The study of the biological correlates of major depressive disorder (MDD) has received great impetus in recent years. Electroencephalographic (EEG) sleep measurements and the Dexamethasone Suppression Test (DST) have been among the most studied and productive of these biological correlates. Commonly described EEG sleep abnormalities in MDD include shortened rapid eye movement (REM) latency, inc...

Sleep loss has marked and selective effects on brain wave activity during subsequent recovery sleep. The electroencephalogram (EEG) responds to sleep deprivation with a relative increase in power density in the delta and theta range during non-rapid eye movement sleep. We investigated age-related changes of the EEG response to sleep deprivation along the antero-posterior axis (Fz, Cz, Pz, Oz) u...

The electroencephalogram (EEG) is the most common tool used in sleep research. This unit describes the methods for recording and analyzing the EEG. Detailed protocols describe recorder calibration, electrode application, EEG recording, and computer EEG analysis with power spectral analysis. Computer digitization of an analog EEG signal is discussed, along with EEG filtering and the parameters o...

Electroencephalographic (EEG) activity is a key indicator of a vigilance state, and quantitative analyses of the EEG have revealed profound differences both between and within vigilance states in humans. We summarize recent studies that investigated how the spectral composition of the EEG during the three vigilance states, that is, wakefulness, rapid eye movement (REM) and non-REM sleep, is mod...

Sleep quality is important, especially given the considerable number of sleep-related pathologies. The distribution of sleep stages is a highly effective and objective way of quantifying sleep quality. As a standard multi-channel recording used in the study of sleep, polysomnography (PSG) is a widely used diagnostic scheme in sleep medicine. However, the standard process of sleep clinical test,...

In this paper we report a detection method for different sleep stages and it is based on a single-channel electroencephalogram (EEG) system. The system is simple and can be easily setup in homes to perform sleep EEG recording, overnight sleep EEG automatic staging, and sleep quality evaluation. EEG data of 14 sleeping subjects were recorded through the entire night. All subjects were within the...

The paper integrates and adapts a range of advanced computational, mathematical and statistical tools for the purpose of analysis of neonate sleep stages based on extensive electroencephalogram (EEG) recordings. The level of brain dysmaturity of a neonate is difficult to assess by direct physical or cognitive examination, but dysmaturity is known to be directly related to the structure of neona...

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obta...

The analysis of electroencephalography (EEG) recordings has attracted increasing interest in recent decades and provides the pivotal scientific tool for researchers to quantitatively study brain activity during sleep, and has extended our knowledge of the fundamental mechanisms of sleep physiology. Conventional EEG analyses are mostly based on Fourier transform technique which assumes linearity...

EEG-microstates exploit spatio-temporal EEG features to characterize the spontaneous EEG as a sequence of a finite number of quasi-stable scalp potential field maps. So far, EEG-microstates have been studied mainly in wakeful rest and are thought to correspond to functionally relevant brain-states. Four typical microstate maps have been identified and labeled arbitrarily with the letters A, B, ...