0000000000606190
AUTHOR
J. Röschke
Macrostructural EEG characterization based on nonparametric change point segmentation: application to sleep analysis
In the present investigation a new methodology for macrostructural EEG characterization based on automatic segmentation has been applied to sleep analysis. A nonparametric statistical approach for EEG segmentation was chosen, because it minimizes the need for a priori information about a signal. The method provides the detection of change-points i.e. boundaries between quasi-stationary EEG segments based on the EEG characteristics within four fundamental frequency bands (delta, theta, alpha and beta). Polysomnographic data of 18 healthy subjects were analyzed. Our findings show that nonparametric change-point segmentation in combination with cluster analysis enables us to obtain a clear pic…
Different phase relationships between EEG frequency bands during NREM and REM sleep.
Phase relationships between distinct frequency bands of the sleep electroencephalogram (EEG) were studied in healthy subjects using cross-correlation coefficients, both over the entire night and separately for nonrapid eye movement (NREM) and rapid eye movement (REM) sleep. Over the entire night, a large positive correlation developed within high- and low-frequency bands, while a negative correlation emerged between low- and high-frequency bands, reflecting their reciprocal temporal course. More detailed analysis revealed different phase relationships during NREM and REM sleep. Findings during NREM were similar to the entire night. However, during REM, a large increase of the correlation be…
Estimation of the dimensionality of sleep-EEG data in schizophrenics
Deterministic chaos could be regarded as a healthy flexibility of the human brain necessary for correct neuronal operations. Several investigations have demonstrated that in healthy subjects the dimensionality of REM sleep is much higher than that of slow wave sleep (SWS). We investigated the sleep-EEG of schizophrenic patients with methods from nonlinear system theory in order to estimate the dynamic properties of CNS. We hypothesized that schizophrenics would reveal alterations of their dynamic EEG features indicating impaired information processing. In 11 schizophrenic patients, the EEG's dimensionality during sleep stages II and REM was reduced. We suggest that such lower dimensional ch…
A Nonlinear Approach to Brain Function: Deterministic Chaos and Sleep EEG
In order to perform a nonlinear dimensional analysis of the sleep electroencephalogram (EEG), we applied an algorithm proposed by Grassberger and Procaccia to calculate the correlation dimension D2 of different sleep stages under Lorazepam medication versus placebo. This correlation dimension characterizes the dynamics of the sleep EEG and it estimates the degrees of freedom of the signal under study. We demonstrate that slow-wave sleep depicts a much smaller dimensionality than light or rapid eye movement (REM) sleep, and that Lorazepam does not alter the EEG's dimensionality except in stage II and REM.