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Journal Article
Research Support, Non-U.S. Gov't
Slow eye movements and EEG power spectra during wake-sleep transition.
Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology 2000 December
OBJECTIVE: The aim of the present study was to assess the relationship between slow eye movements (SEMs) and quantitative EEG measures during the wake-sleep transition.
METHODS: Individual distributions were aligned with respect to the onset of stage 2 to provide an unequivocal hallmark of the beginning of sleep and to reduce the sources of variability in this transition. The relationship between EEG spectral powers and EOG changes was assessed by means of product-moment correlations and bootstrap analyses for individual time series, and by means of a multiple regression analysis for the entire sample.
RESULTS: Results on the individual distributions as well as on averaged data showed a tight relationship between SEMs and EEG changes, negative across the 1-14 Hz frequency range and positive across the 15-30 Hz one. Spectral power in the sigma EEG band, that corresponds to the frequency at the phasic sleep spindles, resulted as the best predictor of SEM variations, being negatively correlated to the EOG changes. With respect to the other EEG frequency bands, the split half of the distributions with respect to stage 2 onset indicated a positive correlation of delta power with the increase of SEM activity before sleep onset, and of beta power with the decrease of SEMs after sleep onset.
CONCLUSIONS: These results seem to suggest that sleep spindles could trigger the reduction and the final disappearance of slow eye movements in the late part of the wake-sleep transition.
METHODS: Individual distributions were aligned with respect to the onset of stage 2 to provide an unequivocal hallmark of the beginning of sleep and to reduce the sources of variability in this transition. The relationship between EEG spectral powers and EOG changes was assessed by means of product-moment correlations and bootstrap analyses for individual time series, and by means of a multiple regression analysis for the entire sample.
RESULTS: Results on the individual distributions as well as on averaged data showed a tight relationship between SEMs and EEG changes, negative across the 1-14 Hz frequency range and positive across the 15-30 Hz one. Spectral power in the sigma EEG band, that corresponds to the frequency at the phasic sleep spindles, resulted as the best predictor of SEM variations, being negatively correlated to the EOG changes. With respect to the other EEG frequency bands, the split half of the distributions with respect to stage 2 onset indicated a positive correlation of delta power with the increase of SEM activity before sleep onset, and of beta power with the decrease of SEMs after sleep onset.
CONCLUSIONS: These results seem to suggest that sleep spindles could trigger the reduction and the final disappearance of slow eye movements in the late part of the wake-sleep transition.
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