scholarly journals EEG connectivity across sleep cycles and age

SLEEP ◽  
2019 ◽  
Author(s):  
Maude Bouchard ◽  
Jean-Marc Lina ◽  
Pierre-Olivier Gaudreault ◽  
Jonathan Dubé ◽  
Nadia Gosselin ◽  
...  
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Verbal Memory ◽  
Sleep Cycle ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Older Individuals ◽  
Age Related ◽  
Eeg Connectivity ◽  
Sleep Cycles

Abstract Study Objectives In young adults, sleep is associated with important changes in cerebral connectivity during the first cycle of non-rapid eye movement (NREM) sleep. Our study aimed to evaluate how electroencephalography (EEG) connectivity during sleep differs between young and older individuals, and across the sleep cycles. Methods We used imaginary coherence to estimate EEG connectivity during NREM and rapid eye movement (REM) sleep in 30 young (14 women; 20–30 years) and 29 older (18 women; 50–70 years) individuals. We also explored the association between coherence and cognitive measures. Results Older individuals showed lower EEG connectivity in stage N2 but higher connectivity in REM and stage N3 compared to the younger cohort. Age-related differences in N3 were driven by the first sleep cycle. EEG connectivity was lower in REM than N3, especially in younger individuals. Exploratory analyses, controlling for the effects of age, indicated that higher EEG connectivity in delta during N2 was associated with higher processing speed, whereas, during REM sleep, lower EEG connectivity in delta and sigma was associated with higher verbal memory performance and a higher global averaged intelligence quotient score. Conclusion Our results indicated that age modifies sleep EEG connectivity but the direction and the magnitude of these effects differ between sleep stages and cycles. Results in N3 and REM point to a reduced ability of the older brains to disconnect as compared to the younger ones. Our results also support the notion that cerebral functional connectivity during sleep may be associated with cognitive functions.

Abstract P417: Relationship Between Blood Pressure Variability and Sleep Architecture

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Xiaoyue Liu ◽  
Jeongok G Logan ◽  
Younghoon Kwon ◽  
Jennifer Lobo ◽  
Hyojung Kang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Time ◽  
Sleep Architecture ◽  
Sleep Stages ◽  
Apnea Hypopnea Index ◽  
Rapid Eye Movement ◽  
Sleep Studies ◽  
The Relationship

Introduction: Blood pressure (BP) variability (BPV) is a novel marker for cardiovascular disease (CVD) independent of high BP. Sleep architecture represents the structured pattern of sleep stages consisting of rapid eye movement (REM) and non-rapid eye movement (NREM), and it is an important element in the homeostatic regulation of sleep. Currently, little is known regarding whether BPV is linked to sleep stages. Our study aimed to examine the relationship between sleep architecture and BPV. Methods: We analyzed in-lab polysomnographic studies collected from individuals who underwent diagnostic sleep studies at a university hospital from 2010 to 2017. BP measures obtained during one year prior to the sleep studies were included. BPV was computed using the coefficient of variation for all individuals who had three or more systolic and diastolic BP data. We conducted linear regression analysis to assess the relationship of systolic BPV (SBPV) and diastolic BPV (DBPV) with the sleep stage distribution (REM and NREM sleep time), respectively. Covariates that can potentially confound the relationships were adjusted in the models, including age, sex, race/ethnicity, body mass index, total sleep time, apnea-hypopnea index, mean BP, and history of medication use (antipsychotics, antidepressants, and antihypertensives) during the past two years before the sleep studies. Results: Our sample (N=3,565; male = 1,353) was racially and ethnically diverse, with a mean age 54 ± 15 years and a mean BP of 131/76 ± 13.9/8.4 mmHg. Among the sleep architecture measures examined, SBPV showed an inverse relationship with REM sleep time after controlling for all covariates ( p = .033). We subsequently categorized SBPV into four quartiles and found that the 3 rd quartile (mean SBP SD = 14.9 ± 2.1 mmHg) had 3.3 fewer minutes in REM sleep compared to the 1 st quartile ( p = .02). However, we did not observe any relationship between DBPV and sleep architecture. Conclusion: Greater SBPV was associated with lower REM sleep time. This finding suggests a possible interplay between BPV and sleep architecture. Future investigation is warranted to clarify the directionality, mechanism, and therapeutic implications.

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

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
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.

scholarly journals Regulation of REM Sleep by Inhibitory Neurons in the Dorsomedial Medulla

2020 ◽  
Author(s):  
Joseph A. Stucynski ◽  
Amanda L. Schott ◽  
Justin Baik ◽  
Shinjae Chung ◽  
Franz Weber
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Gabaergic Neurons ◽  
Inhibitory Neurons ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Brain Rhythms ◽  
Slow Activity ◽  
Raphé Nuclei

ABSTRACTThe two major stages of mammalian sleep – rapid eye movement sleep (REMs) and non-REM sleep (NREMs) – are characterized by distinct brain rhythms ranging from millisecond to minute-long (infraslow) oscillations. The mechanisms controlling transitions between sleep stages and how they are synchronized with infraslow rhythms remain poorly understood. Using opto- and chemogenetic manipulation, we show that GABAergic neurons in the dorsomedial medulla (dmM) promote the initiation and maintenance of REMs, in part through their projections to the dorsal and median raphe nuclei. Fiber photometry revealed that dmM GABAergic neurons are strongly activated during REMs. During NREMs, their activity fluctuated in close synchrony with infraslow oscillations in the spindle band of the electroencephalogram, and the phase of this rhythm modulated the latency of optogenetically induced REMs episodes. Thus, dmM inhibitory neurons powerfully promote REMs, and their slow activity fluctuations may coordinate transitions from NREMs to REMs with infraslow brain rhythms.

scholarly journals Contribution of REM sleep and N2 sleep spindles to procedural memory consolidation in Vipassana meditators and non-meditating controls.

2017 ◽  
Author(s):  
Elizaveta Solomonova ◽  
Simon Dubé ◽  
Cloé Blanchette-Carrière ◽  
Arnaud Samson-Richer ◽  
Michelle Carr ◽  
...  
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Memory Consolidation ◽  
Nrem Sleep ◽  
Procedural Memory ◽  
Sleep Stages ◽  
Sleep Spindles ◽  
Meditation Practice ◽  
Rapid Eye Movement ◽  
Vipassana Meditation

Study objectives: Rapid eye movement (REM) sleep, non-rapid eye movement (NREM) sleep, and sleep spindles are all implicated in the consolidation of procedural memories. The relative contributions of sleep stages and sleep spindles was previously shown to depend on individual differences in task processing. Experience with Vipassana meditation is one such individual difference that has not been investigated in relation to sleep. Vipassana meditation is a form of mental training that enhances proprioceptive and somatic awareness and alters attentional style. The goal was thus to examine a potential moderating role for Vipassana meditation experience on sleep-dependent procedural memory consolidation.Methods: Groups of Vipassana meditation practitioners (N=20) and matched meditation-naïve controls (N=20) slept for a single daytime nap in the laboratory. Before and after the nap they completed a procedural task on the Wii Fit balance platform.Results: Meditators performed slightly better on the task before the nap, but the two groups improved similarly after sleep. The groups showed different patterns of sleep-dependent procedural memory consolidation: in meditators task learning was negatively correlated with density of fast and positively correlated with density of slow occipital spindles, while in controls task improvement was associated with increases in REM sleep. Meditation practitioners had a lower density of sleep spindles, especially in occipital regions.Conclusions: Results suggest that neuroplastic changes associated with sustained meditation practice may alter overall sleep architecture and reorganize sleep-dependent patterns of memory consolidation. The lower density of spindles in meditators may mean that meditation practice compensates for some of the memory functions of sleep.

scholarly journals Don't count your chickens before they're hatched: Elaborative encoding in REM dreaming in face of the physiology of sleep stages

2013 ◽  
Vol 36 (6) ◽  
pp. 613-614
Author(s):  
Gaétane Deliens ◽  
Sophie Schwartz ◽  
Philippe Peigneux
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
De Novo ◽  
Nrem Sleep ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Hidden Patterns ◽  
Episodic Memories ◽  
Novel Associations

AbstractLlewellyn suggests that episodic memories undergo “elaborative encoding” during rapid eye movement (REM) dreams, generating novel associations between recent and remote memories that are then instantiated during non-REM (NREM) sleep. This hypothesis conflicts with our knowledge of the physiology of NREM and then REM sleep stages and their ordered succession. Moreover, associations during sleep might also involve the extraction of hidden patterns rather than de novo associations.

scholarly journals Validation of Fitbit Charge 2 Sleep and Heart Rate Estimates Against Polysomnographic Measures in Shift Workers: Naturalistic Study (Preprint)

2020 ◽  
Author(s):  
Benjamin Stucky ◽  
Ian Clark ◽  
Yasmine Azza ◽  
Walter Karlen ◽  
Peter Achermann ◽  
...  
Keyword(s):  
Heart Rate ◽  
Eye Movement ◽  
Shift Work ◽  
Rem Sleep ◽  
Sleep Onset ◽  
Data Access ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Limits Of Agreement ◽  
Shift Workers

BACKGROUND Multisensor fitness trackers offer the ability to longitudinally estimate sleep quality in a home environment with the potential to outperform traditional actigraphy. To benefit from these new tools for objectively assessing sleep for clinical and research purposes, multisensor wearable devices require careful validation against the gold standard of sleep polysomnography (PSG). Naturalistic studies favor validation. OBJECTIVE This study aims to validate the Fitbit Charge 2 against portable home PSG in a shift-work population composed of 59 first responder police officers and paramedics undergoing shift work. METHODS A reliable comparison between the two measurements was ensured through the data-driven alignment of a PSG and Fitbit time series that was recorded at night. Epoch-by-epoch analyses and Bland-Altman plots were used to assess sensitivity, specificity, accuracy, the Matthews correlation coefficient, bias, and limits of agreement. RESULTS Sleep onset and offset, total sleep time, and the durations of rapid eye movement (REM) sleep and non–rapid-eye movement sleep stages N1+N2 and N3 displayed unbiased estimates with nonnegligible limits of agreement. In contrast, the proprietary Fitbit algorithm overestimated REM sleep latency by 29.4 minutes and wakefulness after sleep onset (WASO) by 37.1 minutes. Epoch-by-epoch analyses indicated better specificity than sensitivity, with higher accuracies for WASO (0.82) and REM sleep (0.86) than those for N1+N2 (0.55) and N3 (0.78) sleep. Fitbit heart rate (HR) displayed a small underestimation of 0.9 beats per minute (bpm) and a limited capability to capture sudden HR changes because of the lower time resolution compared to that of PSG. The underestimation was smaller in N2, N3, and REM sleep (0.6-0.7 bpm) than in N1 sleep (1.2 bpm) and wakefulness (1.9 bpm), indicating a state-specific bias. Finally, Fitbit suggested a distribution of all sleep episode durations that was different from that derived from PSG and showed nonbiological discontinuities, indicating the potential limitations of the staging algorithm. CONCLUSIONS We conclude that by following careful data processing processes, the Fitbit Charge 2 can provide reasonably accurate mean values of sleep and HR estimates in shift workers under naturalistic conditions. Nevertheless, the generally wide limits of agreement hamper the precision of quantifying individual sleep episodes. The value of this consumer-grade multisensor wearable in terms of tackling clinical and research questions could be enhanced with open-source algorithms, raw data access, and the ability to blind participants to their own sleep data.

Altered heart rate variability during sleep in mild cognitive impairment

SLEEP ◽  
2020 ◽  
Author(s):  
Shawn D X Kong ◽  
Camilla M Hoyos ◽  
Craig L Phillips ◽  
Andrew C McKinnon ◽  
Pinghsiu Lin ◽  
...  
Keyword(s):  
Older Adults ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Eye Movement ◽  
Rem Sleep ◽  
Nrem Sleep ◽  
Sleep Stages ◽  
Rapid Eye Movement

Abstract Study Objectives Cardiovascular autonomic dysfunction, as measured by short-term diurnal heart rate variability (HRV), has been reported in older adults with mild cognitive impairment (MCI). However, it is unclear whether this impairment also exists during sleep in this group. We, therefore, compared overnight HRV during sleep in older adults with MCI and those with subjective cognitive impairment (SCI). Methods Older adults (n = 210) underwent overnight polysomnography. Eligible participants were characterized as multi-domain MCI or SCI. The multi-domain MCI group was comprised of amnestic and non-amnestic subtypes. Power spectral analysis of HRV was conducted on the overnight electrocardiogram during non-rapid eye movement (NREM), rapid eye movement (REM), N1, N2, N3 sleep stages, and wake periods. High-frequency HRV (HF-HRV) was employed as the primary measure to estimate parasympathetic function. Results The MCI group showed reduced HF-HRV during NREM sleep (p = 0.018), but not during wake or REM sleep (p > 0.05) compared to the SCI group. Participants with aMCI compared to SCI had the most pronounced reduction in HF-HRV across all NREM sleep stages—N1, N2, and N3, but not during wake or REM sleep. The naMCI sub-group did not show any significant differences in HF-HRV during any sleep stage compared to SCI. Conclusions Our study showed that amnestic MCI participants had greater reductions in HF-HRV during NREM sleep, relative to those with SCI, suggesting potential vulnerability to sleep-related parasympathetic dysfunction. HF-HRV, especially during NREM sleep, may be an early biomarker for dementia detection.

Cluster headache shows no association with rapid eye movement sleep

Cephalalgia ◽  
2012 ◽  
Vol 32 (4) ◽  
pp. 289-296 ◽  
Author(s):  
Sebastian Zaremba ◽  
Dagny Holle ◽  
Thomas E Wessendorf ◽  
Hans C Diener ◽  
Zaza Katsarava ◽  
...  
Keyword(s):  
Cluster Headache ◽  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Stage ◽  
Sleep Time ◽  
Brain Regions ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Sleep State ◽  
Wake Time

Background: The connection of cluster headache (CH) attacks with rapid eye movement (REM) sleep has been suggested by various studies, while other authors challenge this assumption. We performed serial polysomnography to determine the association of nocturnal CH attacks and sleep. Methods: Five patients diagnosed with CH (two with the episodic and three with the chronic subtype) were included and studied over four consecutive nights to evaluate connections between attacks onset and sleep stage. Results: Twenty typical CH attacks were reported. Thirteen of these attacks arose from sleep. Seven attacks were reported after waking in the morning or shortly before going to sleep. The beginnings of sleep-related attacks were distributed arbitrarily between different non-REM sleep stages. No association of CH attacks with REM or sleep disordered breathing was observed. Increased heart rate temporally associated with transition from one sleep state to another was observed before patients awoke with headache. Total sleep time, total wake time, arousal index and distribution of non-REM sleep stages were different between chronic and episodic CH. Conclusion: CH attacks are not associated with REM sleep. Brain regions involved in sleep stage transition might be involved in pathophysiology of CH. Differences in sleep characteristics between subgroups might indicate adaptation processes or underlying pathophysiology.

DHEA administration increases rapid eye movement sleep and EEG power in the sigma frequency range

1995 ◽  
Vol 268 (1) ◽  
pp. E107-E113 ◽  
Author(s):  
E. Friess ◽  
L. Trachsel ◽  
J. Guldner ◽  
T. Schier ◽  
A. Steiger ◽  
...  
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Hormone Secretion ◽  
Power Spectra ◽  
Memory Storage ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Frequency Range ◽  
Eeg Power Spectra ◽  
Eeg Power

Dehydroepi-androsterone (DHEA) exhibits various behavioral effects in mammals, at least one of which is enhancement of memory that appears to be mediated by an interaction with the gamma-aminobutyric acidA (GABAA) receptor complex. We investigated the effects of a single oral dose of DHEA (500 mg) on sleep stages, sleep stage-specific electroencephalogram (EEG) power spectra, and concurrent hormone secretion in 10 healthy young men. DHEA administration induced a significant (P < 0.05) increase in rapid eye movement (REM) sleep, whereas all other sleep variables remained unchanged compared with the placebo condition. Spectral analysis of five selected EEG bands revealed significantly (P < 0.05) enhanced EEG activity in the sigma frequency range during REM sleep in the first 2-h sleep period after DHEA administration. In contrast, the EEG power spectra of non-REM sleep were not affected, nor were the nocturnal time course curves of plasma cortisol, growth hormone, or testosterone concentration. The results suggest that DHEA administration has a mixed GABAA-agonistic/antagonistic effect, exerted either directly or through DHEA-induced changes in steroid metabolism. Because REM sleep has been implicated in memory storage, its augmentation in the present study suggests the potential clinical usefulness of DHEA in age-related dementia.

Polysomnographic measures of sleep moderate the relationship between depression and pain

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 8526-8526 ◽  
Author(s):  
K. P. Parker ◽  
D. L. Bliwise ◽  
J. Dalton ◽  
W. Harris ◽  
S. Jain ◽  
...  
Keyword(s):  
Pain Intensity ◽  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Latency ◽  
Sleep Cycle ◽  
Rapid Eye Movement ◽  
Nocturnal Sleep ◽  
Tumor Stages ◽  
The Mean ◽  
The Relationship

8526 Background: We explored the effects of polysomnographic measures of nocturnal sleep on depression and pain in advanced cancer patients taking opioids. Methods: The sample included 72 subjects (solid tumor, Stages III/IV) with a mean age of 55.9 (9.1); 39 were male. All were taking opioids. Subjects underwent ambulatory polysomnography for 48 hours in their homes. Nocturnal sleep parameters included total sleep time (minutes); sleep efficiency (SE; %); sleep latency (SL; minutes); rapid-eye-movement sleep latency (REML; minutes); the percentages (%) of non-rapid eye movement (NREM) Stages 1, 2, and slow wave sleep (SWS, 3 & 4), and REM sleep; and the number of awakenings > 60 seconds. Subjects kept an opioid diary, data from which were converted into a mean hourly morphine equivalent dose (HMED). Subjects also completed the Brief Pain Inventory (BPI) and the Beck Depression Inventory (BDI). Descriptive, correlation, and regression procedures were used for data analysis. Results: Subjects had a mean nocturnal sleep period of 400.1 ± 97.4 minutes. The SL was normal at 26.5 ± 42.6 minutes but the SE was low (77.5 ± 13.2%). Most sleep was light NREM Stages 1 and 2 with decreased amounts of deep SWS (0.3 ± 2.7%) and REM sleep (14.4 ± 8.5%). The REML was prolonged at 149.1 ± 105.1 minutes. The mean BPI scores for pain intensity and interference were 4.4 ± 1.4 and 5.0 ± 2.1, respectively. The mean BDI score was 13.7 ± 7.9. The average HMED was .59 ± .1. Controlling for age and gender, regression analyses revealed that SWS and REM sleep moderated the relationship between depression and pain. Those with more SWS had lower depression levels in spite of higher pain intensity (t = -2.8, p = .007) while those with more REM sleep had lower depression levels despite higher pain interference (t = -2.0, p = .045). Controlling for pain intensity and interference, HMED was positively associated with Stage 1 % (r = .36, p = .001) and the number of nocturnal awakenings > 60 seconds (r = .28, p = .019). Conclusions: Opioids may lighten and disrupt sleep altering sleep cycle progression. The resulting decrements in SWS and REM sleep may lead to increased depression and enhanced pain. Consideration of the timing and dosing of opioids in relationship to nocturnal sleep may decrease depression and subsequently optimize pain management. No significant financial relationships to disclose.

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