Systemic Homeostasis and Poikilostasis in Sleep

Parmeggiani, Pier Luigi

doi:10.1142/p720

Cited by 9 publications

(5 citation statements)

References 232 publications

(454 reference statements)

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“…Or second, our results in the first SWS cycle may reflect the effect of increased body temperature on cardiac tissue conductance (39,48) independent of neuronal input to the heart itself as body temperature is at its peak just prior to sleep onset (acrophase) and is dropping in the first sleep cycle but still high in the early hours of sleep (12). Cardiac tissue cooling in rabbits has demonstrated an increase in spontaneous sinus cycle length, suggesting hotter core temperature alone could account for the higher heart rate in SWS1 (49).…”

Section: Interpreting the Inconsistenciesmentioning

confidence: 80%

The Inconsistent Nature of Heart Rate Variability During Sleep in Normal Children and Adolescents

Kontos

Baumert

Lushington

et al. 2020

Front. Cardiovasc. Med.

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Section: Interpreting the Inconsistenciesmentioning

confidence: 80%

The Inconsistent Nature of Heart Rate Variability During Sleep in Normal Children and Adolescents

Kontos

Baumert

Lushington

et al. 2020

Front. Cardiovasc. Med.

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“…These phenomena point to fundamental differences in autonomic control mechanisms as the source of the observed respiratory variability. One reason proposed is the systemic suspension of homeostastic control during REM (Parmeggiani 2011), which allows cardiorespiratory variables to drift relative to their values in other stages of sleep.…”

Section: Discussionmentioning

confidence: 99%

Noninvasive dissection of mouse sleep using a piezoelectric motion sensor

Yaghouby

Donohue

O’Hara

et al. 2016

Journal of Neuroscience Methods

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Background Changes in autonomic control cause regular breathing during NREM sleep to fluctuate during REM. Piezoelectric cage-floor sensors have been used to successfully discriminate sleep and wake states in mice based on signal features related to respiration and other movements. This study presents a classifier for noninvasively classifying REM and NREM using a piezoelectric sensor. New Method Vigilance state was scored manually in 4-second epochs for 24-hour EEG/EMG recordings in twenty mice. An unsupervised classifier clustered piezoelectric signal features quantifying movement and respiration into three states: one active; and two inactive with regular and irregular breathing respectively. These states were hypothesized to correspond to Wake, NREM, and REM respectively. States predicted by the classifier were compared against manual EEG/EMG scores to test this hypothesis. Results Using only piezoelectric signal features, an unsupervised classifier distinguished Wake with high (89% sensitivity, 96% specificity) and REM with moderate (73% sensitivity, 75% specificity) accuracy, but NREM with poor sensitivity (51%) and high specificity (96%). The classifier sometimes confused light NREM sleep—characterized by irregular breathing and moderate delta EEG power—with REM. A supervised classifier improved sensitivities to 90, 81, and 67% and all specificities to over 90% for Wake, NREM, and REM respectively. Comparison with Existing Methods Unlike most actigraphic techniques, which only differentiate sleep from wake, the proposed piezoelectric method further dissects sleep based on breathing regularity into states strongly correlated with REM and NREM. Conclusions This approach could facilitate large-sample screening for genes influencing different sleep traits, besides drug studies or other manipulations.

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“…[8][9][10] A turning point in the conception of sleep was achieved finally when rapid eye movement (REM) sleep was detected as a unique state of sleep, 11,12 which differs from NREM sleep not only by its morphology but also by its systemic regulation. [13][14][15] In combination with an increasing knowledge on sleep physiology, this became the basis for the experimental study of sleep and its disorders in…”

Section: Introductionmentioning

confidence: 99%

The Development of Sleep Medicine: A Historical Sketch

Schulz

Salzarulo²

2016

Journal of Clinical Sleep Medicine

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For centuries the scope of sleep disorders in medical writings was limited to those disturbances which were either perceived by the sleeper him-or herself as troublesome, such as insomnia, or which were recognized by an observer as strange behavioral acts during sleep, such as sleepwalking or sleep terrors. Awareness of other sleep disorders, which are caused by malfunction of a physiological system during sleep, such as sleep-related respiratory disorders, were widely unknown or ignored before sleep monitoring techniques became available, mainly in the second half of the 20 th century. Finally, circadian sleepwake disorders were recognized as a group of disturbances by its own only when chronobiology and sleep research began to interact extensively in the last two decades of the 20 th century. Sleep medicine as a medical specialty with its own diagnostic procedures and therapeutic strategies could be established only when key findings in neurophysiology and basic sleep research allowed a breakthrough in the understanding of the sleeping brain, mainly since the second half of the last century. Keywords: history, insomnia, hypersomnia, narcolepsy, parasomnia, sleep-related movement disorder, pediatric sleep disorder, sleep apnea, circadian rhythm sleep-wake disorder Citation: Schulz H, Salzarulo P. The development of sleep medicine: a historical sketch.

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Systemic Homeostasis and Poikilostasis in Sleep

Cited by 9 publications

References 232 publications

The Inconsistent Nature of Heart Rate Variability During Sleep in Normal Children and Adolescents

The Inconsistent Nature of Heart Rate Variability During Sleep in Normal Children and Adolescents

Noninvasive dissection of mouse sleep using a piezoelectric motion sensor

The Development of Sleep Medicine: A Historical Sketch

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