Correct sleep scoring is the base of sleep studying; nonlinear features of EEG can represent different sleep stages. In this paper, correlation dimension (D2) and approximate entropy (ApEn) of sleep EEG have been calculated. The statistical results reveal that: D2 does not come to be saturated when the embedding dimension increases, but the relative value of D2 can effectively distinguish different sleep stages. ApEn has the advantage of calculating simply, steady result and representing preferably different sleep stages. ApEn and the relative value of D2 reveal, from different point of view, the same rule about EEG (brain) complexity changing, that is, both complexity and its fluctuation are maximal in the subject's awake hour, are decreasing with the deepening of sleep, but the complexity in REM is about the level between S1 and S2.
Electroencephalography ; Entropy ; Humans ; Nonlinear Dynamics ; Sleep ; physiology ; Sleep Stages ; physiology

Brain ; physiology ; History, 20th Century ; Humans ; Sleep ; physiology ; Sleep Medicine Specialty ; history ; Sleep, REM ; physiology

Glutamate as an excitatory neurotransmitter in the central nervous system, participate in initiation and maintaining of sleep and wakefulness. The paper presents an overview of the research progress of glutamate in the regulation of sleep and wakefulness, especially focuses on its role in the brainstem, lateral hypothalamus and basal forebrain. Glutamate in the brain stem regulates the brain activity and maintains muscle tone during the wakefulness, as well as adjusts the electroencephalograph (EEG) in rapid eye movement phase and leads to muscle weakness. Glutamate in the lateral hypothalamus participates in the lateral hypothalamic arousal system by activating orexins neurons. The basal forebrain glutamatergic neurons take part in EEG synchronization and cause the decrease of sleep. Finally,The glutamatergic neurons of the cerebral cortex is not just a target of the arousal system, but itself contribute to regulation of arousal. Meantime, the glutamatergic neurons can regulate sleep stages through interaction with other types of neurons, which forms a complex sleep-wake regulation network in the brain. These indicate that the switches between different phases of sleep and wakefulness have different neuronal circuits.So we also reviewed the neuronal circuits and mechanisms that glutamate may be involved in. This review will help us to get a better understanding of the roles of glutamate in sleep and wakefulness.
Glutamic Acid ; physiology ; Humans ; Sleep ; physiology ; Wakefulness ; physiology

The parabrachial nucleus (PBN) integrates interoceptive and exteroceptive information to control various behavioral and physiological processes including breathing, emotion, and sleep/wake regulation through the neural circuits that connect to the forebrain and the brainstem. However, the precise identity and function of distinct PBN subpopulations are still largely unknown. Here, we leveraged molecular characterization, retrograde tracing, optogenetics, chemogenetics, and electrocortical recording approaches to identify a small subpopulation of neurotensin-expressing neurons in the PBN that largely project to the emotional control regions in the forebrain, rather than the medulla. Their activation induces freezing and anxiety-like behaviors, which in turn result in tachypnea. In addition, optogenetic and chemogenetic manipulations of these neurons revealed their function in promoting wakefulness and maintaining sleep architecture. We propose that these neurons comprise a PBN subpopulation with specific gene expression, connectivity, and function, which play essential roles in behavioral and physiological regulation.
Parabrachial Nucleus/physiology* ; Wakefulness/physiology* ; Neurons/physiology* ; Emotions ; Sleep

Difference of chronotypes makes influence to cognitive performance of individuals in routine duties. In this paper, 55 subjects with different chronotypes were subjected to continuous sleep deprivation for 30 h by using the constant routine protocol, during which core body temperature was measured continuously, and subjective sleepiness self-rating and the performance of selective attention were measured hourly. The results showed that the phase difference of core body temperature has no significant difference, yet the amplitude and term difference among the three chronotypes are significant. There was an advance in phase between subjective sleepiness self-rating and core body temperature, and the self-rating sleepiness of evening type came the latest, and the self-rating sleepiness of morning type dissipated the fastest. The response time of selective attention showed a 2 h phase delay with subjective sleepiness self-rating. And the analysis of core body temperature showed that the later the chronotype was, the greater the phase delay was. The correct rate of selective attention of different chronotypes were inconsistent with delay of subjective sleepiness self-rating and core body temperature. We provide reference for industry, aviation, military, medical and other fields to make a more scientific scheduling/ shifting based on cognitive performance characteristics of different chronotypes.
Attention/physiology* ; Circadian Rhythm/physiology* ; Homeostasis ; Humans ; Sleep/physiology* ; Sleep Deprivation ; Sleepiness

Penile erection (PE) is a physiological phenomenon involving complex mechanisms. PE may occur as reactive erections, psychogenic erections in the conscious state and spontaneous erections during the sleep. Sleep-related PE refers to the erections occurring spontaneously during the sleep with rapid eye movement. Studies have shown a correlation between sleep and PE as well as between sleep disorders and erectile dysfunction but not yet revealed the exact mechanisms. This paper updates the relationship between sleep and erectile function.
Erectile Dysfunction ; etiology ; Humans ; Male ; Penile Erection ; physiology ; Sleep ; physiology ; Sleep Wake Disorders ; complications ; Sleep, REM ; physiology

Multi-channel in vivo recording techniques are used to record ensemble neuronal activity and local field potentials (LFP) simultaneously. One of the key points for the technique is how to process these two sets of recorded neural signals properly so that data accuracy can be assured. We intend to introduce data processing approaches for action potentials and LFP based on the original data collected through multi-channel recording system. Action potential signals are high-frequency signals, hence high sampling rate of 40 kHz is normally chosen for recording. Based on waveforms of extracellularly recorded action potentials, tetrode technology combining principal component analysis can be used to discriminate neuronal spiking signals from differently spatially distributed neurons, in order to obtain accurate single neuron spiking activity. LFPs are low-frequency signals (lower than 300 Hz), hence the sampling rate of 1 kHz is used for LFPs. Digital filtering is required for LFP analysis to isolate different frequency oscillations including theta oscillation (4-12 Hz), which is dominant in active exploration and rapid-eye-movement (REM) sleep, gamma oscillation (30-80 Hz), which is accompanied by theta oscillation during cognitive processing, and high frequency ripple oscillation (100-250 Hz) in awake immobility and slow wave sleep (SWS) state in rodent hippocampus. For the obtained signals, common data post-processing methods include inter-spike interval analysis, spike auto-correlation analysis, spike cross-correlation analysis, power spectral density analysis, and spectrogram analysis.
Action Potentials ; Animals ; Humans ; Neurons ; physiology ; Sleep

Neural oscillations reflect synchronized activities of neuronal ensembles in central nervous system. In the hippocampus, thalamus, neocortex and other brain subregions, neural oscillation can be detected and plays a crucial role in many complicated cognitive processes. Decoupling and damaging of neural oscillation play a key role in the induction of severe cognition deficits in many psychiatric disorders. In this review, we summarize research advances in the underlying mechanisms and physiological functions of neural oscillations. We also discuss the abnormal changes of sharp wave-ripple, gamma oscillation and sleep spindle oscillation in major depressive disorder, schizophrenia and Alzheimer's disease, etc. Finally, the application potential of neural oscillations as clinical diagnosis and treatment targets is evaluated and prospected.
Depressive Disorder, Major ; Hippocampus/physiology* ; Humans ; Neurons ; Sleep/physiology*

OBJECTIVETo analyze the sleep electrophysiological changes and the sleep structure changes in children with bruxism by use of the polysomnography.

METHODSTwelve children with severe bruxism and 11 children who had no systemic diseases or sleep disorders were selected for polysomnography.

RESULTSThe proportion of nonrapid eye movements sleep (NREMS)II and NREMS IV stages in bruxism group were (45.7 ± 7.1)% and (19.2 ± 4.9)%, while the control group were (52.9 ± 5.8)% and (13.3 ± 5.3)% respectively. The sleep efficiency and the latency of sleep were (84.0 ± 8.0)% and (39.33 ± 28.73) min in bruxism group, and (94.0 ± 3.7)% and (10.27 ± 7.57) min in the control group respectively. The difference was statistically significant.

CONCLUSIONSThe sleep structure is inordinate in bruxism children.

Case-Control Studies ; Child ; Child, Preschool ; Female ; Humans ; Male ; Polysomnography ; Sleep ; physiology ; Sleep Bruxism ; physiopathology ; Sleep Stages ; physiology ; Sleep, REM ; physiology

BACKGROUNDExcessive daytime sleepiness (EDS) is often associated with obstructive sleep apnea hypopnea syndrome (OSAHS) and contributes to a number of comorbidities in these patients. Therefore, early detection of EDS is critical in disease management. We examined the association between Epworth Sleepiness Scale (ESS) and multiple sleep latency test (MSLT) and diagnostic accuracy of ESS in assessing EDS in OSAHS patients.

METHODSThe ESS, MSLT and overnight polysomnography were administered to 107 Chinese patients to assess EDS and its correlations with polysomnographic parameters. The diagnostic accuracy of ESS in classifying EDS (mean sleep latency (MSL) ≤ 10 minutes) was evaluated by calculating the area under ROC curve.

RESULTSAs the severity of OSAHS increased, MSL decreased with increase in ESS score. Conversely, patients with worsening EDS (shorter MSL) were characterized by advanced nocturnal hypoxaemia and sleep disruption compared to those with normal MSL, suggesting EDS is associated with more severe OSAHS. There was a negative correlation between ESS score and MSL and both moderately correlated with some polysomnographic nocturnal hypoxaemic parameters. The area under ROC curve of ESS for identifying EDS was 0.80 (95% CI: 0.71 to 0.88) and ESS score ≥ 12 provided the best predictive value with a sensitivity of 80% and specificity of 69%.

CONCLUSIONThe ESS score moderately correlates with MSL and our ROC study supports ESS as a screening strategy for assessing EDS in OSAHS.

Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Polysomnography ; Sleep ; physiology ; Sleep Apnea, Obstructive ; physiopathology ; Sleep Stages ; physiology