PURPOSE: The EEG pattern of epilepsy with continuous spike-waves during slow wave sleep (CSWSS) is characterized by an almost continuous activation of spike-and-slow-wave complexes during nREM sleep with a marked reduction of EEG abnormalities during REM sleep and the awake state. Experimental studies indicate that normal sleep oscillations that during nREM sleep lead to the appearance of spindles and delta waves on scalp EEG might develop into paroxysmal synchronization. Spectral analysis enables the quantitative description of the dynamics of delta (Delta Activity, DA, 0.5-4.5 Hz) and sigma activity (SA, 12-16 Hz) and can be used to assess the relationship between SA, DA and epileptiform discharges (EDs) during sleep. METHODS: We analyzed the EDs distribution during sleep in five children affected by CSWSS. We used a model of the evolution of power of DA and SA to which the time series of EDs could be fitted. RESULTS: We found a high and positive correlation between EDs and SA. DA resulted negatively correlated with EDs. CONCLUSION: Our data suggest that neural mechanisms involved in the generation of sleep spindles facilitate EDs production in the CSWSS syndrome. Such a mechanism seems to be an age related phenomenon shared by other epileptic syndromes of childhood.
Distribution of epileptiform discharges during nREM sleep in the CSWSS syndrome: relationship with sigma and delta activities.
De Carli F;
2001
Abstract
PURPOSE: The EEG pattern of epilepsy with continuous spike-waves during slow wave sleep (CSWSS) is characterized by an almost continuous activation of spike-and-slow-wave complexes during nREM sleep with a marked reduction of EEG abnormalities during REM sleep and the awake state. Experimental studies indicate that normal sleep oscillations that during nREM sleep lead to the appearance of spindles and delta waves on scalp EEG might develop into paroxysmal synchronization. Spectral analysis enables the quantitative description of the dynamics of delta (Delta Activity, DA, 0.5-4.5 Hz) and sigma activity (SA, 12-16 Hz) and can be used to assess the relationship between SA, DA and epileptiform discharges (EDs) during sleep. METHODS: We analyzed the EDs distribution during sleep in five children affected by CSWSS. We used a model of the evolution of power of DA and SA to which the time series of EDs could be fitted. RESULTS: We found a high and positive correlation between EDs and SA. DA resulted negatively correlated with EDs. CONCLUSION: Our data suggest that neural mechanisms involved in the generation of sleep spindles facilitate EDs production in the CSWSS syndrome. Such a mechanism seems to be an age related phenomenon shared by other epileptic syndromes of childhood.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
