2006
DOI: 10.1016/j.jneumeth.2005.12.014
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Measuring clusters of spontaneous spike-wave discharges in absence epileptic rats

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Cited by 10 publications
(6 citation statements)
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“…The observed decaying hazard rates of the durations of the inter-SWD intervals in the saline group suggest that, whenever an SWD occurs, it might be easier for a subsequent SWD to occur. This would suggest that SWDs are likely to cluster, which is supported by the data of Midzyanovskaya et al (2006). After vigabatrin, the overall probability that an SWD will start is increased, as was shown by the overall higher value of the hazard rates of the duration of the inter-SWD intervals.…”
Section: Discussionsupporting
confidence: 58%
See 1 more Smart Citation
“…The observed decaying hazard rates of the durations of the inter-SWD intervals in the saline group suggest that, whenever an SWD occurs, it might be easier for a subsequent SWD to occur. This would suggest that SWDs are likely to cluster, which is supported by the data of Midzyanovskaya et al (2006). After vigabatrin, the overall probability that an SWD will start is increased, as was shown by the overall higher value of the hazard rates of the duration of the inter-SWD intervals.…”
Section: Discussionsupporting
confidence: 58%
“…The observed decaying hazard rates of the durations of the inter‐SWD intervals in the saline group suggest that, whenever an SWD occurs, it might be easier for a subsequent SWD to occur. This would suggest that SWDs are likely to cluster, which is supported by the data of Midzyanovskaya et al . (2006).…”
Section: Discussionmentioning
confidence: 99%
“…Each distribution deviated significantly from the expected beta distribution (p<0.0001, Anderson-Darling goodness of fit test). Clustering of SWDs is yet a further characteristic feature of absence seizures (Midzyanovskaya et al 2006). …”
Section: Resultsmentioning
confidence: 99%
“…A number of factors influencing the probability of seizure occurrence in this strain have already been explored, such as the age of the rats [17,18], the circadian timing system [19,20], and sex hormones [21]. Mathematical approaches were also used to describe the timing of seizures' occurrence such as time series analysis of a binary SWDs' signal constructed from long-term EEG recordings [22], the hazard rate, the conditional probability that a seizure starts in the time interval [t,t Δ], given that no seizure has started in the time interval [0, t] [23], and whether principles of intermittency (irregular alternation of phases of apparently periodic and chaotic dynamics) can be demonstrated [24,25]. Other approaches that were used to predict the SWDs' occurrence were based on time-frequency analyses of cortical and thalamic preictal EEG [26], multichannel network analysis of preictal EEG correlates [27][28][29][30], and multichannel synchronization analysis [15].…”
Section: Introductionmentioning
confidence: 99%