ArticleScientific reports2019
Statistical Properties and Predictability of Extreme Epileptic Events.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Spike-wave discharges are uncoupled with cognitive outcome in aged Long-Evans rats.Psychopharmacology · 2026Article
- Pentylenetetrazole kindling impairs place recognition memory associated with suppressing proBDNF-mediated neural information flows at the hippocampal CA3-CA1 synapses.Frontiers in pharmacology · 2026Article
- Characterization of Anesthesia in Rats from EEG in Terms of Long-Range Correlations.Diagnostics (Basel, Switzerland) · 2023Article
- Memristive Neural Networks for Predicting Seizure Activity.Sovremennye tekhnologii v meditsine · 2023Article
- Extended Detrended Fluctuation Analysis of Coarse-Grained Time Series.Diagnostics (Basel, Switzerland) · 2022Article
- Application of Machine Learning Methods for Epilepsy Risk Ranking in Patients with Hematopoietic Malignancies Using.Journal of personalized medicine · 2022Article
- Extreme value theory inspires explainable machine learning approach for seizure detection.Scientific reports · 2022Article
- Prediction of Seizure Recurrence. A Note of Caution.Frontiers in neurology · 2021Article
- Age-Related Distinctions in EEG Signals during Execution of Motor Tasks Characterized in Terms of Long-Range Correlations.Sensors (Basel, Switzerland) · 2020Article
- Article
- Detection of Postictal Generalized Electroencephalogram Suppression: Random Forest Approach.JMIR medical informatics · 2020Article
- From Novel Technology to Novel Applications: Comment on "An Integrated Brain-Machine Interface Platform With Thousands of Channels" by Elon Musk and Neuralink.Journal of medical Internet research · 2019Article
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Authors and funding
10 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The use of extreme events theory for the analysis of spontaneous epileptic brain activity is a relevant multidisciplinary problem. It allows deeper understanding of pathological brain functioning and unraveling mechanisms underlying the epileptic seizure emergence along with its predictability. The latter is a desired goal in epileptology which might open the way for new therapies to control and prevent epileptic attacks. With this goal in mind, we applied the extreme event theory for studying statistical properties of electroencephalographic (EEG) recordings of WAG/Rij rats with genetic predisposition to absence epilepsy. Our approach allowed us to reveal extreme events inherent in this pathological spiking activity, highly pronounced in a particular frequency range. The return interval analysis showed that the epileptic seizures exhibit a highly-structural behavior during the active phase of the spiking activity. Obtained results evidenced a possibility for early (up to 7 s) prediction of epileptic seizures based on consideration of EEG statistical properties.
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