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Epilepsy Behav. 2019 Jul;96:200-209. doi: 10.1016/j.yebeh.2019.04.012. Epub 2019 May 30.

Can absence seizures be predicted by vigilance states?: Advanced analysis of sleep-wake states and spike-wave discharges' occurrence in rats.

Author information

1
Malopolska Centre of Biotechnology, Jagiellonian University in Krakow, Poland; Department of Neurophysiology and Chronobiology, Institute of Zoology and Biomedical Research, Jagiellonian University in Krakow, Poland. Electronic address: magdalena.smyk@gmail.com.
2
Saratov State University, Saratov, Russia; Saratov Branch of Kotel'nikov Institute of Radio Engineering and Electronics, Saratov, Russia. Electronic address: ivssci@gmail.com.
3
Yuri Gagarin State Technical University of Saratov, Saratov, Russia; Saratov Branch of Kotel'nikov Institute of Radio Engineering and Electronics, Saratov, Russia. Electronic address: bobrichek@mail.ru.
4
Donders Centre of Cognition, Radboud University, Nijmegen, the Netherlands. Electronic address: g.vanluijtelaar@donders.ru.nl.
5
Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica N.V., Beerse, Belgium. Electronic address: WDRINKEN@its.jnj.com.

Abstract

Spike-wave discharges (SWDs) are the main manifestation of absence epilepsy. Their occurrence is dependent on the behavioral state, and they preferentially occur during unstable vigilance periods. The present study investigated whether the occurrence of SWDs can be predicted by the preceding behavioral state and whether this relationship is different between the light and the dark phases of the 24-h day. Twenty-four-hour (12:12 light/dark phases) electroencephalographic (EEG) recordings of 12 Wistar Albino Glaxo, originally bred in Rijswijk (WAG/Rij) rats, a well-known genetic model of absence epilepsy, were analyzed and transformed into sequences of 2-s length intervals of the following 6 possible states: active wakefulness (AW), passive wakefulness (PW), deep slow-wave sleep (DSWS), light slow-wave sleep (LSWS), rapid eye movement (REM) sleep, and SWDs, given discrete series of categorical data. Probabilities of all transitions between states and Shannon entropy of transitions were calculated for the light and dark phases separately and statistically analyzed. Common differences between the light and the dark phases were found regarding the time spent in AW, LSWS, DSWS, and SWDs. The most probable transitions were that AW was preceded and followed by PW and vice versa regardless of the phase of the photoperiod. A similar relationship was found for light and deep slow-wave sleep. The most probable transitions to and from SWDs were AW and LSWS, respectively, with these transition likelihoods being consistent across both circadian phases. The second most probable transitions around SWDs appeared more variable between light and dark. During the light phase, SWDs occurred around PW and participated exclusively in sleep initiation; in the dark phase, SWDs were seen on both, ascending and descending steps towards and from sleep. Conditional Shannon entropy showed that AW and DSWS are the most predictable events, while the possible prediction horizon of SWDs is not larger than 4 s and despite the higher occurrence of SWDs in the dark phase, did not differ between phases. It can be concluded that although SWDs show a stable, strong circadian rhythm with a peak in number during the dark phase, their occurrence cannot be reliably predicted by the preceding behavioral state, except at a very short time base.

KEYWORDS:

Absence epilepsy; Conditional Shannon entropy; Predictability; Sleep–wake states; Spike–wave discharges; WAG/Rij rats

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