Sleep Transitions Research Articles

AM-251, A Cannabinoid Antagonist, Modifies the Dynamics of Sleep-Wake Cycles in Rats.

Study Objectives: (a) To describe the microarchitecture of wakefulness and sleep following administrations of 5- and 10-mg/kg AM-251 in rats. (b) To develop a new statistical method to follow bout-to-bout dynamics. Method: Wistar rats (n = 6) had been equipped with electroencephalography (EEG) and electromyography (EMG) electrodes. Following their recovery and habituation after the surgery, the animals were injected with vehicle and 5- and 10-mg/kg AM-251 intraperitoneally and EEG, EMG, and motor activity were analyzed for the subsequent 3 h. Results: AM-251 induced a dose- and time-dependent increase in the number of bouts in active wake (AW), and it decreased this number in all other vigilance states except in passive wake (PW). In contrast, the bout duration in PW compensatory decreased. The effect of AM-251 on the sleep transition dynamics was monitored with a new tool we call “transition heatmap.” The analysis of bout trajectories with transition heatmaps reveals a highly organized pattern. Conclusion: AM-251 selectively influences the frequency of vigilance state transitions, but it has no direct impact on the state lengths. AM-251 markedly changed the state transition dynamics, which was visualized with the help of state transition heatmaps.

Dorsal Striatum Dopamine Levels Fluctuate Across the Sleep-Wake Cycle and Respond to Salient Stimuli in Mice.

Dopamine is involved in numerous neurological processes, and its deficiency has been implicated in Parkinson’s disease, whose patients suffer from severe sleep disorders. Destruction of nigrostriatal dopaminergic neurons or dorsal striatum disrupts the sleep–wake cycle. However, whether striatal dopamine levels correlate with vigilance states still remains to be elucidated. Here, we employed an intensity-based genetically encoded dopamine indicator, dLight1.1, to track striatal dopamine levels across the spontaneous sleep–wake cycle and the dopaminergic response to external stimuli. We found that the striatal dLight1.1 signal was at its highest during wakefulness, lower during non-rapid eye movement (non-REM or NREM) sleep, and lowest during REM sleep. Moreover, the striatal dLight1.1 signal increased significantly during NREM sleep-to-wake transitions, while it decreased during wake-to-NREM sleep transitions. Furthermore, different external stimuli, such as sudden door-opening of the home cage or cage-change to a new environment, caused striatal dopamine release, whereas an unexpected auditory tone did not. Finally, despite both modafinil and caffeine being wake-promoting agents that increased wakefulness, modafinil increased striatal dopamine levels while caffeine did not. Taken together, our findings demonstrated that striatal dopamine levels correlated with the spontaneous sleep–wake cycle and responded to specific external stimuli as well as the stimulant modafinil.

Reducing bedtime physiological arousal levels using immersive audio-visual respiratory bio-feedback: a pilot study in women with insomnia symptoms.

Hyperarousal is a critical component of insomnia, particularly at bedtime when individuals are trying to fall asleep. The current study evaluated the effect of a novel, acute behavioral experimental manipulation (combined immersive audio-visual relaxation and biofeedback) in reducing bedtime physiological hyperarousal in women with insomnia symptoms. After a clinical/adaptation polysomnographic (PSG) night, sixteen women with insomnia symptoms had two random-order PSG nights: immersive audio-visual respiratory bio-feedback across the falling asleep period (manipulation night), and no pre-sleep arousal manipulation (control night). While using immersive audio-visual respiratory bio-feedback, overall heart rate variability was increased and heart rate (HR) was reduced (by ~ 5bpm; p < 0.01), reflecting downregulation of autonomic pre-sleep arousal, relative to no-manipulation. HR continued to be lower during sleep, and participants had fewer awakenings and sleep stage transitions on the manipulation night relative to the control night (p < 0.05). The manipulation did not affect sleep onset latency or other PSG parameters. Overall, this novel behavioral approach targeting the falling asleep process emphasizes the importance of pre-sleep hyperarousal as a potential target for improving sleep and nocturnal autonomic function during sleep in insomnia.

Proceedings #11: Replay of Endogenous Sleep Rhythms to Produce Sleepiness

Varying modes of non-invasive electrical stimulation techniques have been investigated to induce endogenous sleep-like states (historically called Electrosleep). These include transcranial pulsed current stimulation (tPCS) such as Cranial Electrical Stimulation, transcranial direct current stimulation (tDCS), and transcranial alternating current stimulation (tACS) such as 10 Hz sinusoidal stimulation. Prior efforts used synthetic (simple) waveforms selected to modulate excitability (e.g. tDCS) or reproduce a single predominant frequency of endogenous neuronal rhythms of sleep induction (e.g. 10 Hz). To examine the effects of electrical stimulation with a complete spectrum sleep-related endogenous neural activity, we designed and applied an endogenous sleep-derived stimulation waveform to subjects while assessing a range subjective performance and objective physiological data. We hypothesized that a stimulation with complex high-bandwidth waveform reflecting endogenous sleep-associated neuronal activity patterns (transcranial Endogenous Sleep-Derived; tESD) would be more effective, than synthetic frequency-specific waveforms such at tACS, in supporting the transition to sleepiness. The basis for the transcranial Endogenous Sleep-Derived (tESD) waveform was acquired during a resting, sleepy-state EEG session. Data were examined for markers of sleepiness and corresponding segments were extracted, compressed, and scaled to produce a current signal. Stimulation was applied through a custom, high-bandwidth current-control stimulator. Subjects were supine in a light and sound attenuated environment. Using HD bipolar montage (AF7, AF8) with a maximal current amplitude of 0.5 mA over 10 minutes. tESD was also simulated in a computational model. Physiology (EEG, ECG, respiration, EOG, EMG) and behavior (questionnaires, reaction time) was assessed before, during (only for physiology), and after stimulation. Each subject underwent tESD, 10 Hz tACS, and a no-stimulation (non-interventional) sessions in a counterbalanced manner with at least 24 hours between each session. tESD polarized the frontal lobe. Changes in the no-stimulation condition confirms the testing environment was conducive to a wakefulness–sleep transition. Preliminary data indicate an enhanced shift in physiological measures in directions consistent with a relaxed and sleepy state with tESD compared to tACS and no-stimulation conditions. Behavioral data indicate a delay in reactions times post stimulation and subjective sleepiness reports indicate higher sleepiness post stimulation. tESD was well tolerated and blinding was effective. tESD aims to “replay” the endogenous neuronal signature of sleep. Neurophysiological (EEG), physiological (heart rate, respiration) and behavioral (simple reaction time, PVT) indicate that tESD, directed to frontal brain regions, that are associated with top-down thalamo-cortical sleep control mechanisms, accelerated wakefulness–sleep transition in subjects in a baseline relaxed state.

Insomnia in breast cancer: a prospective observational study.

Insomnia in cancer patients is prevalent, persistent, and confers risk for physical and psychological disorder. We must better understand how insomnia develops in cancer patients and explore the main contributors to its chronicity so that insomnia management protocols can be integrated more effectively within cancer care. This study monitors the etiology of insomnia in breast cancer patients and identifies risk factors for its persistence. One hundred seventy-three females with newly diagnosed, non-metastatic breast cancer were tracked from diagnosis for 12 months. Participants completed monthly sleep assessments using the Insomnia Severity Index (ISI) and 3 monthly health-related quality-of-life assessments using the European Organisation for Research and Treatment of Cancer - Breast (EORTC QLQ-C30-BR23) scale. Clinical data on disease status and treatment regimens were also assessed. Prior to diagnosis, 25% of participants reported sleep disturbance, including 8% with insomnia syndrome (IS). Prevalence increased at cancer diagnosis to 46% (18% IS) and remained stable thereafter at around 50% (21% IS). We also explored sleep status transitions. The most common pattern was to remain a good sleeper (34%-49%) or to persist with insomnia (23%-46%). Seventy-seven percent of good sleepers developed insomnia during the 12-month period and 54% went into insomnia remission. Chemotherapy (odds ratio = 0.08, 95% confidence interval [CI] 0.02-0.29, p < .001) and pre-diagnosis ISI scores (odds ratio = 1.13/unit increase in pre-diagnosis sleep score, 95% CI 1.05-1.21, p = .001) were identified as the main risk factors for persistent insomnia. These data advance our understanding of insomnia etiology in cancer patients and help identify those who should be prioritized for insomnia management protocols.

Intracortical Causal Information Flow of Oscillatory Activity (Effective Connectivity) at the Sleep Onset Transition.

We investigated the sleep onset transition in humans from an effective connectivity perspective in a baseline condition (approx. 16 h of wakefulness) and after sleep deprivation (40 h of sustained wakefulness). Using EEG recordings (27 derivations), source localization (LORETA) allowed us to reconstruct the underlying patterns of neuronal activity in various brain regions, e.g., the default mode network (DMN), dorsolateral prefrontal cortex and hippocampus, which were defined as regions of interest (ROI). We applied isolated effective coherence (iCOH) to assess effective connectivity patterns at the sleep onset transition [2 min prior to and 10 min after sleep onset (first occurrence of stage 2)]. ICOH reveals directionality aspects and resolves the spectral characteristics of information flow in a given network of ROIs. We observed an anterior-posterior decoupling of the DMN, and moreover, a prominent role of the posterior cingulate cortex guiding the process of the sleep onset transition, particularly, by transmitting information in the low frequency range (delta and theta bands) to other nodes of DMN (including the hippocampus). In addition, the midcingulate cortex appeared as a major cortical relay station for spindle synchronization (originating from the thalamus; sigma activity). The inclusion of hippocampus indicated that this region might be functionally involved in sigma synchronization observed in the cortex after sleep onset. Furthermore, under conditions of increased homeostatic pressure, we hypothesize that an anterior-posterior decoupling of the DMN occurred at a faster rate compared to baseline overall indicating weakened connectivity strength within the DMN. Finally, we also demonstrated that cortico-cortical spindle synchronization was less effective after sleep deprivation than in baseline, thus, reflecting the reduction of spindles under increased sleep pressure.

Automatic sleep classification using adaptive segmentation reveals an increased number of rapid eye movement sleep transitions.

The reference standard for sleep classification uses manual scoring of polysomnography with fixed 30-s epochs. This limits the analysis of sleep pattern, structure and, consequently, detailed association with other physiologic processes. We aimed to improve the details of sleep evaluation by developing a data-driven method that objectively classifies sleep in smaller time intervals. Two adaptive segmentation methods using 3, 10 and 30-s windows were compared. One electroencephalographic (EEG) channel was used to segment into quasi-stationary segments and each segment was classified using a multinomial logistic regression model. Classification features described the power in the clinical frequency bands of three EEG channels and an electrooculographic (EOG) anticorrelation measure for each segment. The models were optimised using 19 healthy control subjects and validated on 18 healthy control subjects. The models obtained overall accuracies of 0.71±0.09, 0.74±0.09 and 0.76±0.08 on the validation data. However, the models allowed a more dynamic sleep, which challenged a true validation against manually scored hypnograms with fixed epochs. The automated classifications indicated an increased number of stage transitions and shorter sleep bouts using models with smaller window size compared with the hypnograms. An increased number of transitions from rapid eye movement (REM) sleep was likewise expressed in the model using 30-s windows, indicating that REM sleep has more fluctuations than captured by today's standard. The models developed are generally applicable and may contribute to concise sleep structure evaluation, research in sleep control and improved understanding of sleep and sleep disorders. The models could also contribute to objective measuring of sleep stability.

Control of Sleep Onset by Shal/Kv4 Channels in Drosophila Circadian Neurons.

Sleep is highly conserved across animal species. Both wake- and sleep-promoting neurons are implicated in the regulation of wake-sleep transition at dusk in Drosophila However, little is known about how they cooperate and whether they act via different mechanisms. Here, we demonstrated that in female Drosophila, sleep onset was specifically delayed by blocking the Shaker cognate L channels [Shal; also known as voltage-gated K+ channel 4 (Kv4)] in wake-promoting cells, including large ventral lateral neurons (l-LNvs) and pars intercerebralis (PI), but not in sleep-promoting dorsal neurons (DN1s). Delayed sleep onset was also observed in males by blocking Kv4 activity in wake-promoting neurons. Electrophysiological recordings show that Kv4 channels contribute A-type currents in LNvs and PI cells, but are much less conspicuous in DN1s. Interestingly, blocking Kv4 in wake-promoting neurons preferentially increased firing rates at dusk ∼ZT13, when the resting membrane potentials and firing rates were at lower levels. Furthermore, pigment-dispersing factor (PDF) is essential for the regulation of sleep onset by Kv4 in l-LNvs, and downregulation of PDF receptor (PDFR) in PI neurons advanced sleep onset, indicating Kv4 controls sleep onset via regulating PDF/PDFR signaling in wake-promoting neurons. We propose that Kv4 acts as a sleep onset controller by suppressing membrane excitability in a clock-dependent manner to balance the wake-sleep transition at dusk. Our results have important implications for the understanding and treatment of sleep disorders such as insomnia.SIGNIFICANCE STATEMENT The mechanisms by which our brains reversibly switch from waking to sleep state remain an unanswered and intriguing question in biological research. In this study, we identified that Shal/Kv4, a well known voltage-gated K+ channel, acts as a controller of wake-sleep transition at dusk in Drosophila circadian neurons. We find that interference of Kv4 function with a dominant-negative form (DNKv4) in subsets of circadian neurons specifically disrupts sleep onset at dusk, although Kv4 itself does not exhibit circadian oscillation. Kv4 preferentially downregulates neuronal firings at ZT9-ZT17, supporting that it plays an essential role in wake-sleep transition at dusk. Our findings may help understand and eventually treat sleep disorders such as insomnia.

Acute control of the sleep switch in Drosophila reveals a role for gap junctions in regulating behavioral responsiveness.

Sleep is a dynamic process in most animals, involving distinct stages that probably perform multiple functions for the brain. Before sleep functions can be initiated, it is likely that behavioral responsiveness to the outside world needs to be reduced, even while the animal is still awake. Recent work in Drosophila has uncovered a sleep switch in the dorsal fan-shaped body (dFB) of the fly's central brain, but it is not known whether these sleep-promoting neurons also govern the acute need to ignore salient stimuli in the environment during sleep transitions. We found that optogenetic activation of the sleep switch suppressed behavioral responsiveness to mechanical stimuli, even in awake flies, indicating a broader role for these neurons in regulating arousal. The dFB-mediated suppression mechanism and its associated neural correlates requires innexin6 expression, suggesting that the acute need to reduce sensory perception when flies fall asleep is mediated in part by electrical synapses.

The Color of Noise and Weak Stationarity at the NREM to REM Sleep Transition in Mild Cognitive Impaired Subjects.

In Older Adults (OAs), Electroencephalogram (EEG) slowing in frontal lobes and a diminished muscle atonia during Rapid Eye Movement sleep (REM) have each been effective tracers of Mild Cognitive Impairment (MCI), but this relationship remains to be explored by non-linear analysis. Likewise, data provided by EEG, EMG (Electromyogram) and EOG (Electrooculogram)—the three required sleep indicators—during the transition from REM to Non-REM (NREM) sleep have not been related jointly to MCI. Therefore, the main aim of the study was to explore, with results for Detrended Fluctuation Analysis (DFA) and multichannel DFA (mDFA), the Color of Noise (CN) at the NREM to REM transition in OAs with MCI vs. subjects with good performances. The comparisons for the transition from NREM to REM were made for each group at each cerebral area, taking bilateral derivations to evaluate interhemispheric coupling and anteroposterior and posterior networks. In addition, stationarity analysis was carried out to explore if the three markers distinguished between the groups. Neuropsi and the Mini-Mental State Examination (MMSE) were administered, as well as other geriatric tests. One night polysomnography was applied to 6 OAs with MCI (68.1 ± 3) and to 7 subjects without it (CTRL) (64.5 ± 9), and pre-REM and REM epochs were analyzed for each subject. Lower scores for attention, memory and executive funcions and a greater index of arousals during sleep were found for the MCI group. Results confirmed that EOGs constituted significant markers of MCI, increasing the CN for the MCI group in REM sleep. The CN of the EEG from the pre-REM to REM was higher for the MCI group vs. the opposite for the CTRL group at frontotemporal areas. Frontopolar interhemispheric scaling values also followed this trend as well as right anteroposterior networks. EMG Hurst values for both groups were lower than those for EEG and EOG. Stationarity analyses showed differences between stages in frontal areas and right and left EOGs for both groups. These results may demonstrate the breakdown of fractality of areas especially involved in executive functioning and the way weak stationarity analyses may help to distinguish between sleep stages in OAs.

Genetic Activation, Inactivation, and Deletion Reveal a Limited And Nuanced Role for Somatostatin-Containing Basal Forebrain Neurons in Behavioral State Control.

Recent studies have identified an especially important role for basal forebrain GABAergic (BFVGAT) neurons in the regulation of behavioral waking and fast cortical rhythms associated with cognition. However, BFVGAT neurons comprise several neurochemically and anatomically distinct subpopulations, including parvalbumin-containing BFVGAT neurons and somatostatin-containing BFVGAT neurons (BFSOM neurons), and it was recently reported that optogenetic activation of BFSOM neurons increases the probability of a wakefulness to non-rapid-eye movement (NREM) sleep transition when stimulated during the rest period of the animal. This finding was unexpected given that most BFSOM neurons are not NREM sleep active and that central administration of the synthetic somatostatin analog, octreotide, suppresses NREM sleep or increases REM sleep. Here we used a combination of genetically driven chemogenetic and optogenetic activation, chemogenetic inhibition, and ablation approaches to further explore the in vivo role of BFSOM neurons in arousal control. Our findings indicate that acute activation or inhibition of BFSOM neurons is neither wakefulness nor NREM sleep promoting and is without significant effect on the EEG, and that chronic loss of these neurons is without effect on total 24 h sleep amounts, although a small but significant increase in waking was observed in the lesioned mice during the early active period. Our in vitro cell recordings further reveal electrophysiological heterogeneity in BFSOM neurons, specifically suggesting at least two distinct subpopulations. Together, our data support the more nuanced view that BFSOM neurons are electrically heterogeneous and are not NREM sleep or wake promoting per se, but may exert, in particular during the early active period, a modest inhibitory influence on arousal circuitry.SIGNIFICANCE STATEMENT The cellular basal forebrain (BF) is a highly complex area of the brain that is implicated in a wide range of higher-level neurobiological processes, including regulating and maintaining normal levels of electrocortical and behavioral arousal. The respective in vivo roles of BF cell populations and their neurotransmitter systems in the regulation of electrocortical and behavioral arousal remains incompletely understood. Here we seek to define the neurobiological contribution of GABAergic somatostatin-containing BF neurons to arousal control. Understanding the respective contribution of BF cell populations to arousal control may provide critical insight into the pathogenesis of a host of neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, schizophrenia, and the cognitive impairments of normal aging.

S93. Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data

Sleep is a complex physiological process, linked with the function of every bodily organ, and its dysregulation has negative impacts for well-being and health. Despite its importance, after decades of research, much uncertainty remains with respect to brain functional changes occurring when we fall asleep. The known point is that there are remarkable changes between full awake and sleep conditions and that the variety of human states of consciousness and the wakefulness–sleep (W–S) transition are based on the dynamic connectivity of brain regions that continuously interact through complex neural networks with time- and task-varying architecture. Sleep onset is characterized by a specific and orchestrated pattern of frequency and topographical EEG changes. Conventional power analyses of electroencephalographic (EEG) and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. Here, we assess how “small world” characteristics of the brain networks, as reflected in the EEG rhythms, are modified in the wakefulness-sleep transition comparing the pre- and post-sleep onset epochs. The results show that sleep onset is characterized by a less ordered brain network (as reflected by the higher value of small world) in the sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in the low frequency delta and theta bands indicating disconnection on the remaining brain areas. Our results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset. This study opens interesting avenues for future researches investigating eventual modifications of brain connectivity and network organization in the evolution of sleep stages.

0064 Lateral Hypothalamic Control of REM Sleep Expression During Ambient Temperature Warming

Sleep and thermoregulation are tightly integrated. Moreover, ambient temperature (Ta) warming preferentially increases REM sleep over NREM sleep across species. Although the role of the anterior hypothalamus in thermoregulation and NREM sleep expression are well documented, the hypothalamic control of REM sleep during ambient temperature manipulation remains to be determined. We examined the role of the posterior lateral hypothalamus (LH) melanin concentrating hormone (MCH) system in the modulation of REM sleep during Ta manipulation. Genetically engineered MCH-R1-knockout (KO) mice or MCH::cre mice implanted with cortical EEG and neck EMG electrodes were used for these experiments. Mice were housed at 23.0 ± 1.0°C in their home cages in a temperature-controlled cabinet. During the light period at two hour intervals, four bouts of rapid Ta warming to a maximum of 31.7°C were achieved for 30 minutes with a thermostatically controlled combination of convection heater and indirect infrared lamp. To optogenetically stimulate MCH neurons, we stereotactically injected AAV2-ChR2-eYFP or AAV2-eYFP (controls) in the LH of MCH::Cre mice. In wild type (WT) controls, REM sleep was significantly increased in the warm (27.5–31°C) versus cool (24.0–27.5˚C) condition. However, MCH-R1-KO mice showed no significant changes in REM sleep as a function of Ta. Random semi-chronic optical activation of MCH neurons significantly increased NREM-to-REM sleep transitions, and prolonged REM sleep durations compared to YFP controls, but did not affect NREM sleep. Additional Ta warming had an additive effect on increasing REM sleep, demonstrating that optical stimulation of MCH neurons in combination with Ta warming was able to “over-drive” the expression of REM sleep beyond what optical stimulation or Ta warming alone could achieve. Indeed, optical stimulation had the same effect on increasing REM sleep expression as Ta warming in the YFP control mice. These data support a key role for the MCH system in the output expression of REM sleep during Ta manipulation, and show that concomitant MCH activation with Ta warming can over-express this effect. Ohio Sleep Medicine and Neuroscience Institute, Inselspital Bern University Hospital.

Automated EEG sleep staging in the term-age baby using a generative modelling approach

Objective. We develop a method for automated four-state sleep classification of preterm and term-born babies at term-age of 38–40 weeks postmenstrual age (the age since the last menstrual cycle of the mother) using multichannel electroencephalogram (EEG) recordings. At this critical age, EEG differentiates from broader quiet sleep (QS) and active sleep (AS) stages to four, more complex states, and the quality and timing of this differentiation is indicative of the level of brain development. However, existing methods for automated sleep classification remain focussed only on QS and AS sleep classification. Approach. EEG features were calculated from 16 EEG recordings, in 30 s epochs, and personalized feature scaling used to correct for some of the inter-recording variability, by standardizing each recording’s feature data using its mean and standard deviation. Hidden Markov models (HMMs) and Gaussian mixture models (GMMs) were trained, with the HMM incorporating knowledge of the sleep state transition probabilities. Performance of the GMM and HMM (with and without scaling) were compared, and Cohen’s kappa agreement calculated between the estimates and clinicians’ visual labels. Main results. For four-state classification, the HMM proved superior to the GMM. With the inclusion of personalized feature scaling, mean kappa (±standard deviation) was 0.62 (±0.16) compared to the GMM value of 0.55 (±0.15). Without feature scaling, kappas for the HMM and GMM dropped to 0.56 (±0.18) and 0.51 (±0.15), respectively. Significance. This is the first study to present a successful method for the automated staging of four states in term-age sleep using multichannel EEG. Results suggested a benefit in incorporating transition information using an HMM, and correcting for inter-recording variability through personalized feature scaling. Determining the timing and quality of these states are indicative of developmental delays in both preterm and term-born babies that may lead to learning problems by school age.

Efficacy of a mandibular advancement intraoral appliance (MOA) for the treatment of obstructive sleep apnea syndrome (OSAS) in pediatric patients: A pilot-study.

BackgroundTo evaluate the treatment efficacy of a mandibular advancement intraoral appliance (MOA) for treatment of obstructive sleep apnea syndrome (OSAS) in pediatric patients.Material and MethodsEighteen patients (mean=8.39 years old, women=44.4%) were selected. Sleep disorders, sleep bruxism, and temporomandibular disorders were assessed by the Sleep Disturbance Scale for Children (SDSC), the BiteStrip® (portable SB device), and the Research Diagnostic Criteria for Temporomandibular Disorders, respectively. The clinical diagnosis of OSAS was confirmed with a type 3 portable monitor device (ApneaLinkTM Plus). A silicon-based material MOA was used by patients for 60 days, and the results were compared to baseline.ResultsThe median RDI was significantly reduced from 10 to 4.5 events/hour. Nadir SpO2 significantly increased from 82.6% to 88.9%. Total snoring events/hour have also significantly decreased from 205.5 to 91.5. Signs and symptoms of TMD remained unaltered. There was also a reduction from moderate to absence of SB in 12 patients. Similarly, all variables measured by the SDSC have had very significant reductions: disorders of initiating and maintaining sleep, sleep disordered breathing, disorders of arousal, nightmares, sleep wake transition disorders, disorders of excessive somnolence, and sleep hyperhidrosis.ConclusionsIn selected cases, OA maybe considered as an alternative for the OSAS treatment. Key words:Snoring appliances, sleep apnea, bruxism, sleep disorders, children

Evolution of macrosleep in the acute and subacute phase after stroke

Introduction: A restorative sleep is essential for physical and psychological health. Even though literature is highly heterogeneous, stroke patients mostly tend to have a lower sleep efficiency, reduced N2, N3 and REM sleep, and generally a more fragmented sleep, especially in the acute phase. Crucially, there might be an association between an impaired sleep architecture and impaired cognitive outcome. As such, a poor sleep efficiency, a low amount of N2 and N3 and enhanced wakefulness after sleep onset have been linked to an acute impaired outcome. However, the specific role of macrosleep variations for the long-term recovery is still unknown. Therefore, we aim at observing the evolution of sleep macrostructure at several time points after stroke and relating them to the long-term clinical outcome. We will further apply transitional sleep scoring which might allow a more profound insight into sleep stability. Materials and methods: We have measured so far 8 adult stroke patients (6 m, 2f; age±SEM 50.7±4.0 years; range: 27–60; 5 hemispheric, 2 bithalamic, 1 cerebellar) in the acute (day range: 3–17) and 4 of those patients in the subacute phase (day range: 72–120). We applied high-density EEG during a full night of sleep, and investigated the cognitive outcome by neuropsychological examination. We relate our data also to 2 healthy not-yet age-matched controls (31±2.1 years), having spent one night at the hospital. The transitional sleep scoring method classifies the sleep recording epoch- and time-independently, thereby allowing for a detailed and continuous scoring of sleep stages and transitions throughout the night. Results: Our very preliminary analysis shows that in the acute phase, stroke patients, as compared to controls, descriptively tend to sleep less (values expressed as means±SEM; 64.3%3.9 vs. 75.3%±6.5), to be more awake (35.7%±3.9 vs. 24.7%±6.5), to have less N3 (10.6%±1.8 vs. 23.4%±0.5) and presumably less REM sleep (12.1%±2.2 vs. 16.6%±3.8). Patients might exhibit more sleep transitions than controls (211.6±20.7 vs. 157±38.2). In the subacute phase, patients sleep shows non-significant improvements (70.2%±35.1 sleep efficiency, 19.1%±9.5 of N3, 13.9%±6.9 of REM sleep). The classical sleep scoring captured less transitions (211.6±20.7) as compared to the transitional scoring (338.4±42.4) in the acute phase, while the percentage of sleep stayed almost similar (64.3%3.9 vs. 69.8%±3.6). Conclusions: In line with current literature, our preliminary results seem to support the evidence that stroke patients may display variations in macrosleep, especially in the acute phase, having a lower sleep efficiency, less N3 and less REM sleep. Our data also show that all-night high-density EEG recordings are feasible in this hospital setting. Furthermore, transitional scoring may provide a more profound insight into sleep stability. Acknowledgements: This study was funded by the SNF Sinergia Grant (Project number: 160803).

Cellular and Molecular Mechanisms of REM Sleep Homeostatic Drive: A Plausible Component for Behavioral Plasticity.

Homeostatic regulation of REM sleep drive, as measured by an increase in the number of REM sleep transitions, plays a key role in neuronal and behavioral plasticity (i.e., learning and memory). Deficits in REM sleep homeostatic drive (RSHD) are implicated in the development of many neuropsychiatric disorders. Yet, the cellular and molecular mechanisms underlying this RSHD remain to be incomplete. To further our understanding of this mechanism, the current study was performed on freely moving rats to test a hypothesis that a positive interaction between extracellular-signal-regulated kinase 1 and 2 (ERK1/2) activity and brain-derived neurotrophic factor (BDNF) signaling in the pedunculopontine tegmentum (PPT) is a causal factor for the development of RSHD. Behavioral results of this study demonstrated that a short period (<90 min) of selective REM sleep restriction (RSR) exhibited a strong RSHD. Molecular analyses revealed that this increased RSHD increased phosphorylation and activation of ERK1/2 and BDNF expression in the PPT. Additionally, pharmacological results demonstrated that the application of the ERK1/2 activation inhibitor U0126 into the PPT prevented RSHD and suppressed BDNF expression in the PPT. These results, for the first time, suggest that the positive interaction between ERK1/2 and BDNF in the PPT is a casual factor for the development of RSHD. These findings provide a novel direction in understanding how RSHD-associated specific molecular changes can facilitate neuronal plasticity and memory processing.

Transitions in sleep problems from late adolescence to young adulthood: A longitudinal analysis of the effects of peer victimization.

Adolescence is a developmental period with high vulnerability to sleep problems. However, research identifying distinct patterns and underlying determinants of sleep problems is scarce. This study investigated discrete subgroups of, changes in, and stability of sleep problems. We also examined whether peer victimization influenced sleep problem subgroups and transitions in patterns of sleep problems from late adolescence to young adulthood. Sex differences in the effects of peer victimization were also explored. In total, 1,455 male and 1,399 female adolescents from northern Taiwan participated in this longitudinal study. Latent transition analysis was used to examine changes in patterns of sleep problems and the effects of peer victimization on these changes. We identified three subgroups of sleep problems in males and two in females, and found that there was a certain level of instability in patterns of sleep problems during the study period. For both sexes, those with greater increases in peer victimization over time were more likely to change from being a good sleeper to a poor sleeper. The effects of peer victimization on baseline status of sleep problems, however, was only significant for males, with those exposed to higher levels of peer victimization more likely to be poor sleepers at baseline. Our findings reveal an important role of peer victimization in predicting transitions in patterns of sleep problems. Intervention programs aimed at decreasing peer victimization may help reduce the development and escalation of sleep problems among adolescents, especially in males.

Targeted disruption of supraspinal motor circuitry reveals a distributed network underlying Restless Legs Syndrome (RLS)-like movements in the rat

In this study we uncovered, through targeted ablation, a potential role for corticospinal, cerebello-rubro-spinal, and hypothalamic A11 dopaminergic systems in the development of restless legs syndrome (RLS)-like movements during sleep. Targeted lesions in select basal ganglia (BG) structures also revealed a major role for nigrostriatal dopamine, the striatum, and the external globus pallidus (GPe) in regulating RLS-like movements, in particular pallidocortical projections from the GPe to the motor cortex. We further showed that pramipexiole, a dopamine agonist used to treat human RLS, reduced RLS-like movements. Taken together, our data show that BG-cortico-spinal, cerebello-rubro-spinal and A11 descending projections all contribute to the suppression of motor activity during sleep and sleep-wake transitions, and that disruption of these circuit nodes produces RLS-like movements. Taken together with findings from recent genomic studies in humans, our findings provide additional support for the concept that the anatomic and genetic etiological bases of RLS are diverse.

0768 BAYESIAN NETWORK MODELING OF DAYTIME AND NIGHTTIME SLEEP ARCHITECTURE

The complex pattern of sleep stages over a night (sleep architecture) exhibits abnormal patterns in disorders such as apnea and depression. Quantifying variability in sleep architecture caused by benign versus harmful factors may provide a powerful diagnostic tool. Current measures of sleep architecture, such as stage proportions, fail to capture the dynamics of human sleep stage transitions. Here, we investigate the effect of individual (age, sex, BMI) and previous sleep factors (time of day, time spent in a stage) on alternate measures of sleep architecture: transition probabilities (the likelihood of transition from one state to another) and stage duration distributions. We fit various discrete Bayesian networks to large amounts of sleep data (>9000 nights/naps) to determine the relational structure between variables. We find, in accordance with the literature, that sex, age, but not BMI significantly influence sleep stage durations. Specifically, older men have shorter bouts (more fragmentation) of REM sleep (11% more bouts < 6 minutes) and Slow Wave Sleep (2% more bouts < 6 mins) compared to older women. Older males and females had more fragmented sleep across all stages, although this pattern was stronger for males (older vs younger females = 3%, older vs younger males = 5% more < 6 minutes). Interestingly, transition probabilities are unaffected by sex, age, and BMI. Additionally, we find that the identity of the next stage is dependent on only the last two states. These findings demonstrate low complexity in sleep stage transitions, which can be useful for future work on a higher resolution continuous Bayesian network capable of predicting sleep stage sequences. Future work will also use Bayesian network modeling to characterize differences between healthy and unhealthy sleep architecture patterns.