Eye Movement Sleep Electroencephalogram Research Articles

The two-process model of sleep regulation: Beginnings and outlook.

SummaryThe two‐process model serves as a major conceptual framework in sleep science. Although dating back more than four decades, it has not lost its relevance for research today. Retracing its origins, I describe how animal experiments aimed at exploring the oscillators driving the circadian sleep–wake rhythm led to the recognition of gradients of sleep states within the daily sleep period. Advances in signal analysis revealed that the level of slow‐wave activity in non‐rapid eye movement sleep electroencephalogram is high at the beginning of the 12‐light period and then declines. After sleep deprivation, the level of slow‐wave activity is enhanced. By scheduling recovery sleep to the animal's activity period, the conflict between the sleep–wake‐dependent and the circadian influence resulted in a two‐stage recovery pattern. These experiments provided the basis for the first version of the two‐process model. Sleep deprivation experiments in humans showed that the decline of slow‐wave activity during sleep is exponential. The two‐process model posits that a sleep–wake‐dependent homeostatic process (Process S) interacts with a process controlled by the circadian pacemaker (Process C). At present, homeostatic and circadian facets of sleep regulation are being investigated at the synaptic level as well as in the transcriptome and proteome domains. The notion of sleep has been extended from a global phenomenon to local representations, while the master circadian pacemaker has been supplemented by multiple peripheral oscillators. The original interpretation that the emergence of sleep may be viewed as an escape from the rigid control imposed by the circadian pacemaker is still upheld.

S6. SLEEP ENDOPHENOTYPES OF SCHIZOPHRENIA: A HIGH-DENSITY EEG STUDY IN DRUG-NAïVE, FIRST EPISODE PSYCHOSIS PATIENTS

BackgroundSlow waves, the hallmark of the deep nonrapid eye movement sleep electroencephalogram (EEG), are critical for restorative sleep and brain plasticity. They arise from the synchronous depolarization and hyperpolarization of millions of cortical neurons and their proper generation and propagation relies upon the integrity of widespread cortico-thalamic networks. Slow wave abnormalities have been reported in patient with Schizophrenia, although with partially contradictory results, probably related to antipsychotic and sedative medications. Recently, their presence and delineation, have been convincingly shown in first-episode psychosis patients (FEP). However, clear evidence of this biomarker at the onset of the disease, prior to any psychopharmacological intervention, remains limited. Moreover, no attempt has been made to elucidate the prognostic meaning of this finding.MethodsWe collected whole night sleep high–density electroencephalography recordings (64-channel BrainAmp, Brain Products GmbH, Gilching, Germany) in 20 drug-naive FEP patients and 20 healthy control subjects (HC). Several clinical psychometric scales as well as neurocognitive tests were administered to all subjects in order to better define psychopathological status and vulnerability. EEG slow wave activity (SWA, spectral power between 1 and 4 Hz) and several slow wave parameters were computed at each electrode location, including density and amplitude, at each electrode location. Along with a group analysis between FEP and HC, a subgroup analysis was also computed between patients who showed a progression of symptoms to full-blown Schizophrenia (SCZ, n = 10) over the next 12-month follow-up and those who did not (OTH, n = 10).ResultsSleep macro-architecture was globally preserved in FEP patients. SWA (1–4 Hz) was lower in FEP compared to HC but this difference didn’t reach statistical significance. Slow wave density was decreased in FEP compared to HC, with a significance that survived multiple comparison correction over a large fronto-central cluster. Mean amplitude was preserved. At the subgroup analysis, these results were largely driven by the subgroup of patients with a confirmed diagnosis of SCZ at a 12-month follow-up. Indeed, no difference could be found between OTH and HC, while a strong significance was still evident between SCZ and HC.DiscussionOur data confirm previous findings on reduced slow wave density in FEP, and expand them to acute subjects, before any treatment is prescribed. This is in line with available data on diffuse abnormalities of cortico-cortical and cortico-thalamic networks in these patients. Interestingly, our data also offer preliminary evidence that this deficit is specific for SCZ, as it appears to differentiate patients who developed SCZ from those with other diagnoses at follow-up. Given the traveling properties of slow waves, future research should establish their potential as markers of connectivity in SCZ.

NREM sleep EEG slow waves in autistic and typically developing children: Morphological characteristics and scalp distribution.

Autism is a developmental disorder with a neurobiological aetiology. Studies of the autistic brain identified atypical developmental trajectories that may lead to an impaired capacity to modulate electroencephalogram activity during sleep. We assessed the topography and characteristics of non-rapid eye movement sleep electroencephalogram slow waves in 26 boys aged between 6 and 13 years old: 13 with an autism spectrum disorder and 13 typically developing. None of the participants was medicated, intellectually disabled, reported poor sleep, or suffered from medical co-morbidities. Results are derived from a second consecutive night of polysomnography in a sleep laboratory. Slow waves (0.3-4.0 Hz; >75 µV) were automatically detected on artefact-free sections of non-rapid eye movement sleep along the anteroposterior axis in frontal, central, parietal and occipital derivations. Slow wave density (number per minute), amplitude (µV), slope (µV s-1 ) and duration (s) were computed for the first four non-rapid eye movement periods. Slow wave characteristics comparisons between groups, derivations and non-rapid eye movement periods were assessed with three-way mixed ANOVAs. Slow wave density, amplitude, slope and duration were higher in anterior compared with most posterior derivations in both groups. Children with autism spectrum disorder showed lower differences in slow waves between recording sites along the anteroposterior axis than typically developing children. These group differences in the topography of slow wave characteristics were stable across the night. We propose that slow waves during non-rapid eye movement sleep could be an electrophysiological marker of the deviant cortical maturation in autism linked to an atypical functioning of thalamo-cortical networks.

Traveling Slow Oscillations During Sleep: A Marker of Brain Connectivity in Childhood.

Slow oscillations, a defining characteristic of the nonrapid eye movement sleep electroencephalogram (EEG), proliferate across the scalp in highly reproducible patterns. In adults, the propagation of slow oscillations is a recognized fingerprint of brain connectivity and excitability. In this study, we (1) describe for the first time maturational features of sleep slow oscillation propagation in children (n = 23; 2-13 years) using high-density (hd) EEG and (2) examine associations between sleep slow oscillatory propagation characteristics (ie, distance, traveling speed, cortical involvement) and white matter myelin microstructure as measured with multicomponent Driven Equilibrium Single Pulse Observation of T1 and T2-magnetic resonance imaging (mcDESPOT-MRI). Results showed that with increasing age, slow oscillations propagated across longer distances (average growth of 0.2 cm per year; R(21) = 0.50, p < .05), while traveling speed and cortical involvement (ie, slow oscillation expanse) remained unchanged across childhood. Cortical involvement (R(20) = 0.44) and slow oscillation speed (R(20) = -0.47; both p < .05, corrected for age) were associated with myelin content in the superior longitudinal fascicle, the largest anterior-posterior, intrahemispheric white matter connectivity tract. Furthermore, slow oscillation distance was moderately associated with whole-brain (R(21) = 0.46, p < .05) and interhemispheric myelin content, the latter represented by callosal myelin water fraction (R(21) = 0.54, p < .01, uncorrected). Thus, we demonstrate age-related changes in slow oscillation propagation distance, as well as regional associations between brain activity during sleep and the anatomical connectivity of white matter microstructure. Our findings make an important contribution to knowledge of the brain connectome using a noninvasive and novel analytic approach. These data also have implications for understanding the emergence of neurodevelopmental disorders and the role of sleep in brain maturation trajectories.

The spectrum of the non-rapid eye movement sleep electroencephalogram following total sleep deprivation is trait-like.

The sleep electroencephalogram (EEG) spectrum is unique to an individual and stable across multiple baseline recordings. The aim of this study was to examine whether the sleep EEG spectrum exhibits the same stable characteristics after acute total sleep deprivation. Polysomnography (PSG) was recorded in 20 healthy adults across consecutive sleep periods. Three nights of baseline sleep [12h time in bed (TIB)] following 12h of wakefulness were interleaved with three nights of recovery sleep (12h TIB) following 36h of sustained wakefulness. Spectral analysis of the non-rapid eye movement (NREM) sleep EEG (C3LM derivation) was used to calculate power in 0.25Hz frequency bins between 0.75 and 16.0Hz. Intraclass correlation coefficients (ICCs) were calculated to assess stable individual differences for baseline and recovery night spectra separately and combined. ICCs were high across all frequencies for baseline and recovery and for baseline and recovery combined. These results show that the spectrum of the NREM sleep EEG is substantially different among individuals, highly stable within individuals and robust to an experimental challenge (i.e. sleep deprivation) known to have considerable impact on the NREM sleep EEG. These findings indicate that the NREM sleep EEG represents a trait.

Sleep spindles and rapid eye movement sleep as predictors of next morning cognitive performance in healthy middle‐aged and older participants

Spindles and slow waves are hallmarks of non-rapid eye movement sleep. Both these oscillations are markers of neuronal plasticity, and play a role in memory and cognition. Normal ageing is associated with spindle and slow wave decline and cognitive changes. The present study aimed to assess whether spindle and slow wave characteristics during a baseline night predict cognitive performance in healthy older adults the next morning. Specifically, we examined performance on tasks measuring selective and sustained visual attention, declarative verbal memory, working memory and verbal fluency. Fifty-eight healthy middle-aged and older adults (aged 50-91years) without sleep disorders underwent baseline polysomnographic sleep recording followed by neuropsychological assessment the next morning. Spindles and slow waves were detected automatically on artefact-free non-rapid eye movement sleep electroencephalogram. All-night stage N2 spindle density (no./min) and mean frequency (Hz) and all-night non-rapid eye movement sleep slow wave density (no./min) and mean slope (μV/s) were analysed. Pearson's correlations were performed between spindles, slow waves, polysomnography and cognitive performance. Higher spindle density predicted better performance on verbal learning, visual attention and verbal fluency, whereas spindle frequency and slow wave density or slope predicted fewer cognitive performance variables. In addition, rapid eye movement sleep duration was associated with better verbal learning potential. These results suggest that spindle density is a marker of cognitive functioning in older adults and may reflect neuroanatomic integrity. Rapid eye movement sleep may be a marker of age-related changes in acetylcholine transmission, which plays a role in new information encoding.

Slow oscillations in human non-rapid eye movement sleep electroencephalogram: effects of increased sleep pressure

Slow oscillations (< 1 Hz) in the non-rapid eye movement (NREM) sleep electroencephalogram (EEG) result from slow membrane potential fluctuations of cortical neurones, alternating between a depolarized up-state and a hyperpolarized down-state. They are thought to underlie the restorative function of sleep. We investigated the behaviour of slow oscillations in humans under increased sleep pressure to assess their contribution to sleep homeostasis. EEG recordings (C3A2) of baseline and recovery sleep after sleep deprivation (eight healthy males, mean age 23 years; 40 h of prolonged wakefulness) were analysed. Half-waves were defined as positive or negative deflections between consecutive zero crossings in the 0.5-2 Hz range of the band-pass filtered EEG. Increased sleep pressure resulted in a redistribution of half-waves between 0.5 and 2 Hz: the number of half-waves per minute was reduced below 0.9 Hz while it was increased above 1.2 Hz. EEG power was increased above 1 Hz. The increase in frequency was accompanied by increased slope of the half-waves and decreased number of multi-peak waves. In both baseline and recovery sleep, amplitude and slope were correlated highly over a broad frequency range and positive half-waves were characterized by a lower frequency than the negative ones, pointing to a longer duration of up- than down-states. We hypothesize that the higher frequency of slow oscillatory activity after prolonged wakefulness may relate to faster alternations between up- and down-states at the cellular level under increased sleep pressure. This study does not question slow-wave activity as a marker of sleep homeostasis, as the observed changes occurred within the same frequency range.

Microstructure of the non-rapid eye movement sleep electroencephalogram in patients with newly diagnosed Parkinson's disease: effects of dopaminergic treatment.

We investigated non-rapid eye movement (non-REM) sleep in patients with newly diagnosed Parkinson's disease (PD) who had never previously received dopaminergic medication. There were no significant differences in the conventional sleep parameters between de novo patients with PD and a healthy control group, but the length of stage 1 sleep and the number of awakenings increased significantly upon administration of dopaminergic drugs. Analyzing the quantitative electroencephalogram (EEG), we observed a significant reduction in the low-delta frequency range and a nonsignificant increase in the sigma frequency range in de novo patients with PD. The dopaminergic medication also nonsignificantly reduced the low-delta and sigma frequencies, the latter to the level of the controls. Possible mechanisms that may account for the observed differences are discussed. It is suggested that Parkinson's disease as well as the application of dopaminergic drugs exerts a desynchronizing effect on the sleep EEG that is reflected in a disruption of sleep continuity.

Spectral analysis of the rapid eye movement sleep electroencephalogram in right and left temporal regions: a biological marker of Alzheimer's disease.

Spectral analysis of electroencephalograms (EEGs) for both wakefulness and rapid eye movement (REM) sleep was performed over the temporal regions in 8 patients with mild to moderate Alzheimer's disease and in 8 age-matched control subjects. EEG slowing in Alzheimer patients was found to be much more prominent during REM sleep than during wakefulness. In addition, asymmetry on the awake EEG of Alzheimer patients was found to be even more prominent than on the REM sleep EEG. When EEG values of the most impaired hemisphere during REM sleep were examined, no overlap was found between the two groups either for the ratio of slow to fast frequencies or for percent power of each of the frequency bands. This was not the case for the awake EEG. These results suggest that diagnostically meaningful cutoff values for discriminating patients with mild to moderate Alzheimer's disease from age-matched control subjects can be derived from the REM sleep EEG of the temporal lobe.