A model of Ponto-Geniculo-Occipital waves supports bidirectional control of cortical plasticity across sleep-stages

During sleep, cortical network connectivity likely undergoes both synaptic potentiation and depression through system consolidation and homeostatic processes. However, how these modifications are coordinated across sleep stages remains largely unknown. Candidate mechanisms are Ponto-Geniculo-Occipital (PGO) waves, propagating across several structures during Rapid Eye Movement (REM) sleep and the transitional stage from non-REM sleep to REM sleep (pre-REM), and exhibiting sleep stage-specific dynamic patterns. To understand their impact on cortical plasticity, we built an acetylcholine-modulated neural mass model of PGO wave propagation through pons, thalamus and cortex, reproducing a broad range of electrophysiological characteristics across sleep stages. Using a population model of Spike-Time-Dependent Plasticity, we show that recurrent cortical circuits in different transient regimes depending on the sleep stage with different impacts on plasticity. Specifically, this leads to the potentiation of cortico-cortical synapses during pre-REM, and to their depression during REM sleep. Overall, our results provide a new view on how transient sleep events and their associated sleep stage may implement a precise control of system-wide plastic changes.

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Sleep, Subcortical Stimulation and Kindling in the Cat

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/s031716710002059x ◽

1975 ◽

Vol 2 (4) ◽

pp. 447-455 ◽

Cited By ~ 32

Author(s):

T. Tanaka ◽

H. Lange ◽

R. Naquet

Keyword(s):

Rem Sleep ◽

Sleep Stage ◽

Low Frequency ◽

Mesencephalic Reticular Formation ◽

Seizure Threshold ◽

Sleep Stages ◽

Central Gray Matter ◽

Spike Discharge ◽

Amygdaloid Stimulation ◽

Stimulation Of

SUMMARY:A longitudinal study of the effects of sleep on amygdaloid kindling showed that kindling disrupted normal sleep patterns by reducing REM sleep and increasing awake time. Few interictal spike discharges were observed during the awake stage, while a marked increase in discharge was observed during the light and deep sleep stages. No discharges were observed during REM sleep. During the immediate post-stimulation period the nonstimulated amygdala showed a much higher rate of spike discharge. On the other hand, there was an increase in spike discharge in the stimulated amygdala during natural sleep without preceding amygdaloid stimulation. Amygdaloid stimulation at the generalized seizure threshold during each sleep stage resulted in a generalized convulsion.The influence of subcortical electrical stimulation on kindled amygdaloid convulsions was investigated in a second experiment. Stimulation of the centre median and the caudate nucleus was without effect on kindled convulsions, while stimulation of the mesencephalic reticular formation at high frequency (300 Hz) reduced the latency of onset of kindled generalized convulsions. Stimulation of the nucleus ventralis lateralis of the thalamus at low frequency (10 Hz) prolonged the convulsion latency, and at high current levels blocked the induced convulsion. Stimulation in the central gray matter at low frequency (10 Hz) also blocked kindled amygdaloid convulsions.

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1193 Accuracy of a Commercial Wearable in Detecting Sleep Stages Compared to Polysomnography in Adults: Considering Sleep Classification Methods and Effects of Evening Alcohol Consumption

SLEEP ◽

10.1093/sleep/zsaa056.1187 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A456-A457 ◽

Cited By ~ 1

Author(s):

L Menghini ◽

V Alschuler ◽

S Claudatos ◽

A Goldstone ◽

F Baker ◽

...

Keyword(s):

Alcohol Consumption ◽

Rem Sleep ◽

Sleep Stage ◽

Cardiac Activity ◽

Sleep Stages ◽

Classification Methods ◽

Management Platform ◽

Wake Patterns ◽

Wake Detection ◽

Data Management Platform

Abstract Introduction Commercial wearable devices have shown the capability of collecting and processing multisensor information (motion, cardiac activity), claiming to be able to measure sleep-wake patterns and differentiate sleep stages. While using these devices, users should be aware of their accuracy, sources of measurement error and contextual factors that may affect their performance. Here, we evaluated the agreement between Fitbit Charge 2™ and PSG in adults, considering effects of two different sleep classification methods and pre-sleep alcohol consumption. Methods Laboratory-based synchronized recordings of device and PSG data were obtained from 14 healthy adults (42.6±9.7y; 6 women), who slept between one and three nights in the lab, for a total of 27 nights of data. On 10 of these nights, participants consumed alcohol (up to 4 standard drinks) in the 2 hours before bedtime. Device performance relative to PSG was evaluated using epoch-by-epoch and Bland-Altman analyses, with device data obtained from a data-management platform, Fitabase, via two methods one that accounts for short wakes (SW, awakenings that last less than 180s) and one that does not (not-SW). Results SW and not-SW methods were similar in scoring (96.76% agreement across epochs), although the SW method had better accuracy for differentiating “light”, “deep”, and REM sleep; but produced more false positives in wake detection. The device (SW-method) classified epochs of wake, “light” (N1+N2), “deep” (N3) and REM sleep with 56%, 77%, 46%, and 62% sensitivity, respectively. Bland-Altman analysis showed that the device significantly underestimated “light” (~19min) and “deep” (~26min) sleep. Alcohol consumption enhanced PSG-device discrepancies, in particular for REM sleep (p=0.01). Conclusion Our results indicate promising accuracy in sleep-wake and sleep stage identification for this device, particularly when accounting for short wakes, as compared to PSG. Alcohol consumption, as well as other potential confounders that could affect measurement accuracy should be further investigated. Support This study was supported by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) grant R21-AA024841 (IMC and MdZ). The content is solely the responsibility of the authors and does not necessarily represent the official views the National Institutes of Health.

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Why Are Seizures Rare in Rapid Eye Movement Sleep? Review of the Frequency of Seizures in Different Sleep Stages

Epilepsy Research and Treatment ◽

10.1155/2013/932790 ◽

2013 ◽

Vol 2013 ◽

pp. 1-10 ◽

Cited By ~ 22

Author(s):

Marcus Ng ◽

Milena Pavlova

Keyword(s):

Eye Movement ◽

Rem Sleep ◽

Low Voltage ◽

Sleep Stage ◽

Sleep Stages ◽

Seizure Freedom ◽

Rapid Eye Movement ◽

Focal Seizures ◽

Generalized Seizures ◽

Interictal Discharges

Since the formal characterization of sleep stages, there have been reports that seizures may preferentially occur in certain phases of sleep. Through ascending cholinergic connections from the brainstem, rapid eye movement (REM) sleep is physiologically characterized by low voltage fast activity on the electroencephalogram, REMs, and muscle atonia. Multiple independent studies confirm that, in REM sleep, there is a strikingly low proportion of seizures (~1% or less). We review a total of 42 distinct conventional and intracranial studies in the literature which comprised a net of 1458 patients. Indexed to duration, we found that REM sleep was the most protective stage of sleep against focal seizures, generalized seizures, focal interictal discharges, and two particular epilepsy syndromes. REM sleep had an additional protective effect compared to wakefulness with an average 7.83 times fewer focal seizures, 3.25 times fewer generalized seizures, and 1.11 times fewer focal interictal discharges. In further studies REM sleep has also demonstrated utility in localizing epileptogenic foci with potential translation into postsurgical seizure freedom. Based on emerging connectivity data in sleep, we hypothesize that the influence of REM sleep on seizures is due to a desynchronized EEG pattern which reflects important connectivity differences unique to this sleep stage.

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Modulation of the ultradian human nasal cycle by sleep stage and body position

Arquivos de Neuro-Psiquiatria ◽

10.1590/0004-282x20160178 ◽

2017 ◽

Vol 75 (1) ◽

pp. 9-14 ◽

Cited By ~ 1

Author(s):

Richard E. Frye ◽

Deborah F. Rosin ◽

Adrian R. Morrison ◽

Fidias E. Leon-Sarmiento ◽

Richard L. Doty

Keyword(s):

Rem Sleep ◽

Sleep Stage ◽

Body Position ◽

Video Camera ◽

Sleep Stages ◽

Nasal Airflow ◽

Somatosensory Stimulation ◽

Nasal Cycle ◽

Left And Right ◽

The Right

ABSTRACT Objective: The nasal cycle, which is present in a significant number of people, is an ultradian side-to-side rhythm of nasal engorgement associated with cyclic autonomic activity. We studied the nasal cycle during REM/non-REM sleep stages and examined the potentially confounding influence of body position on lateralized nasal airflow. Methods: Left- and right-side nasal airflow was measured in six subjects during an eight-hour sleep period using nasal thermistors. Polysomnography was performed. Simultaneously, body positions were monitored using a video camera in conjunction with infrared lighting. Results: Significantly greater airflow occurred through the right nasal chamber (relative to the left) during periods of REM sleep than during periods of non-REM sleep (p<0.001). Both body position (p < 0.001) and sleep stage (p < 0.001) influenced nasal airflow lateralization. Conclusions: This study demonstrates that the lateralization of nasal airflow and sleep stage are related. Some types of asymmetrical somatosensory stimulation can alter this relationship.

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Impact of sound stimulation during different sleep stages in patients with tinnitus

Loquens ◽

10.3989/loquens.2018.053 ◽

2019 ◽

Vol 5 (2) ◽

pp. 053

Author(s):

Marisa Pedemonte ◽

Marcela Díaz ◽

Eduardo Medina-Ferret ◽

Martín Testa

Keyword(s):

Rem Sleep ◽

Auditory Processing ◽

Therapeutic Strategy ◽

Sleep Stage ◽

Sleep Stages ◽

Auditory Information ◽

Sound Stimulation ◽

Paired Student ◽

Before And After

It is known that auditory information is continuously processed both during wakefulness and sleep. Consistently, it has been shown that sound stimulation mimicking tinnitus during sleep decreases the intensity of tinnitus and improves the patients’ quality of life. The mechanisms underlying this effect are not known. To begin to address this question, eleven patients suffering from tinnitus were stimulated with sound mimicking tinnitus at different sleep stages; 4 were stimulated in N2, 4 in stage N3 (slow waves sleep) and 3 in REM sleep (stage with Rapid Eyes Movements). Patients’ sleep stage was monitored through polysomnography, for sound stimulation application. Tinnitus level reported by subjects were compared the days before and after stimulation and statistically analyzed (paired Student t test). All patients stimulated at stage N2 reported significantly lower tinnitus intensity the day after stimulation, while none stimulated during stage N3 and only one out of three stimulated during REM sleep showed changes. These results are consistent with studies showing that sound stimulation during N2 (sleep stage with spindles) changes power spectrum and coherence of electroencephalographic signals, and suggest that the N2 sleep stage is a critical period for reducing tinnitus intensity using this therapeutic strategy, during which auditory processing networks are more malleable by sound stimulation.

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0746 Dynamics of Sleep Stage Transitions in Patients with Narcolepsy and Other Hypersomnias

SLEEP ◽

10.1093/sleep/zsaa056.742 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A283-A284

Author(s):

A Kishi ◽

T Kitajima ◽

R Kawai ◽

M Hirose ◽

N Iwata ◽

...

Keyword(s):

Rem Sleep ◽

Transition Probabilities ◽

Sleep Stage ◽

Sleep Onset ◽

Sleep Stages ◽

Subsequent Stage ◽

Dynamic Features ◽

Survival Curves ◽

Transition Analysis ◽

Sleep Transition

Abstract Introduction Narcolepsy is a chronic sleep disorder characterized by excessive daytime sleepiness and abnormal REM sleep phenomena. Narcolepsy can be distinguished into type 1 (NT1; with cataplexy) and type 2 (NT2; without cataplexy). It has been reported that sleep stage sequences at sleep-onset as well as sleep-wake dynamics across the night may be useful in the differential diagnosis of hypersomnia. Here we studied dynamic features of sleep stage transitions during whole night sleep in patients with NT1, NT2, and other types of hypersomnia (o-HS). Methods Twenty patients with NT1, 14 patients with NT2, and 35 patients with o-HS underwent overnight PSG. Transition probabilities between sleep stages (wake, N1, N2, N3, and REM) and survival curves of continuous runs of each sleep stage were compared between groups. Transition-specific survival curves of continuous runs of each sleep stage, dependent on the subsequent stage of the transition, were also compared. Results The probability of transitions from N1-to-wake was significantly greater in NT1 than in NT2 and o-HS while that from N1-to-N2 was significantly smaller in NT1 than in NT2 and o-HS. The probability of transitions from N2-to-REM was significantly smaller in NT1 than in o-HS. Wake and N1 were significantly more continuous in NT1 than in NT2; specifically, N1 followed by N2 was significantly more continuous in NT1 than in NT2 and o-HS. N2 was significantly less continuous in NT1 and NT2 than in o-HS; this was specifically confirmed for N2 followed by N1/wake. REM sleep was significantly less continuous in NT1 than in NT2 and o-HS; specifically, REM sleep followed by wake was significantly less continuous in NT1 than in o-HS. Continuity of N3 did not differ significantly between groups. Conclusion Dynamics of sleep stage transitions differed between NT1, NT2, and o-HS. Dynamic features of sleep such as sleep instability, persistency of wake/N1, and REM fragmentation may differentiate NT1 from NT2, while N2 continuity may differentiate narcolepsy from o-HS. The results suggest that sleep transition analysis may be of clinical utility and provide insights into the underlying pathophysiology of hypersomnia and narcolepsy. Support JSPS KAKENHI (18K17891 to AK).

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Sleep Stage Transitions in Healthy Humans Altered by Central Monoaminergic Antagonist

Methods of Information in Medicine ◽

10.3414/me09-02-0032 ◽

2010 ◽

Vol 49 (05) ◽

pp. 458-461 ◽

Cited By ~ 4

Author(s):

A. Kishi ◽

H. Yasuda ◽

T. Matsumoto ◽

Y. Inami ◽

J. Horiguchi ◽

...

Keyword(s):

Rem Sleep ◽

Transition Probabilities ◽

Sleep Stage ◽

Young Male ◽

Stage Ii ◽

Stage Iii ◽

Sleep Stages ◽

Healthy Humans ◽

Sleep Rhythms ◽

Dynamical Aspect

Summary Objectives: Sleep stage transitions constitute one of the key components of the dynamical aspect of sleep. However, neural mechanisms of sleep stage transitions have not, to date, been fully elucidated. We investigate the effects of administrating risperi-done, a central serotonergic and dopaminergic antagonist, on sleep stage transitions inhumans, and also on ultradian rapid-eye-movement (REM) sleep rhythms. Methods: Ten healthy young male volunteers (age: 22 ± 3.7 years) participated in this study. The subjects spent three nights in a sleep laboratory. The first was the adaptation night, and the second was the baseline night. On the third night, the subjects received risperidone (1 mg tablet) 30 min before the polysomnography recording. We measured and investigated transition probabilities between waking, REM and non-REM (stages I–IV) sleep stages. Results: We found that the probability of transition from stage II to stage III was significantly greater for the risperidone night than for the baseline night. We also found that risperidone administration prolonged REM-onset intervals, when compared to the baseline night. Conclusions: We demonstrate that central serotonergic and /or dopaminergic neural transmissions are involved in the regulation of sleep stage transitions from light (stage II) to deep (stage III) sleep, and also in determining ultradian REM sleep rhythms.

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Development of Automated Sleep Stage Classification System Using Multivariate Projection-Based Fixed Boundary Empirical Wavelet Transform and Entropy Features Extracted from Multichannel EEG Signals

Entropy ◽

10.3390/e22101141 ◽

2020 ◽

Vol 22 (10) ◽

pp. 1141

Author(s):

Rajesh Kumar Tripathy ◽

Samit Kumar Ghosh ◽

Pranjali Gajbhiye ◽

U. Rajendra Acharya

Keyword(s):

Wavelet Transform ◽

Rem Sleep ◽

Sleep Stage ◽

Sleep Stages ◽

Theoretic Approach ◽

Eeg Signals ◽

Fixed Boundary ◽

Empirical Wavelet Transform ◽

Sleep Stage Classification ◽

Information Theoretic Approach

The categorization of sleep stages helps to diagnose different sleep-related ailments. In this paper, an entropy-based information–theoretic approach is introduced for the automated categorization of sleep stages using multi-channel electroencephalogram (EEG) signals. This approach comprises of three stages. First, the decomposition of multi-channel EEG signals into sub-band signals or modes is performed using a novel multivariate projection-based fixed boundary empirical wavelet transform (MPFBEWT) filter bank. Second, entropy features such as bubble and dispersion entropies are computed from the modes of multi-channel EEG signals. Third, a hybrid learning classifier based on class-specific residuals using sparse representation and distances from nearest neighbors is used to categorize sleep stages automatically using entropy-based features computed from MPFBEWT domain modes of multi-channel EEG signals. The proposed approach is evaluated using the multi-channel EEG signals obtained from the cyclic alternating pattern (CAP) sleep database. Our results reveal that the proposed sleep staging approach has obtained accuracies of 91.77%, 88.14%, 80.13%, and 73.88% for the automated categorization of wake vs. sleep, wake vs. rapid eye movement (REM) vs. Non-REM, wake vs. light sleep vs. deep sleep vs. REM sleep, and wake vs. S1-sleep vs. S2-sleep vs. S3-sleep vs. REM sleep schemes, respectively. The developed method has obtained the highest overall accuracy compared to the state-of-art approaches and is ready to be tested with more subjects before clinical application.

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Dynamics of sleep stage transitions in healthy humans and patients with chronic fatigue syndrome

AJP Regulatory Integrative and Comparative Physiology ◽

10.1152/ajpregu.00925.2007 ◽

2008 ◽

Vol 294 (6) ◽

pp. R1980-R1987 ◽

Cited By ~ 38

Author(s):

Akifumi Kishi ◽

Zbigniew R. Struzik ◽

Benjamin H. Natelson ◽

Fumiharu Togo ◽

Yoshiharu Yamamoto

Keyword(s):

Chronic Fatigue Syndrome ◽

Power Law ◽

Rem Sleep ◽

Sleep Stage ◽

Chronic Fatigue ◽

Stage I ◽

Sleep Stages ◽

Deep Sleep ◽

Healthy Humans ◽

Fatigue Syndrome

Physiological and/or pathological implications of the dynamics of sleep stage transitions have not, to date, been investigated. We report detailed duration and transition statistics between sleep stages in healthy subjects and in others with chronic fatigue syndrome (CFS); in addition, we also compare our data with previously published results for rats. Twenty-two healthy females and 22 female patients with CFS, characterized by complaints of unrefreshing sleep, underwent one night of polysomnographic recording. We find that duration of deep sleep (stages III and IV) follows a power-law probability distribution function; in contrast, stage II sleep durations follow a stretched exponential and stage I, and REM sleep durations follow an exponential function. These stage duration distributions show a gradually increasing departure from the exponential form with increasing depth of sleep toward a power-law type distribution for deep sleep, suggesting increasing complexity of regulation of deeper sleep stages. We also find a substantial number of REM to non-REM sleep transitions in humans, while this transition is reported to be virtually nonexistent in rats. The relative frequency of this REM to non-REM sleep transition is significantly lower in CFS patients than in controls, resulting in a significantly greater relative transition frequency of moving from both REM and stage I sleep to awake. Such an alteration in the transition pattern suggests that the normal continuation of sleep in light or REM sleep is disrupted in CFS. We conclude that dynamic transition analysis of sleep stages is useful for elucidating yet-to-be-determined human sleep regulation mechanisms with pathophysiological implications.

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Two Types of Insomnia: Too Much Waking or Not Enough Sleep

The British Journal of Psychiatry ◽

10.1192/bjp.126.5.439 ◽

1975 ◽

Vol 126 (5) ◽

pp. 439-445 ◽

Cited By ~ 18

Author(s):

Vlasta Brezinová ◽

Ian Oswald ◽

John Loudon

Keyword(s):

Rem Sleep ◽

Drug Withdrawal ◽

Sleep Stage ◽

Sleep Stages ◽

Hypnotic Drug ◽

Episode Duration ◽

Significant Change ◽

The Stability

SummaryThe stability of sleep was examined in two kinds of induced insomnia, namely after caffeine administration and after hypnotic drug withdrawal. The duration of each episode of any one sleep stage or any episode of intervening wakefulness plus drowsiness was determined.After caffeine mere was an increase in longer episodes of intervening wakefulness plus drowsiness, but no significant change in the episode duration of any of the sleep stages. In the case of drug withdrawal there was no change in the episode duration of intervening wakefulness plus drowsiness, but there was a significant shortening of episode duration in sleep stages 2 and 3 +4, with a similar trend for REM sleep episodes.Caffeine ‘insomnia’ thus seems characterized by increased stability of wakefulness, and hypnotic withdrawal ‘insomnia’ by decreased stability of sleep. The type of analysis undertaken in this study could increase understanding of other types of insomnia.

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