Augmenting expiratory neuronal activity in sleep and wakefulness and in relation to duration of expiration

1998 ◽  
Vol 85 (4) ◽  
pp. 1260-1266 ◽  
Author(s):  
John Orem
Keyword(s):  
Correlation Analysis ◽  
Eye Movement ◽  
Neuronal Activity ◽  
Rem Sleep ◽  
Inverse Relationship ◽  
Rapid Eye Movement ◽  
Consistent Relationship ◽  
Kendall’S Τ ◽  
Relationship Of ◽  
The Relationship

Augmenting expiratory cells ( n = 23) were recorded in the rostral medulla of five cats in sleep and wakefulness. The objective was to determine the relationship of their activity to the duration of expiration (Te) and, particularly, to Te in rapid-eye-movement (REM) sleep, when expirations are short and may even cause fractionated breathing. Correlation analysis (Kendall’s τ) showed no consistent relationship in any state between the breath-by-breath mean activity of augmenting expiratory cells and Te. This result contradicts predications of an inverse relationship between augmenting expiratory activity and Te. Some cells (11 of 23) were more active in REM than in non-REM sleep and were active during fractionated breathing. This suggests that fractionated breathing in REM sleep is caused by short expiratory phases and not by intermittent inhibition of an ongoing inspiration.

scholarly journals The Relationship Between Daily Rapid-Eye Movement Sleep and Cognitive Functioning in Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 159-159
Author(s):  
Tiana Broen ◽  
Tomiko Yoneda ◽  
Jonathan Rush ◽  
Jamie Knight ◽  
Nathan Lewis ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Cognitive Functioning ◽  
Eye Movement ◽  
Rem Sleep ◽  
Cognitive Tests ◽  
Rapid Eye Movement ◽  
Targeted Interventions ◽  
The Impact ◽  
The Relationship

Abstract Previous cross-sectional research suggests that age-related decreases in Rapid-Eye Movement (REM) sleep may contribute to poorer cognitive functioning (CF); however, few studies have examined the relationship at the intraindividual level by measuring habitual sleep over multiple days. Applying a 14-day daily diary design, the current study examines the dynamic relationship between REM sleep and CF in 69 healthy older adults (M age=70.8 years, SD=3.37; 73.9% female; 66.6% completed at least an undergraduate degree). A Fitbit device provided actigraphy indices of REM sleep (minutes and percentage of total sleep time), while CF was measured four times daily on a smartphone via ambulatory cognitive tests that captured processing speed and working memory. This research addressed the following questions: At the within-person level, are fluctuations in quantity of REM sleep associated with fluctuations in next day cognitive measures across days? Do individuals who spend more time in REM sleep on average, perform better on cognitive tests than adults who spend less time in REM sleep? A series of multilevel models were fit to examine the extent to which each index of sleep accounted for daily fluctuations in performance on next day cognitive tests. Results indicated that during nights when individuals had more REM sleep minutes than was typical, they performed better on the working memory task the next morning (estimate = -.003, SE = .002, p = .02). These results highlight the impact of REM sleep on CF, and further research may allow for targeted interventions for earlier treatment of sleep-related cognitive impairment.

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.

Marijuana and Ethanol: Effects on Sleep

1973 ◽  
Vol 4 (2) ◽  
pp. 201-212 ◽  
Author(s):  
Vincent P. Zarcone
Keyword(s):  
Sleep Deprivation ◽  
Eye Movement ◽  
Neuronal Activity ◽  
Slow Wave ◽  
Rem Sleep ◽  
Slow Wave Sleep ◽  
Rapid Eye Movement ◽  
Acute Effects ◽  
Rem Sleep Deprivation ◽  
The Public

Both marijuana and alcohol have effects on sleep which can be clinically important if either drug is used heavily. A number of polygraphic studies of both drugs' effect on sleep demonstrate that both are rapid eye movement (REM) sleep suppressors and that both effect the REM sleep deprivation response for days after the acute effects have ceased. Marijuana also increases slow wave sleep compared to alcohol which decreases it. The studies reviewed indicate that marijuana, like alcohol, has persisting effects on neuronal activity and presumably on its underlying neurochemical regulation. Also, the studies suggest that caution should be employed in advising the public about the use of marijuana.

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.

Effects of selective sleep deprivation on ventilation during recovery sleep in normal humans

1992 ◽  
Vol 72 (1) ◽  
pp. 100-109 ◽  
Author(s):  
J. B. Neilly ◽  
N. B. Kribbs ◽  
G. Maislin ◽  
A. I. Pack
Keyword(s):  
Sleep Deprivation ◽  
Eye Movement ◽  
Rem Sleep ◽  
Minute Ventilation ◽  
Nrem Sleep ◽  
Rapid Eye Movement ◽  
Rem Sleep Deprivation ◽  
Sleep Period ◽  
Recovery Sleep ◽  
The Relationship

To assess the effects of selective sleep loss on ventilation during recovery sleep, we deprived 10 healthy young adult humans of rapid-eye-movement (REM) sleep for 48 h and compared ventilation measured during the recovery night with that measured during the baseline night. At a later date we repeated the study using awakenings during non-rapid-eye-movement (NREM) sleep at the same frequency as in REM sleep deprivation. Neither intervention produced significant changes in average minute ventilation during presleep wakefulness, NREM sleep, or the first REM sleep period. By contrast, both interventions resulted in an increased frequency of breaths, in which ventilation was reduced below the range for tonic REM sleep, and in an increased number of longer episodes, in which ventilation was reduced during the first REM sleep period on the recovery night. The changes after REM sleep deprivation were largely due to an increase in the duration of the REM sleep period with an increase in the total phasic activity and, to a lesser extent, to changes in the relationship between ventilatory components and phasic eye movements. The changes in ventilation after partial NREM sleep deprivation were associated with more pronounced changes in the relationship between specific ventilatory components and eye movement density, whereas no change was observed in the composition of the first REM sleep period. These findings demonstrate that sleep deprivation leads to changes in ventilation during subsequent REM sleep.

Analysis of Maximum Expiratory Flow Volume Curves Using Canonical Correlation Analysis

1985 ◽  
Vol 24 (02) ◽  
pp. 91-100 ◽  
Author(s):  
W. van Pelt ◽  
Ph. H. Quanjer ◽  
M. E. Wise ◽  
E. van der Burg ◽  
R. van der Lende
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Flow Volume ◽  
Non Linear ◽  
Maximum Expiratory Flow ◽  
Expiratory Flow ◽  
Relationship Of ◽  
The Relationship ◽  
Age And Sex

SummaryAs part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.

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