Rhythmic activity in EEG and sleep in rats with absence epilepsy.

This study examines the hypothesis that absence epilepsy is accompanied by disturbances of rhythmic activity in EEG during sleep. Sleep-wake architecture and time-frequency parameters of EEG were analyzed during drowsiness and sleep in WAG/Rij rats with genetic predisposition to absence epilepsy. The incidence of seizures varied in a group of 10 rats, in which 5 individuals did not develop epileptic discharges in their EEG (asymptomatic rats). In contrast to asymptomatic, symptomatic subjects (1) displayed less percentage of wakefulness EEG pattern and more non-REM sleep, (2) showed higher beta and less delta EEG power in frontal cortex during non-REM sleep. Mid-frequency oscillations, such as sleep spindles and 5-9 Hz oscillations, were detected in EEG automatically and underwent time-frequency analysis by means of skeletons of wavelet surfaces. Some mid-frequency oscillations showed "complex" frequency structure, consisting of the dominant and subdominant components. "Complex" sleep spindles more frequently appeared in asymptomatic rats than in symptomatic, whereas the dominant frequency of these spindles in symptomatic rats was higher than in asymptomatic (12.7 vs 11.9 Hz). In general, low-frequency components were readily integrated in sleep spindles in asymptomatic WAG/Rij rats, and decrease in number of "complex" sleep spindles may be associated with epileptic phenotype.

Age-Dependent Increase of Absence Seizures and Intrinsic Frequency Dynamics of Sleep Spindles in Rats.

The risk of neurological diseases increases with age. In WAG/Rij rat model of absence epilepsy, the incidence of epileptic spike-wave discharges is known to be elevated with age. Considering close relationship between epileptic spike-wave discharges and physiologic sleep spindles, it was assumed that age-dependent increase of epileptic activity may affect time-frequency characteristics of sleep spindles. In order to examine this hypothesis, electroencephalograms (EEG) were recorded in WAG/Rij rats successively at the ages 5, 7, and 9 months. Spike-wave discharges and sleep spindles were detected in frontal EEG channel. Sleep spindles were identified automatically using wavelet-based algorithm. Instantaneous (localized in time) frequency of sleep spindles was determined using continuous wavelet transform of EEG signal, and intraspindle frequency dynamics were further examined. It was found that in 5-months-old rats epileptic activity has not fully developed (preclinical stage) and sleep spindles demonstrated an increase of instantaneous frequency from beginning to the end. At the age of 7 and 9 months, when animals developed matured and longer epileptic discharges (symptomatic stage), their sleep spindles did not display changes of intrinsic frequency. The present data suggest that age-dependent increase of epileptic activity in WAG/Rij rats affects intrinsic dynamics of sleep spindle frequency.

Time-frequency characteristics and dynamics of sleep spindles in WAG/Rij rats with absence epilepsy.

In rat models of absence epilepsy, epileptic spike-wave discharges appeared in EEG spontaneously, and the incidence of epileptic activity increases with age. Spike-wave discharges and sleep spindles are known to share common thalamo-cortical mechanism, suggesting that absence seizures might affect some intrinsic properties of sleep spindles. This paper examines time-frequency EEG characteristics of anterior sleep spindles in non-epileptic Wistar and epileptic WAG/Rij rats at the age of 7 and 9 months. Considering non-stationary features of sleep spindles, EEG analysis was performed using Morlet-based continuous wavelet transform. It was found, first, that the average frequency of sleep spindles in non-epileptic Wistar rats was higher than in WAG/Rij (13.2 vs 11.2 Hz). Second, the instantaneous frequency ascended during a spindle event in Wistar rats, but it was constant in WAG/Rij. Third, in WAG/Rij rats, the number and duration of epileptic discharges increased in a period between 7 and 9 months of age, but duration and mean value of intra-spindle frequency did not change. In general, age-dependent aggravation of absence seizures in WAG/Rij rats did not affect EEG properties of sleep spindles; it was suggested that pro-epileptic changes in thalamo-cortical network in WAG/Rij rats might prevent dynamic changes of sleep spindles that were detected in Wistar.

On-off intermittency of thalamo-cortical oscillations in the electroencephalogram of rats with genetic predisposition to absence epilepsy.

Spike-wave discharges (SWD) are electroencephalographic hallmarks of absence epilepsy. SWD are known to originate from thalamo-cortical neuronal network that normally produces sleep spindle oscillations. Although sleep spindles and SWD are considered as thalamo-cortical oscillations, functional relationship between them is not obvious. The present study describes temporal dynamics of SWD and sleep spindles as determined in 24h EEG recorded in WAG/Rij rat model of absence epilepsy. SWD, sleep spindles (10-15 Hz) and 5-9 Hz oscillations were automatically detected in EEG using wavelet-based algorithm. It was found that non-linear dynamics of SWD fitted well to the law of 'on-off intermittency'. Sleep spindles also demonstrated 'on-off intermittency', in contrast to 5-9 Hz oscillations, whose dynamics could not be classified as having any known type of non-linear behavior. Intermittency in sleep spindles and SWD implies that (1) temporal dynamics of these oscillations are deterministic in nature, and (2) it might be controlled by a system-level mechanism responsible for circadian modulation of neuronal network activity.

Sleep spindles and spike-wave discharges in EEG: Their generic features, similarities and distinctions disclosed with Fourier transform and continuous wavelet analysis.

Epileptic activity in the form of spike-wave discharges (SWD) appears in the electroencephalogram (EEG) during absence seizures. A relationship between SWD and normal sleep spindles is often assumed. This study compares time-frequency parameters of SWD and sleep spindles as recorded in the EEG in the WAG/Rij rat model of absence epilepsy. Fast Fourier transformation and continuous wavelet transformation were used for EEG analysis. Wavelet analysis was performed in non-segmented full-length EEG. A specific wavelet-based algorithm was developed for the automatic identification of sleep spindles and SWD. None of standard wavelet templates provided precise identification of all sleep spindles and SWD in the EEG and different wavelet templates were imperative in order to accomplish this task. SWD were identified with high probability using standard Morlet wavelet, but sleep spindles were identified using two types of customized adoptive 'spindle wavelets'. It was found that (1) almost 100% of SWD (but only 50-60% of spindles) were identified using the Morlet-based wavelet transform. (2) 82-91% of sleep spindles were selected using adoptive 'spindle wavelet 1' (template's peak frequency approximately 12.2 Hz), the remaining sleep spindles with 'spindle wavelet 2' (peak frequency approximately 20-25 Hz). (3) Sleep spindles and SWD were detected by the elevation of wavelet energy in different frequencies: SWD, in 30-50 Hz band, sleep spindles, in 7-14 Hz. It is concluded that the EEG patterns of sleep spindles and SWD belong to different families of phasic EEG events with different time frequency characteristics.