research on Sleep and Circadian Rhythms

In study designs with repeated measures for multiple subjects, population models capturing within- and between-subjects variances enable efficient individualized prediction of outcome measures (response variables) by incorporating individuals response data through Bayesian forecasting. When measurement constraints preclude reasonable levels of prediction accuracy, additional (secondary) response variables measured alongside the primary response may help to increase prediction accuracy. We investigate this for the case of substantial between-subjects correlation between primary and secondary response variables, assuming negligible within-subjects correlation. We show how to determine the accuracy of primary response predictions as a function of secondary response observations. Given measurement costs for primary and secondary variables, we determine the number of observations that produces, with minimal cost, a fixed average prediction accuracy for a model of subject means. We illustrate this with estimation of subject-specific sleep parameters using polysomnography and wrist actigraphy. We also consider prediction accuracy in an example time-dependent, linear model and derive equations for the optimal timing of measurements to achieve, on average, the best prediction accuracy. Finally, we examine an example involving a circadian rhythm model and show numerically that secondary variables can improve individualized predictions in this time-dependent nonlinear model as well.

Sleep, recovery, and metaregulation: explaining the benefits of sleep

A commonly held view is that extended wakefulness is causal for a broad spectrum of deleterious effects at molecular, cellular, network, physiological, psychological, and behavioral levels. Consequently, it is often presumed that sleep plays an active role in providing renormalization of the changes incurred during preceding waking. Not surprisingly, unequivocal empirical evidence supporting such a simple bi-directional interaction between waking and sleep is often limited or controversial. One difficulty is that, invariably, a constellation of many intricately interrelated factors, including the time of day, specific activities or behaviors during preceding waking, metabolic status and stress are present at the time of measurement, shaping the overall effect observed. In addition to this, although insufficient or disrupted sleep is thought to prevent efficient recovery of specific physiological variables, it is also often difficult to attribute specific changes to the lack of sleep proper. Furthermore, sleep is a complex phenomenon characterized by a multitude of processes, whose unique and distinct contributions to the purported functions of sleep are difficult to determine, because they are interrelated. Intensive research effort over the last decades has greatly progressed current understanding of the cellular and physiological processes underlying the regulation of vigilance states. Notably, it also highlighted the infinite complexity within both waking and sleep, and revealed a number of fundamental conceptual and technical obstacles that need to be overcome in order to fully understand these processes. A promising approach could be to view sleep not as an entity, which has specific function(s) and is subject to direct regulation, but as a manifestation of the process of metaregulation, which enables efficient moment-to-moment integration between internal and external factors, preceding history and current homeostatic needs.

About sleep's role in memory

Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

Characteristic changes in the slow cortical waves after a 6-h sleep deprivation in rat

Sleep deprivation is followed by an increase in EEG delta power during recovery sleep indicating an increased sleep propensity. Delta waves mostly reflect the rhythmic recurring of generalized hyperpolarizations (DOWN state) in cortical neurons causing large, deep-positive waves in the LFP. Enhancement of delta power in recovery sleep can be the consequence of either the more frequent occurrence, or the higher amplitude caused by higher synchrony, or the longer duration of these DOWN states. In the present experiments, we examined these possibilities and found the strongest increase in the incidence of slow deep positive LFP waves (slow waves) following sleep deprivation indicating enhancement of DOWN state inducing and/or weakening of UP state maintaining processes. The strong decrease in multiunit activity during slow waves was preceded by a gradual buildup of activity. The significant correlation between these changes both in control and recovery recordings indicate that excitation might determine the subsequent drop in activity. Increased sensitivity of cortical neurons to excitation might offer an explanation for this observation. Current-source-density analysis indicated in our experiments that the first sources during DOWN states appeared in layer III-IV. Activation was then displaced to layer V. In the motor cortex, both corticocortical and thalamocortical fibers terminate in layer III that provides a strong feedforward excitation to layer V. As propagation of facilitatory signals through cortical layers is downwardly biased, disfacilitation might also follow this pattern. Sleep deprivation caused only quantitative differences in the sink-source patterns, indicating that existing processes were enhanced by sleep deprivation.

The multiple time scales of sleep dynamics as a challenge for modelling the sleeping brain

A particular property of the sleeping brain is that it exhibits dynamics on very different time scales ranging from the typical sleep oscillations such as sleep spindles and slow waves that can be observed in electroencephalogram (EEG) segments of several seconds duration over the transitions between the different sleep stages on a time scale of minutes to the dynamical processes involved in sleep regulation with typical time constants in the range of hours. There is an increasing body of work on mathematical and computational models addressing these different dynamics, however, usually considering only processes on a single time scale. In this paper, we review and present a new analysis of the dynamics of human sleep EEG at the different time scales and relate the findings to recent modelling efforts pointing out both the achievements and remaining challenges.

Effects of anesthesia on the response to sleep deprivation

STUDY OBJECTIVE

Slow wave activity (SWA) during NREM sleep is the best characterized marker of sleep homeostasis, and the occurrence of sleep slow waves is necessary to reduce sleep need. Recent evidence suggests that sleep slow waves may mediate several beneficial effects of sleep on performance, from the prevention of cognitive impairments to memory consolidation. However, slow waves are also triggered by low doses of many anesthetics, but very few reports have examined whether anesthesia-mediated slow waves affect the homeostatic regulation of sleep. Moreover, no study has examined how sleep is affected by higher doses of anesthetics, which lead to a predominantly "isoelectric" EEG tracing without slow waves.

DESIGN

We studied in rats whether 1 hour of a dose of isoflurane or desflurane able to induce almost continuous slow waves (ISO-sw, DES-sw), and of a dose of desflurane resulting in a predominantly isoelectric EEG (DES-iso) reduces the sleep pressure caused by 4 h of sleep deprivation. Anesthesia was compared to a mock condition in which rats were only anesthetized for 2-3 min.

SETTING

Basic sleep research laboratory.

PATIENTS OR PARTICIPANTS

Male WKY rats (n=31).

INTERVENTIONS

Total sleep deprivation by exposure to novel objects starting at light onset, followed by one hour of anesthesia or mock anesthesia.

MEASUREMENTS AND RESULTS

One hour of anesthesia (sw or iso) did not affect either sleep duration or the overall sleep pattern. Anesthesia with ISO-sw or DES-sw, both associated with the occurrence of almost continuous slow waves, reduced the SWA rebound expected following 4 h of sleep deprivation. One hour of anesthesia with DES-iso, associated with isoelectric EEG and few slow waves, also reduced the SWA rebound after sleep deprivation, and did so to an extent similar to that observed after DES-sw. However, in contrast to DES-sw, SWA after DES-iso remained chronically lower than in baseline, resulting in reduced slow wave energy (SWE, SWA × time) for at least 2 days.

CONCLUSION

The blunted SWA rebound after ISO-sw and DES-sw suggests that anesthesia slow waves may substitute for sleep slow waves. The reduced SWA rebound after DES-iso may reflect a pathological condition that results in a chronic decrease in SWA, or may suggest that anesthesia slow waves are not an absolute requirement to discharge sleep pressure.

Electrophysiological correlates of sleep homeostasis in freely behaving rats

The electrical activity of the brain does not only reflect the current level of arousal, ongoing behavior, or involvement in a specific task but is also influenced by what kind of activity, and how much sleep and waking occurred before. The best marker of sleep-wake history is the electroencephalogram (EEG) spectral power in slow frequencies (slow-wave activity, 0.5-4 Hz, SWA) during sleep, which is high after extended wakefulness and low after consolidated sleep. While sleep homeostasis has been well characterized in various species and experimental paradigms, the specific mechanisms underlying homeostatic changes in brain activity or their functional significance remain poorly understood. However, several recent studies in humans, rats, and computer simulations shed light on the cortical mechanisms underlying sleep regulation. First, it was found that the homeostatic changes in SWA can be fully accounted for by the variations in amplitude and slope of EEG slow waves, which are in turn determined by the efficacy of corticocortical connectivity. Specifically, the slopes of sleep slow waves were steeper in early sleep compared to late sleep. Second, the slope of cortical evoked potentials, which is an established marker of synaptic strength, was steeper after waking, and decreased after sleep. Further, cortical long-term potentiation (LTP) was partially occluded if it was induced after a period of waking, but it could again be fully expressed after sleep. Finally, multiunit activity recordings during sleep revealed that cortical neurons fired more synchronously after waking, and less so after a period of consolidated sleep. The decline of all these electrophysiological measures-the slopes of slow waves and evoked potentials and neuronal synchrony-during sleep correlated with the decline of the traditional marker of sleep homeostasis, EEG SWA. Taken together, these data suggest that homeostatic changes in sleep EEG are the result of altered neuronal firing and synchrony, which in turn arise from changes in functional neuronal connectivity.

Mutual information analysis of EEG signals indicates age-related changes in cortical interdependence during sleep in middle-aged versus elderly women

Elderly subjects exhibit declining sleep efficiency parameters with longer time spent awake at night and greater sleep fragmentation. In this article, we report on the changes in cortical interdependence during sleep stages between 15 middle-aged (range: 42-50 years) and 15 elderly (range: 71-86 years) women subjects. Cortical interdependence assessed from EEG signals typically exhibits increasing levels of correlation because human subjects progress from wake to deeper stages of sleep. EEG signals acquired from previously existing polysomnogram datasets were subjected to mutual information analysis to detect changes in information transmission associated with change in sleep stage and to understand how age affects the interdependence values. We observed a significant reduction in the interdependence between central EEG signals of elderly subjects in nonrapid eye movement and rapid eye movement stage sleep in comparison with middle-aged subjects (age group effect: elderly versus middle aged P < 0.001, sleep stage effect: P < 0.001, interaction effect between age group and sleep stage: P = 0.007). A narrowband analysis revealed that the reduction in mutual information was present in delta, theta, and sigma frequencies. These findings suggest that the lowered cortical interdependence in sleep of elderly subjects may indicate independently evolving dynamic neural activities at multiple cortical sites. The loss of synchronization between neural activities during sleep in the elderly may make these women more susceptible to localized disturbances that could lead to frequent arousals.

Topography of homeostatic sleep pressure dissipation across the night in young and middle-aged men and women

Decline in slow-wave activity (SWA) across the night is believed to reflect dissipation of the homeostatic sleep drive. This study evaluated the effects of age, sex and topography on SWA dissipation. The sleep electroencephalogram of 48 young [22 women, 26 men; mean = 23.3 years; standard deviation (SD) = 2.4] and 39 middle-aged (21 women, 18 men; mean = 51.9 years; SD = 4.6) healthy volunteers was analysed. Spectral analysis (0.5-22.0 Hz) was performed per non-rapid eye movement period for Fp1, F3, C3, P3 and O1. SWA (1.0-5.0 Hz) dissipation was modelled using linear and exponential decay functions applied to each age and sex subgroup data set for each derivation. The relative adequacy of both functions was compared using Akaike's information criterion. Results suggest that the exponential model provides a better data fit than the linear fit independently of age, gender and brain location. In women, age reduced the span (distance between the y intercept and the asymptote) of SWA decay in Fp1, F3, P3 and O1. In men, however, the effect of age on the span of SWA decay was limited to Fp1 and F3. In all age and sex subgroups, anterior regions showed a higher span than posterior regions. The asymptote was lower in anterior regions in young but not in middle-aged subjects. These results suggest that the homeostatic process operates on a larger scale in anterior regions. Importantly, ageing reduced the scale of homeostatic dissipation in both sexes, but this effect was more widespread across the brain in women.

The effects of sleep deprivation in humans: topographical electroencephalogram changes in non-rapid eye movement (NREM) sleep versus REM sleep

Studies on homeostatic aspects of sleep regulation have been focussed upon non-rapid eye movement (NREM) sleep, and direct comparisons with regional changes in rapid eye movement (REM) sleep are sparse. To this end, evaluation of electroencephalogram (EEG) changes in recovery sleep after extended waking is the classical approach for increasing homeostatic need. Here, we studied a large sample of 40 healthy subjects, considering a full-scalp EEG topography during baseline (BSL) and recovery sleep following 40 h of wakefulness (REC). In NREM sleep, the statistical maps of REC versus BSL differences revealed significant fronto-central increases of power from 0.5 to 11 Hz and decreases from 13 to 15 Hz. In REM sleep, REC versus BSL differences pointed to significant fronto-central increases in the 0.5-7 Hz and decreases in the 8-11 Hz bands. Moreover, the 12-15 Hz band showed a fronto-parietal increase and that at 22-24 Hz exhibited a fronto-central decrease. Hence, the 1-7 Hz range showed significant increases in both NREM sleep and REM sleep, with similar topography. The parallel change of NREM sleep and REM sleep EEG power is related, as confirmed by a correlational analysis, indicating that the increase in frequency of 2-7 Hz possibly subtends a state-aspecific homeostatic response. On the contrary, sleep deprivation has opposite effects on alpha and sigma activity in both states. In particular, this analysis points to the presence of state-specific homeostatic mechanisms for NREM sleep, limited to <2 Hz frequencies. In conclusion, REM sleep and NREM sleep seem to share some homeostatic mechanisms in response to sleep deprivation, as indicated mainly by the similar direction and topography of changes in low-frequency activity.

Impact of alcoholism on sleep architecture and EEG power spectra in men and women

STUDY OBJECTIVES

To determine the impact of alcoholism on sleep architecture and sleep EEG power spectra in men and women with uncomplicated alcoholism.

DESIGN AND PARTICIPANTS

42 alcoholics (27 men) and 42 controls (19 men) screened for medical, psychiatric, and sleep problems participated in a full night of polysomnography following an adaptation night. Data were collected from multiple scalp sites and subjected to power spectral analysis. Sleep architecture and EEG spectral power measures were evaluated for the effects of diagnosis and sex using age as a covariate.

RESULTS

Compared with controls, alcoholics had less slow wave sleep and increased proportions of stage 1 and REM sleep. Spectral analysis of NREM sleep showed reduced levels of slow wave activity (SWA, 0.3-4 Hz) and slow theta (theta) power (4-6 Hz) in alcoholics. The differences in SWA extended across the slow band (0.3-1 Hz) and all delta (delta) frequencies and were most prominent over frontal scalp regions. No group differences were seen in the power spectra of REM sleep. Women had more SWA and theta power than men, but there were no sex by diagnosis interactions for any measures, suggesting that alcoholism does not differentially influence men and women.

CONCLUSION

Long-term alcoholism affects sleep even after long periods of abstinence in both men and women. Measures of frontal slow wave activity were particularly sensitive markers of this long-lasting effect. Sleep EEG measures would thus seem to provide a functional correlate of the changes in brain structure seen in frontal cortex of long-term alcoholics.

Sleep homeostasis and cortical synchronization: II. A local field potential study of sleep slow waves in the rat

STUDY OBJECTIVE

Sleep slow-wave activity (SWA, EEG power between 0.5 and 4.0 Hz) decreases homeostatically in the course of non-rapid eye movement sleep (NREM) sleep. According to a recent hypothesis, the homeostatic decrease of sleep SWA is due to a progressive decrease in the strength of corticocortical connections. This hypothesis was evaluated in a large-scale thalamocortical model, which showed that a decrease in synaptic strength, implemented through a reduction of postsynaptic currents, resulted in lower sleep SWA in simulated local field potentials (LFP). The decrease in SWA was associated with a decreased proportion of high-amplitude slow waves, a decreased slope of the slow waves, and an increase in the number of multipeak waves. Here we tested the model predictions by obtaining LFP recordings from the rat cerebral cortex and comparing conditions of high homeostatic sleep pressure (early sleep) and low homeostatic sleep pressure (late sleep).

DESIGN

Intracortical LFP recordings during baseline sleep and after 6 hours of sleep deprivation.

SETTING

Basic sleep research laboratory.

PATIENTS OR PARTICIPANTS

WKY adult male rats.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

Early sleep (sleep at the beginning of the major sleep phase, sleep immediately after sleep deprivation) was associated with (1) high SWA, (2) many large slow waves, (3) steep slope of slow waves, and (4) rare occurrence of multipeak waves. By contrast, late sleep (sleep at the end of the major sleep phase, sleep several hours after the end of sleep deprivation) was associated with (1) low SWA, (2) few high-amplitude slow waves, (3) reduced slope of slow waves, and (4) more frequent multipeak waves.

CONCLUSION

In rats, changes in sleep SWA are associated with changes in the amplitude and slope of slow waves, and in the number of multi-peak waves. Such changes in slow-wave parameters are compatible with the hypothesis that average synaptic strength decreases in the course of sleep.

Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain signals

Background

It has been acknowledged that the frequency spectrum of measured electromagnetic (EM) brain signals shows a decrease in power with increasing frequency. This spectral behaviour may lead to difficulty in distinguishing event-related peaks from ongoing brain activity in the electro- and magnetoencephalographic (EEG and MEG) signal spectra. This can become an issue especially in the analysis of low frequency oscillations (LFOs) – below 0.5 Hz – which are currently being observed in signal recordings linked with specific pathologies such as epileptic seizures or attention deficit hyperactivity disorder (ADHD), in sleep studies, etc.

Methods

In this work we propose a simple method that can be used to compensate for this 1/f trend hence achieving spectral normalisation. This method involves filtering the raw measured EM signal through a differentiator prior to further data analysis.

Results

Applying the proposed method to various exemplary datasets including very low frequency EEG recordings, epileptic seizure recordings, MEG data and Evoked Response data showed that this compensating procedure provides a flat spectral base onto which event related peaks can be clearly observed.

Conclusion

Findings suggest that the proposed filter is a useful tool for the analysis of physiological data especially in revealing very low frequency peaks which may otherwise be obscured by the 1/f spectral activity inherent in EEG/MEG recordings.

Sleep homeostasis in the rat in the light and dark period

Sleep is regulated by the interaction of a homeostatic (Process S) and a circadian component. The duration of prior wakefulness is the main factor influencing subsequent sleep duration and its intensity. We investigated in the rat whether the sleep-wake history before sleep deprivation (SD) contributes to the effects of sleep loss incurred during the SD. A 24-h baseline recording was followed by 6 h SD at light onset (SD-Light, n=7), or at dark onset (SD-Dark, n=8) and 18 h recovery. Both SDs led to a pronounced increase in slow wave activity (SWA, EEG power between 0.75 and 4.0 Hz) in NREM sleep and increased sleep consolidation. The prolongation of sleep episodes was associated with increased intra-episode SWA. The amount of waking before the SD correlated positively with the SWA increase during recovery, and SWA levels before SD were negatively correlated with their subsequent increase. The time-course of SWA (Process S) as well as of single frequency bins within the SWA band was successfully simulated based on vigilance-state distribution. The time constant of the exponential monotonic decay (Td) was higher for the 0.75-1.0 Hz bin compared to all remaining frequency bins of the SWA band, reflecting a slower process determining the slow EEG component during sleep. The data show that the homeostatic response after SD, consisting of increased sleep intensity and sleep consolidation is determined by a combination of SD and the preceding vigilance-state history. The slower dynamics of low frequency delta power compared to fast delta frequencies point to heterogeneity within the traditionally defined SWA band.

Kinetics of NREM delta EEG power density across NREM periods depend on age and on delta-band designation

STUDY OBJECTIVES

(1) To determine whether children and elderly exhibit the atypical kinetics of very low frequency (VLF) power found in young adults, (2) to test the hypothesis that variations in "delta" bandwidth designations can explain discrepancies in whether normalized delta power density declines across non-rapid eye movement periods (NREMPs) linearly or shows the curvature expected of exponential change, and (3) to test our hypothesis that the decline in normailized delta power density in children across NREMPs would have a slope similar to that which we had previously found in young adults and elderly.

METHODS

In 3 age groups (mean ages 11, 22, and 71 years) NREM electroencephalograms were analyzed with fast Fourier transform for frequencies between 0.3 and 4 Hz in bands. Across-NREMP trends of normalized power density for various "delta" bands were analyzed by analyses of variance for linearity, curvature, and age interactions.

RESULTS

We replicated the atypical kinetics of VLF power (-0.3-0.9 Hz) in young adults reported by others and showed that this pattern exists in children and normal elderly. As frequencies increased above 0.7 Hz, power showed first a linear and then a concave-upward curvilinear decline across NREMPs in children and young adults; the decline across NREMPS in the elderly became linear but never developed curvilinearity. For all designations of delta, the across-NREMP decline in children was significantly steeper than in young adults.

CONCLUSIONS

The findings that all normalized "delta" electroencephalogram bands in children showed a curvilinear decline across NREMPs that was steeper than that in young adults confirms observations of others and refutes our hypothesis that the decline would be linear with the same slope we found in young adults and elderly. Whether the decline in normalized power in young adults appears linear or curvilinear depends on whether the convex trend of VLF power is included.

The adolescent decline of NREM delta, an indicator of brain maturation, is linked to age and sex but not to pubertal stage

Two dramatic phenomena of human adolescence are sexual maturation and a steep decline in the delta EEG of non-rapid eye movement (NREM) sleep. It has long been speculated that these developmental changes are causally related. Here, we present the first longitudinal data on this issue. Cohorts of 9- and 12-year-old children (n = 31, 38) were studied with in-home sleep EEG recordings at 6-mo intervals over 2 years. Pubertal (Tanner) stage, height, and weight were obtained at each time point. NREM delta power density (DPD) did not change significantly over ages 9-11 years, and its level did not differ in boys and girls. DPD declined by 25% between ages 12 and 14 years. This decline was parallel in the two sexes, but levels were lower in girls, suggesting that their DPD decline began earlier. Mixed effect analyses demonstrated that DPD was strongly related to age with Tanner stage, height, weight and body mass index controlled but that none of these measures of physical and sexual development was related to DPD with age controlled. NREM delta is the sleep EEG component homeostatically related to prior waking duration and the intensity of waking brain activity. We hypothesize that the DPD decline is caused by age-programmed synaptic pruning that decreases waking brain metabolic rate. This reduced rate would decrease the "substrate" for delta homeostasis. Whether or not this interpretation proves correct, these longitudinal data demonstrate that the delta decline in adolescence reflects brain processes that are not predicted by physical growth or sexual maturation.