EEG Cartography of a Night of Sleep and Dreams

Abstract

A night of sleep has been recorded under the conditions of a sleep laboratory. The subject was a woman of 55 years, well-trained in dream recall. The subject was awakened three times at the end of sleep cycles. EEG was monitored for 7 h with a 16-channel polygraph (REEGA 16, Alvar) connected to two systems of EEG cartography: minicomputers (HP Fourier Analyser 5451 C and HP 1000) and a microinformatic system (Cartovar, Alvar). A second 8-channel polygraph (Mini-huit, Alvar) was used in parallel for polygraphy (EOG, EMG, respiration, acto-gram, EKG). Based on immediate visual inspection of EEG and polygraphic tracings, 500 EEG recordings of selected epochs (of 6, 30 or 60 s length) have been quantified, submitted on-line to spectral analysis (on Cartovar) and stored on floppy disks for further printing of EEG maps. The 16 EEG channels were placed over the scalp according to the 10/20 system and following Giannitrapani’s placement. We have chosen a common average electrode. For each of the 500 EEG epochs, four EEG maps were edited (raw EEG between 0 and 30 Hz, 0 and 7 Hz, 8 and 12 Hz, 13 and 30 Hz). Each of these 2,000 maps has been checked visually in comparison with the polygraphic recordings for visual rejection of artifacts or transitory states. The remaining EEG epochs and EEG maps, scored by 2 independent trained sleep scorers, were classified into stages I, II, III-IV, and REM, apart from control runs of active wakefulness with eyes open (EO) and quiet wakefulness with eyes closed (EC), which were undertaken on mini- and microsystems of EEG analysis. Later, the spectral values of chosen EEG maps were averaged on Hewlett-Packard minicomputer, for each of the six chosen states. Typical EEG maps of EO, EC, I, II, III-IV and REM were computed, together with averaged EEG maps for each state. Dynamic and statistical analyses have also been computed together with correlations between the four types of EEG maps (raw EEG, 0–7, 8–12, 13–30 Hz).

Spectral and Topographic Microstructure of Brain Alpha Activity During Drowsiness at Sleep Onset and REM Sleep

“…Additionally, each sleep stage is characterized by a spectral structure with a specific topographic distribution over the scalp. This information has been conventionally captured through spectral analysis (Dumermuth et al., 1983) and brain-mapping techniques (Etevenon & Guillou, 1986; Maurer et al, 1989; Zeitlhofer et al, 1993) using long temporal series of brain activity. However, few researchers have studied the spectral features of the sleep microstructure, and most of them have been focused on sleep spindles.…”