Item does not contain fulltextBackground and objectives: In standard practice, sleep is classified into distinct stages by human observers according to specific rules as for instance specified in the AASM manual. We here show proof of principle for a conceptualization of sleep stages as attractor states in a nonlinear dynamical system in order to develop new empirical criteria for sleep stages. Methods: EEG (single channel) of two healthy sleeping participants was used to demonstrate this conceptualization. Firstly, distinct EEG epochs were selected, both detected by a MLR classifier and through manual scoring. Secondly, change point analysis was used to identify abrupt changes in the EEG signal. Thirdly, these detected change points were e...
Brain dynamics depicts an extremely complex energy landscape that changes over time, and its charact...
We propose that the critical function of sleep is to prevent uncontrolled neuronal feedback while al...
The recommendations for identifying sleep stages based on the interpretation of electrophysiological...
Background and objectives: In standard practice, sleep is classified into distinct stages by human o...
<div><p>The sleep onset process (SOP) is a dynamic process correlated with a multitude of behavioral...
The modern understanding of sleep is based on the classification of sleep into stages defined by the...
Complex systems are occasionally switching between several qualitatively different modes of behavior...
Falling asleep is a dynamical process that is poorly defined. The period preceding sleep, characteri...
The conventional approach to the analysis of human sleep uses a set of pre-defined rules to allocate...
Over the last decades sleep research has focused on epidemiological studies of how different factors...
The conventional staging classification reduces all patterns of sleep polysomnogram signals to a sma...
EEG source localization is an essential tool to reveal the cortical sources underlying brain oscilla...
Introduction: Enhanced characterization of sleep architecture, compared with routine polysomnographi...
The ability to react to events in the external world determines the fate of every living organism, ...
How do we lose and regain consciousness? The space between healthy wakefulness and unconsciousness e...
Brain dynamics depicts an extremely complex energy landscape that changes over time, and its charact...
We propose that the critical function of sleep is to prevent uncontrolled neuronal feedback while al...
The recommendations for identifying sleep stages based on the interpretation of electrophysiological...
Background and objectives: In standard practice, sleep is classified into distinct stages by human o...
<div><p>The sleep onset process (SOP) is a dynamic process correlated with a multitude of behavioral...
The modern understanding of sleep is based on the classification of sleep into stages defined by the...
Complex systems are occasionally switching between several qualitatively different modes of behavior...
Falling asleep is a dynamical process that is poorly defined. The period preceding sleep, characteri...
The conventional approach to the analysis of human sleep uses a set of pre-defined rules to allocate...
Over the last decades sleep research has focused on epidemiological studies of how different factors...
The conventional staging classification reduces all patterns of sleep polysomnogram signals to a sma...
EEG source localization is an essential tool to reveal the cortical sources underlying brain oscilla...
Introduction: Enhanced characterization of sleep architecture, compared with routine polysomnographi...
The ability to react to events in the external world determines the fate of every living organism, ...
How do we lose and regain consciousness? The space between healthy wakefulness and unconsciousness e...
Brain dynamics depicts an extremely complex energy landscape that changes over time, and its charact...
We propose that the critical function of sleep is to prevent uncontrolled neuronal feedback while al...
The recommendations for identifying sleep stages based on the interpretation of electrophysiological...