A postsleep decline in auditory evoked potential amplitude reflects sleep homeostasis

Timing and cortical region matter: theta power differences between teenagers affected by Major Depression and healthy controls

In adults affected by Major Depressive Disorder (MDD), most findings point to higher electroencephalographic (EEG) theta power during wake compared to healthy controls (HC) as a potential biomarker aiding the diagnostic process or subgrouping for stratified treatment. Besides these group differences, theta power is modulated by time of day, sleep/wake history, and age. Thus, we aimed at assessing if the time of recording alters theta power in teenagers affected by MDD or HC. Standardized wake EEG power was assessed with high-density EEG in 15 children and adolescents with MDD and in 15 age- and sex-matched HC in the evening and morning. Using a two-way ANOVA, group, time, and their interaction were tested. In patients, the current severity of depression was rated using the Children's Depression Rating Scale. Broadband EEG power was lower in the morning after sleep, with a significant interaction (group x time) in central regions in the 4-6 Hz range. In MDD relative to HC, theta power was decreased over occipital areas in the evening and increased over frontal areas in the morning. A higher frontal theta power was correlated with more severe depressive mood in the morning but not in the evening. This was a cross-sectional study design, including patients on antidepressant medication. In conclusion, depending on time of recording, region-specific opposite differences of theta power were found between teenagers with MDD and HC. These findings stress the importance of the time of the recording when investigating theta power's relationship to psychopathology.

Changes in electroencephalographic microstates between evening and morning are associated with overnight sleep slow waves in healthy individuals

STUDY OBJECTIVES

Microstates are semi-stable voltage topographies that account for most of electroencephalogram (EEG) variance. However, the impact of time of the day and sleep on microstates has not been examined. To address this gap, we assessed whether microstates differed between the evening and morning and whether sleep slow waves correlated with microstate changes in healthy participants.

METHODS

Forty-five healthy participants were recruited. Each participant underwent 6 minutes of resting state EEG recordings in the evening and morning, interleaved by sleep EEGs. Evening-to-morning changes in microstate duration, coverage, and occurrence were assessed. Furthermore, correlation between microstate changes and sleep slow-wave activity (SWA) and slow-wave density (SWD) were performed.

RESULTS

Two-way ANOVAs with microstate class (A, B, C, and D) and time (evening and morning) revealed significant microstate class × time interaction for duration (F(44) = 5.571, p = 0.002), coverage (F(44) = 6.833, p = 0.001), and occurrence (F(44) = 5.715, p = 0.002). Post hoc comparisons showed significant effects for microstate C duration (padj = 0.048, Cohen's d = -0.389), coverage (padj = 0.002, Cohen's d = -0.580), and occurrence (padj = 0.002, Cohen's d = -0.606). Topographic analyses revealed inverse correlations between SWD, but not SWA, and evening-to-morning changes in microstate C duration (r = -0.51, padj = 0.002), coverage (r = -0.45, padj = 0.006), and occurrence (r = -0.38, padj = 0.033).

CONCLUSIONS

Microstate characteristics showed significant evening-to-morning changes associated with, and possibly regulated by, sleep slow waves. These findings suggest that future microstate studies should control for time of day and sleep effects.

Utility of the Compensatory Tracking Task for Objective Differentiation of Hypersomnolence in Depression: A High-Density EEG Investigation

Hypersomnolence is a common and debilitating symptom in mood disorders. However, objective differentiation of excessive daytime sleepiness (EDS) from non-EDS in depression has not yet been achieved. This study compared performance on the Compensatory Tracking Task (CTT) and concurrently-recorded high-density (hd)EEG theta power in 22 patients with major depressive disorder (MDD) and co-occurring EDS against 22 age- and sex-matched patients with MDD but no EDS, as well as 22 age- and sex-matched healthy controls. Though depressed hypersomnolent participants endorsed feeling sleepier than depressed non-hypersomnolent and healthy control participants prior to starting the CTT, no group differences in CTT performance were observed. Average hdEEG theta power was higher during periods of high error on the CTT compared to periods of low error, but did not differ between the groups. Though the CTT still holds promise as an objective neurobehavioral measure, these results do not indicate a capability to differentiate EDS from non-EDS in mood disorders.

Local sleep-like events during wakefulness and their relationship to decreased alertness in astronauts on ISS

Adequate sleep quantity and quality is required to maintain vigilance, cognitive and learning processes. A decrease of sleep quantity preflight and on the International Space Station (ISS) has been reported. Recent counter-measures have been implemented to better regulate sleep opportunities on ISS. In our study, astronauts were allocated enough time for sleep the night before the recordings. However, for proper sleep recovery, the quality of sleep is also critical. Unfortunately, data on sleep quality have yet to be acquired from the ISS. Here, we investigate sleep pressure markers during wakefulness in five astronauts throughout their 6-month space mission by the mean of electroencephalographic recordings. We show a global increase of theta oscillations (5–7 Hz) on the ISS compared to on Earth before the mission. We also show that local sleep-like events, another marker of sleep pressure, are more global in space (p < 0.001). By analysing the performances of the astronauts during a docking simulation, we found that local sleep-like events are more global when reaction times are slower (R² = 0.03, p = 0.006) and there is an increase of reaction times above 244 ms after 2 months in space (p = 0.012). Our analyses provide first evidence for increased sleep pressure in space and raise awareness on possible impacts on visuomotor performances in space.

Metabolite Clearance During Wakefulness and Sleep

Mechanisms for elimination of metabolites from ISF include metabolism, blood-brain barrier transport and non-selective, perivascular efflux, this last being assessed by measuring the clearance of markers like inulin. Clearance describes elimination. Clearance of a metabolite generated within the brain is determined as its elimination rate divided by its concentration in interstitial fluid (ISF). However, the more frequently measured parameter is the rate constant for elimination determined as elimination rate divided by amount present, which thus depends on both the elimination processes and the distribution of the metabolite in the brain. The relative importance of the various elimination mechanisms depends on the particular metabolite. Little is known about the effects of sleep on clearance via metabolism or blood-brain barrier transport, but studies with inulin in mice comparing perivascular effluxes during sleep and wakefulness reveal a 4.2-fold increase in clearance. Amongst the important brain metabolites considered, CO₂ is eliminated so rapidly across the blood-brain barrier that clearance is blood flow limited and elimination quickly balances production. Glutamate is removed from ISF primarily by uptake into astrocytes and conversion to glutamine, but also by transport across the blood-brain barrier. Both lactate and amyloid-β are eliminated by metabolism, blood-brain barrier transport and perivascular efflux and both show decreased production, decreased ISF concentration and increased perivascular clearance during sleep. Taken altogether available data indicate that sleep increases perivascular and non-perivascular clearances for amyloid-β which reduces its concentration and may have long-term consequences for the formation of plaques and cerebral arterial deposits.

High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep

Auditory rhythmic sensory stimulation modulates brain oscillations by increasing phase-locking to the temporal structure of the stimuli and by increasing the power of specific frequency bands, resulting in Auditory Steady State Responses (ASSR). The ASSR is altered in different diseases of the central nervous system such as schizophrenia. However, in order to use the ASSR as biological markers for disease states, it needs to be understood how different vigilance states and underlying brain activity affect the ASSR. Here, we compared the effects of auditory rhythmic stimuli on EEG brain activity during wake and NREM sleep, investigated the influence of the presence of dominant sleep rhythms on the ASSR, and delineated the topographical distribution of these modulations. Participants (14 healthy males, 20-33 years) completed on the same day a 60 min nap session and two 30 min wakefulness sessions (before and after the nap). During these sessions, amplitude modulated (AM) white noise auditory stimuli at different frequencies were applied. High-density EEG was continuously recorded and time-frequency analyses were performed to assess ASSR during wakefulness and NREM periods. Our analysis revealed that depending on the electrode location, stimulation frequency applied and window/frequencies analysed the ASSR was significantly modulated by sleep pressure (before and after sleep), vigilance state (wake vs. NREM sleep), and the presence of slow wave activity and sleep spindles. Furthermore, AM stimuli increased spindle activity during NREM sleep but not during wakefulness. Thus, (1) electrode location, sleep history, vigilance state and ongoing brain activity needs to be carefully considered when investigating ASSR and (2) auditory rhythmic stimuli during sleep might represent a powerful tool to boost sleep spindles.

Theta waves in children's waking electroencephalogram resemble local aspects of sleep during wakefulness

Vyazovskiy and colleagues found in rats’ multi-unit recordings brief periods of silence (off-states) in local populations of cortical neurons during wakefulness which closely resembled the characteristic off-states during sleep. These off-states became more global and frequent with increasing sleep pressure and were associated with the well-known increase of theta activity under sleep deprivation in the surface EEG. Moreover, the occurrence of such off-states was related to impaired performance. While these animal experiments were based on intracranial recordings, we aimed to explore whether the human surface EEG may also provide evidence for such a local sleep-like intrusion during wakefulness. Thus, we analysed high-density wake EEG recordings during an auditory attention task in the morning and evening in 12 children. We found that, theta waves became more widespread in the evening and the occurrence of widespread theta waves was associated with slower reaction times in the attention task. These results indicate that widespread theta events measured on the scalp might be markers of local sleep in humans. Moreover, such markers of local sleep, seem to be related to the well described performance decline under high sleep pressure.

Large Scale Cortical Functional Networks Associated with Slow-Wave and Spindle-Burst-Related Spontaneous Activity

Cortical sensory systems are active with rich patterns of activity during sleep and under light anesthesia. Remarkably, this activity shares many characteristics with those present when the awake brain responds to sensory stimuli. We review two specific forms of such activity: slow-wave activity (SWA) in the adult brain and spindle bursts in developing brain. SWA is composed of 0.5-4 Hz resting potential fluctuations. Although these fluctuations synchronize wide regions of cortex, recent large-scale imaging has shown spatial details of their distribution that reflect underlying cortical structural projections and networks. These networks are regulated, as prior awake experiences alter both the spatial and temporal features of SWA in subsequent sleep. Activity patterns of the immature brain, however, are very different from those of the adult. SWA is absent, and the dominant pattern is spindle bursts, intermittent high frequency oscillations superimposed on slower depolarizations within sensory cortices. These bursts are driven by intrinsic brain activity, which act to generate peripheral inputs, for example via limb twitches. They are present within developing sensory cortex before they are mature enough to exhibit directed movements and respond to external stimuli. Like in the adult, these patterns resemble those evoked by sensory stimulation when awake. It is suggested that spindle-burst activity is generated purposefully by the developing nervous system as a proxy for true external stimuli. While the sleep-related functions of both slow-wave and spindle-burst activity may not be entirely clear, they reflect robust regulated phenomena which can engage select wide-spread cortical circuits. These circuits are similar to those activated during sensory processing and volitional events. We highlight these two patterns of brain activity because both are prominent and well-studied forms of spontaneous activity that will yield valuable insights into brain function in the coming years.

Synaptic plasticity model of therapeutic sleep deprivation in major depression

Therapeutic sleep deprivation (SD) is a rapid acting treatment for major depressive disorder (MDD). Within hours, SD leads to a dramatic decrease in depressive symptoms in 50-60% of patients with MDD. Scientifically, therapeutic SD presents a unique paradigm to study the neurobiology of MDD. Yet, up to now, the neurobiological basis of the antidepressant effect, which is most likely different from today's first-line treatments, is not sufficiently understood. This article puts the idea forward that sleep/wake-dependent shifts in synaptic plasticity, i.e., the neural basis of adaptive network function and behavior, represent a critical mechanism of therapeutic SD in MDD. Particularly, this article centers on two major hypotheses of MDD and sleep, the synaptic plasticity hypothesis of MDD and the synaptic homeostasis hypothesis of sleep-wake regulation, and on how they can be integrated into a novel synaptic plasticity model of therapeutic SD in MDD. As a major component, the model proposes that therapeutic SD, by homeostatically enhancing cortical synaptic strength, shifts the initially deficient inducibility of associative synaptic long-term potentiation (LTP) in patients with MDD in a more favorable window of associative plasticity. Research on the molecular effects of SD in animals and humans, including observations in the neurotrophic, adenosinergic, monoaminergic, and glutamatergic system, provides some support for the hypothesis of associative synaptic plasticity facilitation after therapeutic SD in MDD. The model proposes a novel framework for a mechanism of action of therapeutic SD that can be further tested in humans based on non-invasive indices and in animals based on direct studies of synaptic plasticity. Further determining the mechanisms of action of SD might contribute to the development of novel fast acting treatments for MDD, one of the major health problems worldwide.

Topographic deficits in alpha-range resting EEG activity and steady state visual evoked responses in schizophrenia

Deficits in both resting alpha-range (8-12Hz) electroencephalogram (EEG) activity and steady state evoked potential (SSVEP) responses have been reported in schizophrenia. However, the topographic specificity of these effects, the relationship between resting EEG and SSVEP, as well as the impact of antipsychotic medication on these effects, have not been clearly delineated. The present study sought to address these questions with 256 channel high-density EEG recordings in a group of 13 schizophrenia patients, 13 healthy controls, and 10 non-schizophrenia patients with psychiatric diagnoses currently taking antipsychotic medication. At rest, the schizophrenia group demonstrated decreased alpha EEG power in frontal and occipital areas relative to healthy controls. With SSVEP stimulation centered in the alpha band (10Hz), but not with stimulation above (15Hz) or below (7Hz) this range, the occipital deficit in alpha power was partially reverted. However, the frontal deficit persisted and contributed to a significantly reduced topographic relationship between occipital and frontal alpha activity for resting EEG and 10Hz SSVEP alpha power in schizophrenia patients. No significant differences were observed between healthy and medicated controls or between medicated controls and schizophrenia. These findings suggest a potential intrinsic deficit in frontal eyes-closed EEG alpha oscillations in schizophrenia, whereby potent visual stimulation centered in that frequency range results in an increase in the occipital alpha power of these patients, which however does not extend to frontal regions. Future research to evaluate the cortical and subcortical mechanisms of these effects is warranted.

Comparison of feature and classifier algorithms for online automatic sleep staging based on a single EEG signal

Automatic sleep staging on an online basis has recently emerged as a research topic motivated by fundamental sleep research. The aim of this paper is to find optimal signal processing methods and machine learning algorithms to achieve online sleep staging on the basis of a single EEG signal. The classification performance obtained using six different EEG signals and various signal processing feature sets is compared using the kappa statistic which has very recently become popular in sleep staging research. A variable duration of the EEG segment (or epoch) to decide on the sleep stage is also analyzed. Spectral-domain, time-domain, linear, and nonlinear features are compared in terms of performance and two types of machine learning approaches (random forests and support vector machines) are assessed. We have determined that frontal EEG signals, with spectral linear features, epoch durations between 18 and 30 seconds, and a random forest classifier lead to optimal classification performance while ensuring real-time online operation.

Altered overnight modulation of spontaneous waking EEG reflects altered sleep homeostasis in major depressive disorder: a high-density EEG investigation

BACKGROUND

Prior investigations have suggested sleep homeostasis is altered in major depressive disorder (MDD). Low frequency activity (LFA) in the electroencephalogram during waking has been correlated with sleep slow wave activity (SWA), suggesting that waking LFA reflects sleep homeostasis in healthy individuals. This study investigated whether the overnight change in waking LFA and its relationship with sleep SWA are altered in MDD.

METHODS

256-channel high-density electroencephalography (hdEEG) recordings during waking (pre- and post-sleep) and during sleep were collected in 14 unmedicated, unipolar MDD subjects (9 women) and age- and sex-matched healthy controls (HC).

RESULTS

Waking LFA (3.25-6.25 Hz) declined significantly overnight in the HC group, but not in the group of MDD subjects. Overnight decline of waking LFA correlated with sleep SWA in frontal brain regions in HC, but a comparable relationship was not found in MDD.

LIMITATIONS

This study is not able to definitely segregate overnight changes in the waking EEG that may occur due to homeostatic and/or circadian factors.

CONCLUSIONS

MDD involves altered overnight modulation of waking low frequency EEG activity that may reflect altered sleep homeostasis in the disorder. Future research is required to determine the functional significance and clinical implications of these findings.

Synaptic plasticity by antidromic firing during hippocampal network oscillations

Learning and other cognitive tasks require integrating new experiences into context. In contrast to sensory-evoked synaptic plasticity, comparatively little is known of how synaptic plasticity may be regulated by intrinsic activity in the brain, much of which can involve nonclassical modes of neuronal firing and integration. Coherent high-frequency oscillations of electrical activity in CA1 hippocampal neurons [sharp-wave ripple complexes (SPW-Rs)] functionally couple neurons into transient ensembles. These oscillations occur during slow-wave sleep or at rest. Neurons that participate in SPW-Rs are distinguished from adjacent nonparticipating neurons by firing action potentials that are initiated ectopically in the distal region of axons and propagate antidromically to the cell body. This activity is facilitated by GABA(A)-mediated depolarization of axons and electrotonic coupling. The possible effects of antidromic firing on synaptic strength are unknown. We find that facilitation of spontaneous SPW-Rs in hippocampal slices by increasing gap-junction coupling or by GABA(A)-mediated axon depolarization resulted in a reduction of synaptic strength, and electrical stimulation of axons evoked a widespread, long-lasting synaptic depression. Unlike other forms of synaptic plasticity, this synaptic depression is not dependent upon synaptic input or glutamate receptor activation, but rather requires L-type calcium channel activation and functional gap junctions. Synaptic stimulation delivered after antidromic firing, which was otherwise too weak to induce synaptic potentiation, triggered a long-lasting increase in synaptic strength. Rescaling synaptic weights in subsets of neurons firing antidromically during SPW-Rs might contribute to memory consolidation by sharpening specificity of subsequent synaptic input and promoting incorporation of novel information.

Local experience-dependent changes in the wake EEG after prolonged wakefulness

STUDY OBJECTIVES

Prolonged wakefulness leads to a progressive increase in sleep pressure, reflected in a global increase in slow wave activity (SWA, 0.5-4.5 Hz) in the sleep electroencephalogram (EEG). A global increase in wake theta activity (5-9 Hz) also occurs. Recently, it was shown that prolonged wakefulness in rodents leads to signs of "local sleep" in an otherwise awake brain, accompanied by a slow/theta wave (2-6 Hz) in the local EEG that occurs at different times in different cortical areas. Compelling evidence in animals and humans also indicates that sleep is locally regulated by the amount of experience-dependent plasticity. Here, we asked whether the extended practice of tasks that involve specific brain circuits results in increased occurrence of local intermittent theta waves in the human EEG, above and beyond the global EEG changes previously described.

DESIGN

Participants recorded with high-density EEG completed 2 experiments during which they stayed awake ≥ 24 h practicing a language task (audiobook listening [AB]) or a visuomotor task (driving simulator [DS]).

SETTING

Sleep laboratory.

PATIENTS OR PARTICIPANTS

16 healthy participants (7 females).

INTERVENTIONS

Two extended wake periods.

MEASUREMENTS AND RESULTS

Both conditions resulted in global increases in resting wake EEG theta power at the end of 24 h of wake, accompanied by increased sleepiness. Moreover, wake theta power as well as the occurrence and amplitude of theta waves showed regional, task-dependent changes, increasing more over left frontal derivations in AB, and over posterior parietal regions in DS. These local changes in wake theta power correlated with similar local changes in sleep low frequencies including SWA.

CONCLUSIONS

Extended experience-dependent plasticity of specific circuits results in a local increase of the wake theta EEG power in those regions, followed by more intense sleep, as reflected by SWA, over the same areas.

Extracellular levels of lactate, but not oxygen, reflect sleep homeostasis in the rat cerebral cortex

STUDY OBJECTIVE

It is well established that brain metabolism is higher during wake and rapid eye movement (REM) sleep than in nonrapid eye movement (NREM) sleep. Most of the brain's energy is used to maintain neuronal firing and glutamatergic transmission. Recent evidence shows that cortical firing rates, extracellular glutamate levels, and markers of excitatory synaptic strength increase with time spent awake and decline throughout NREM sleep. These data imply that the metabolic cost of each behavioral state is not fixed but may reflect sleep-wake history, a possibility that is investigated in the current report.

DESIGN

Chronic (4d) electroencephalographic (EEG) recordings in the rat cerebral cortex were coupled with fixed-potential amperometry to monitor the extracellular concentration of oxygen ([oxy]) and lactate ([lac]) on a second-by-second basis across the spontaneous sleep-wake cycle and in response to sleep deprivation.

SETTING

Basic sleep research laboratory.

PATIENTS OR PARTICIPANTS

Wistar Kyoto (WKY) adult male rats.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

Within 30-60 sec [lac] and [oxy] progressively increased during wake and REM sleep and declined during NREM sleep (n = 10 rats/metabolite), but with several differences. [Oxy], but not [lac], increased more during wake with high motor activity and/or elevated EEG high-frequency power. Meanwhile, only the NREM decline of [lac] reflected sleep pressure as measured by slow-wave activity, mirroring previous results for cortical glutamate.

CONCLUSIONS

The observed state-dependent changes in cortical [lac] and [oxy] are consistent with higher brain metabolism during waking and REM sleep in comparison with NREM sleep. Moreover, these data suggest that glycolytic activity, most likely through its link with glutamatergic transmission, reflects sleep homeostasis.

Overnight changes in waking auditory evoked potential amplitude reflect altered sleep homeostasis in major depression

OBJECTIVE

Sleep homeostasis is altered in major depressive disorder (MDD). Pre- to postsleep decline in waking auditory evoked potential (AEP) amplitude has been correlated with sleep slow wave activity (SWA), suggesting that overnight changes in waking AEP amplitude are homeostatically regulated in healthy individuals. This study investigated whether the overnight change in waking AEP amplitude and its relation to SWA is altered in MDD.

METHOD

Using 256-channel high-density electroencephalography, all-night sleep polysomnography and single-tone waking AEPs pre- and postsleep were collected in 15 healthy controls (HC) and 15 non-medicated individuals with MDD.

RESULTS

N1 and P2 amplitudes of the waking AEP declined after sleep in the HC group, but not in MDD. The reduction in N1 amplitude also correlated with fronto-central SWA in the HC group, but a comparable relationship was not found in MDD, despite equivalent SWA between groups. No pre- to postsleep differences were found for N1 or P2 latencies in either group. These findings were not confounded by varying levels of alertness or differences in sleep variables between groups.

CONCLUSION

MDD involves altered sleep homeostasis as measured by the overnight change in waking AEP amplitude. Future research is required to determine the clinical implications of these findings.

High density electroencephalography in sleep research: potential, problems, future perspective

High density EEG (hdEEG) during sleep combines the superior temporal resolution of EEG recordings with high spatial resolution. Thus, this method allows a topographical analysis of sleep EEG activity and thereby fosters the shift from a global view of sleep to a local one. HdEEG allowed to investigate sleep rhythms in terms of their characteristic behavior (e.g., the traveling of slow waves) and in terms of their relationship to cortical functioning (e.g., consciousness and cognitive abilities). Moreover, recent studies successfully demonstrated that hdEEG can be used to study brain functioning in neurological and neuro-developmental disorders, and to evaluate therapeutic approaches. This review highlights the potential, the problems, and future perspective of hdEEG in sleep research.

Electrophysiological traces of visuomotor learning and their renormalization after sleep

OBJECTIVE

Adapting movements to a visual rotation involves the activation of right posterior parietal areas. Further performance improvement requires an increase of slow wave activity in subsequent sleep in the same areas. Here we ascertained whether a post-learning trace is present in wake EEG and whether such a trace is influenced by sleep slow waves.

METHODS

In two separate sessions, we recorded high-density EEG in 17 healthy subjects before and after a visuomotor rotation task, which was performed both before and after sleep. High-density EEG was recorded also during sleep. One session aimed to suppress sleep slow waves, while the other session served as a control.

RESULTS

After learning, we found a trace in the eyes-open wake EEG as a local, parietal decrease in alpha power. After the control night, this trace returned to baseline levels, but it failed to do so after slow wave deprivation. The overnight change of the trace correlated with the dissipation of low frequency (<8 Hz) NREM sleep activity only in the control session.

CONCLUSIONS

Visuomotor learning leaves a trace in the wake EEG alpha power that appears to be renormalized by sleep slow waves.

SIGNIFICANCE

These findings link visuomotor learning to regional changes in wake EEG and sleep homeostasis.