1993
DOI: 10.1159/000119017
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Cortical and Subcortical EEG in Relation to Sleep-Wake Behavior in Mammalian Species

Abstract: In humans and several other mammals, a quantitative EEG analysis has been used to study the regulation of sleep-wake behavior. In all mammalian species studied, cortical EEG recorded during non-REM sleep (NREMS) is characterized by the occurrence of spindles and high voltage, slow waves (0.5-4.0 Hz). Furthermore, slow-wave activity (SWA) is low at the beginning of a NREM episode and it rises in the course of a NREM episode. The rise rate and the maximal level of SWA are a monotonic function of the duration of … Show more

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Cited by 15 publications
(11 citation statements)
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“…The duration of any data set was never less than 60 s (30 sweeps) and most lasted about 200 s (100 sweeps). The EEG patterns were similar to those described previously for cats under the same type of anaesthesia (Ikeda & Wright, 1974; Funke & Eysel, 1992), and the changes in the power of δ waves were similar to those found in the behaving cat (Lancel et al 1992; Lancel, 1993) but with a less pronounced activity in the high‐frequency range (above 15 Hz). In a majority of the dLGN relay cells recorded, the cell type (X, Y, on or off) could be determined, but for the results described here all data sets were pooled because we did not find any significant difference between cell types.…”
Section: Resultssupporting
confidence: 84%
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“…The duration of any data set was never less than 60 s (30 sweeps) and most lasted about 200 s (100 sweeps). The EEG patterns were similar to those described previously for cats under the same type of anaesthesia (Ikeda & Wright, 1974; Funke & Eysel, 1992), and the changes in the power of δ waves were similar to those found in the behaving cat (Lancel et al 1992; Lancel, 1993) but with a less pronounced activity in the high‐frequency range (above 15 Hz). In a majority of the dLGN relay cells recorded, the cell type (X, Y, on or off) could be determined, but for the results described here all data sets were pooled because we did not find any significant difference between cell types.…”
Section: Resultssupporting
confidence: 84%
“…With the use of the sliding time‐window analysis we found two different patterns of variation in the spectral composition of the EEG that were correlated with changes in geniculate visual activity: (i) slow steady increments or decrements in the EEG‐PR lasting up to minutes, termed ‘slow gradations’ and, (ii) fast, periodic changes within a few seconds which occurred in a repetitive manner for longer periods called ‘oscillations’. These results were obtained from anaesthetized cats, but may also hold for a behaving animal since cats anaesthetized with nitrous oxide and halothane show spontaneous changes in EEG pattern (Ikeda & Wright, 1974; Livingstone & Hubel, 1981; Sawai et al 1988; Funke & Eysel, 1992) which are comparable with changes of the EEG signal of the behaving cat (Lancel, 1993 and discussion below).…”
Section: Discussionmentioning
confidence: 55%
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“…The reason for this may be related to spontaneous changes in EEG. Even during halothane/nitrous oxide anaesthesia, the endogenous sleep–wake rhythm of the cat goes on, leading to spontaneous transitions between high and low delta states about every 30 min (Lancel, 1993) which are not under the control of the experimenter. Thus, the likelihood that an internal state change happens at the same time as a change induced by rTMS is statistically lower for short (1 or 5 min) than for long (20 min) rTMS applications.…”
Section: Discussionmentioning
confidence: 99%
“…Nevertheless, some fluctuations of response strength and spectral composition of the EEG are always present (Li et al 1999). Complete recording sessions including control measurements, drug applications with different ejection currents and interleaved recoveries, all tested for different stimulus features, lasted for several hours and could be accompanied by spontaneous changes in the EEG pattern that followed the natural sleep‐wake cycle of the cat (Lancel, 1993). Discarding those records with too dissimilar EEG patterns considerably further reduced the sample of usable data.…”
Section: Resultsmentioning
confidence: 99%