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https://www.readbyqxmd.com/read/28337411/physiological-and-pathological-high-frequency-oscillations-have-distinct-sleep-homeostatic-properties
#1
Nicolás von Ellenrieder, François Dubeau, Jean Gotman, Birgit Frauscher
OBJECTIVE: The stage of sleep is a known modulator of high-frequency oscillations (HFOs). For instance, high amplitude slow waves during NREM sleep and the subtypes of REM sleep were shown to contribute to a better separation between physiological and pathological HFOs. This study investigated rates and spatial spread of the different HFO types (physiological and pathological ripples in the 80-250 Hz frequency band, and fast ripples above 250 Hz) depending on time spent in sleep across the different sleep cycles...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28334175/attenuated-fast-steady-state-visual-evoked-potentials-during-human-sleep
#2
Omer Sharon, Yuval Nir
During sleep, external sensory events rarely elicit a behavioral response or affect perception. However, how sensory processing differs between wakefulness and sleep remains unclear. A major difficulty in this field stems from using brief auditory stimuli that often trigger nonspecific high-amplitude "K-complex" responses and complicate interpretation. To overcome this challenge, here we delivered periodic visual flicker stimulation across sleep and wakefulness while recording high-density electroencephalography (EEG) in humans...
February 25, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28329204/new-neuroscience-tools-that-are-identifying-the-sleep-wake-circuit
#3
Priyattam J Shiromani, John H Peever
The complexity of the brain is yielding to technology. In the area of sleep neurobiology, conventional neuroscience tools such as lesions, cell recordings, c-Fos, and axon-tracing methodologies have been instrumental in identifying the complex and intermingled populations of sleep- and arousal-promoting neurons that orchestrate and generate wakefulness, NREM, and REM sleep. In the last decade, new technologies such as optogenetics, chemogenetics and the CRISPR-Cas system have begun to transform how biologists understand the finer details associated with sleep-wake regulation...
March 1, 2017: Sleep
https://www.readbyqxmd.com/read/28326118/spectral-analysis-of-polysomnography-in-narcolepsy
#4
Seok Ho Yun, Ho Dong Choi, Wan Seok Seo
OBJECTIVE: This study was conducted to identify differences between people with narcolepsy and the normal control of delta and theta activity using electroencephalogram (EEG) spectrum analysis of nocturnal polysomnography (PSG). METHODS: Seven narcolepsy patients and seven age-sex matched normal controls underwent PSG and multiple sleep latency tests. Participants' non-rapid eye movement (NREM) sleep EEGs in PSG was analyzed using a Fast Fourier Transform technique...
March 2017: Psychiatry Investigation
https://www.readbyqxmd.com/read/28325016/sleep-stage-classification-by-non-contact-vital-signs-indices-using-doppler-radar-sensors
#5
Masayuki Kagawa, Kazuki Suzumura, Takemi Matsui
Disturbed sleep has become more common in recent years. To improve the quality of sleep, undergoing sleep observation has gained interest as a means to resolve possible problems. In this paper, we evaluate a non-restrictive and non-contact method for classifying real-time sleep stages and report on its potential applications. The proposed system measures heart rate (HR), heart rate variability (HRV), body movements, and respiratory signals of a sleeping person using two 24-GHz microwave radars placed beneath the mattress...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28315757/chronic-social-stress-leads-to-altered-sleep-homeostasis-in-mice
#6
Nadja Olini, Iru Rothfuchs, Damiano Azzinnari, Christopher R Pryce, Salome Kurth, Reto Huber
Disturbed sleep and altered sleep homeostasis are core features of many psychiatric disorders such as depression. Chronic uncontrollable stress is considered an important factor in the development of depression, but little is known on how chronic stress affects sleep regulation and sleep homeostasis. We therefore examined the effects of chronic social stress (CSS) on sleep regulation in mice. Adult male C57BL/6 mice were implanted for electrocortical recordings (ECoG) and underwent either a 10-day CSS protocol or control handling (CON)...
March 15, 2017: Behavioural Brain Research
https://www.readbyqxmd.com/read/28306130/brain-connectivity-is-altered-by-extreme-physical-exercise-during-non-rem-sleep-and-wakefulness-indications-from-eeg-and-fmri-studies
#7
D Menicucci, C Gentili, A Piarulli, M Laurino, S Pellegrini, F Mastorci, R Bedini, D Montanaro, L Sebastiani, A Gemignani
Brain connectivity is associated to behavioral states (e.g. wake, sleep) and modified by physical activity although, to date, it is not clear which components (e.g. hypothalamus-pituitary-adrenal axis hormones, cytokines) associated to the exercise are involved. In this pilot study, we used extreme exercise (UltraTriathlon) as a model to investigate physical-activity-related changes of brain connectivity. We studied post-race brain synchronization during wakefulness and sleep as well as possible correlations between exercise-related cytokines/hormones and synchronization features...
December 1, 2016: Archives Italiennes de Biologie
https://www.readbyqxmd.com/read/28288386/sleep-regulation-of-the-distribution-of-cortical-firing-rates
#8
REVIEW
Daniel Levenstein, Brendon O Watson, John Rinzel, György Buzsáki
Sleep is thought to mediate both mnemonic and homeostatic functions. However, the mechanism by which this brain state can simultaneously implement the 'selective' plasticity needed to consolidate novel memory traces and the 'general' plasticity necessary to maintain a well-functioning neuronal system is unclear. Recent findings show that both of these functions differentially affect neurons based on their intrinsic firing rate, a ubiquitous neuronal heterogeneity. Furthermore, they are both implemented by the NREM slow oscillation, which also distinguishes neurons based on firing rate during sequential activity at the DOWN→UP transition...
March 10, 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28275652/altered-sleep-and-eeg-power-in-the-p301s-tau-transgenic-mouse-model
#9
Jerrah K Holth, Thomas E Mahan, Grace O Robinson, Andreia Rocha, David M Holtzman
OBJECTIVE: Sleep disturbances are prevalent in human tauopathies yet despite the importance of sleep, little is known about its relationship with tau pathology. Here, we investigate this interaction by analyzing sleep and tau pathology throughout tauopathy disease progression in P301S human tau transgenic mice. METHODS: P301S and wild-type mice were analyzed by electroencephalography (EEG)/electromyography at 3, 6, 9, and 11 months of age for sleep/wake time, EEG power, and homeostatic response...
March 2017: Annals of Clinical and Translational Neurology
https://www.readbyqxmd.com/read/28268910/estimation-of-macro-sleep-stages-from-whole-night-audio-analysis
#10
E Dafna, M Halevi, D Ben Or, A Tarasiuk, Y Zigel
During routine sleep diagnostic procedure, sleep is broadly divided into three states: rapid eye movement (REM), non-REM (NREM) states, and wake, frequently named macro-sleep stages (MSS). In this study, we present a pioneering attempt for MSS detection using full night audio analysis. Our working hypothesis is that there might be differences in sound properties within each MSS due to breathing efforts (or snores) and body movements in bed. In this study, audio signals of 35 patients referred to a sleep laboratory were recorded and analyzed...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268909/sleep-stage-recognition-using-respiration-signal
#11
Jialei Yang, James M Keller, Mihail Popescu, Marjorie Skubic
This paper presents a sleep stage recognition system for Awake, rapid eye movement (REM) and non-REM (NREM) sleep detection. Two respiratory variability (RV) features are extracted from oro-nasal airflow signals provided in the sleep-EDF (Expanded) database. A two layer system with threshold comparison classifier is implemented. This system achieved state-of-the-art performance with simple features and classifiers. The average accuracy of 74.00%±5.30% and Cohen's kappa coefficient of 0.49±0.08 were achieved with 21 recordings...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268908/bioradiolocation-based-sleep-stage-classification
#12
Alexander Tataraidze, Lyudmila Korostovtseva, Lesya Anishchenko, Mikhail Bochkarev, Yurii Sviryaev, Sergey Ivashov
This paper presents a method for classifying wakefulness, REM, light and deep sleep based on the analysis of respiratory activity and body motions acquired by a bioradar. The method was validated using data of 32 subjects without sleep-disordered breathing, who underwent a polysomnography study in a sleep laboratory. We achieved Cohen's kappa of 0.49 in the wake-REM-light-deep sleep classification, 0.55 for the wake-REM-NREM classification and 0.57 for the sleep/wakefulness determination. The results might be useful for the development of unobtrusive sleep monitoring systems for diagnostics, prevention, and management of sleep disorders...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268907/probabilistic-characterization-of-sleep-architecture-home-based-study-on-healthy-volunteers
#13
Gary Garcia-Molina, Sreeram Vissapragada, Anandi Mahadevan, Robert Goodpaster, Brady Riedner, Michele Bellesi, Giulio Tononi
The quantification of sleep architecture has high clinical value for diagnostic purposes. While the clinical standard to assess sleep architecture is in-lab based polysomnography, higher ecological validity can be obtained with multiple sleep recordings at home. In this paper, we use a dataset composed of fifty sleep EEG recordings at home (10 per study participant for five participants) to analyze the sleep stage transition dynamics using Markov chain based modeling. The statistical analysis of the duration of continuous sleep stage bouts is also analyzed to identify the speed of transition between sleep stages...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28261503/cpap-treatment-partly-normalizes-sleep-spindle-features-in-obstructive-sleep-apnea
#14
Tiia Saunamäki, Eero Huupponen, Juho Loponen, Sari-Leena Himanen
Objective. Obstructive sleep apnea (OSA) decreases sleep spindle density and frequency. We evaluated the effects of continuous positive airway pressure (CPAP) treatment on different features of sleep spindles. Methods. Twenty OSA patients underwent two night polysomnographies in a diagnostic phase and one night polysomnography after 6 months of CPAP treatment. The control group comprised 20 healthy controls. Sleep spindles were analyzed by a previously developed automated method. Unilateral and bilateral spindles were identified in central and frontopolar brain locations...
2017: Sleep Disorders
https://www.readbyqxmd.com/read/28255162/differences-in-electroencephalographic-non-rapid-eye-movement-sleep-slow-wave-characteristics-between-young-and-old-mice
#15
Maria Panagiotou, Vladyslav V Vyazovskiy, Johanna H Meijer, Tom Deboer
Changes in sleep pattern are typical for the normal aging process. However, aged mice show an increase in the amount of sleep, whereas humans show a decrease when aging. Mice are considered an important model in aging studies, and this divergence warrants further investigation. Recently, insights into the network dynamics of cortical activity during sleep were obtained by investigating characteristics of individual electroencephalogram (EEG) slow waves in young and elderly humans. In this study, we investigated, for the first time, the parameters of EEG slow waves, including their incidence, amplitude, duration and slopes, in young (6 months) and older (18-24 months) C57BL/6J mice during undisturbed 24 h, and after a 6-h sleep deprivation (SD)...
March 3, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28255086/mechanisms-of-the-deep-slow-wave-sleep-related-increase-of-upper-airway-muscle-tone-in-healthy-humans
#16
Amelia Hicks, Jennifer M Cori, Amy S Jordan, Christian L Nicholas, Leszek Kubin, John G Semmler, Atul Malhotra, David Gerard Peter McSharry, John A Trinder
Upper airway muscle activity is reportedly elevated during slow-wave sleep (SWS) when compared to lighter sleep stages. To uncover the possible mechanisms underlying this elevation, we explored the correlation between different indices of central and reflex inspiratory drive, such as the changes in airway pressure and end-expiratory CO2, and the changes in the genioglossus (GG) and tensor palatini (TP) muscle activity accompanying transitions from the lighter N2 to the deeper N3 stage of non-rapid eye movement (NREM) sleep in healthy young adult men...
March 2, 2017: Journal of Applied Physiology
https://www.readbyqxmd.com/read/28229642/sleep-loss-and-recovery-after-administration-of-drugs-related-to-different-arousal-systems-in-rats
#17
T Hajnik, A Tóth, Ö Szalontai, M Pethő, L Détári
Sleep is homeostatically regulated suggesting a restorative function. Sleep deprivation is compensated by an increase in length and intensity of sleep. In this study, suppression of sleep was induced pharmacologically by drugs related to different arousal systems. All drugs caused non-rapid eye movement (NREM) sleep loss followed by different compensatory processes. Apomorphine caused a strong suppression of sleep followed by an intense recovery. In the case of fluoxetine and eserine, recovery of NREM sleep was completed by the end of the light phase due to the biphasic pattern demonstrated for these drugs first in the present experiments...
September 2016: Physiol Int
https://www.readbyqxmd.com/read/28227613/sleep-stage-classification-by-non-contact-vital-signs-indices-using-doppler-radar-sensors
#18
Masayuki Kagawa, Kazuki Suzumura, Takemi Matsui, Masayuki Kagawa, Kazuki Suzumura, Takemi Matsui, Kazuki Suzumura, Takemi Matsui, Masayuki Kagawa
Disturbed sleep has become more common in recent years. To improve the quality of sleep, undergoing sleep observation has gained interest as a means to resolve possible problems. In this paper, we evaluate a non-restrictive and non-contact method for classifying real-time sleep stages and report on its potential applications. The proposed system measures heart rate (HR), heart rate variability (HRV), body movements, and respiratory signals of a sleeping person using two 24-GHz microwave radars placed beneath the mattress...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227112/estimation-of-macro-sleep-stages-from-whole-night-audio-analysis
#19
E Dafna, M Halevi, D Ben Or, A Tarasiuk, Y Zigel, E Dafna, M Halevi, D Ben Or, A Tarasiuk, Y Zigel, D Ben Or, Y Zigel, M Halevi, E Dafna, A Tarasiuk
During routine sleep diagnostic procedure, sleep is broadly divided into three states: rapid eye movement (REM), non-REM (NREM) states, and wake, frequently named macro-sleep stages (MSS). In this study, we present a pioneering attempt for MSS detection using full night audio analysis. Our working hypothesis is that there might be differences in sound properties within each MSS due to breathing efforts (or snores) and body movements in bed. In this study, audio signals of 35 patients referred to a sleep laboratory were recorded and analyzed...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227111/sleep-stage-recognition-using-respiration-signal
#20
Jialei Yang, James M Keller, Mihail Popescu, Marjorie Skubic, Jialei Yang, James M Keller, Mihail Popescu, Marjorie Skubic, James M Keller, Mihail Popescu, Marjorie Skubic, Jialei Yang
This paper presents a sleep stage recognition system for Awake, rapid eye movement (REM) and non-REM (NREM) sleep detection. Two respiratory variability (RV) features are extracted from oro-nasal airflow signals provided in the sleep-EDF (Expanded) database. A two layer system with threshold comparison classifier is implemented. This system achieved state-of-the-art performance with simple features and classifiers. The average accuracy of 74.00%±5.30% and Cohen's kappa coefficient of 0.49±0.08 were achieved with 21 recordings...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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