Published September 5, 2025
| Version v1
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Machine Learning Analysis Reveals Dynamic Remodeling of Hippocampal Interictal Spikes in Temporal Lobe Epilepsy
Authors/Creators
- 1. Department of Neurology, Mayo Clinic, Rochester, United States
- 2. Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
- 3. Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
Description
Interictal epileptiform spikes (IESs) are transient neural events that reflect the underlying epileptic network. We employed machine learning (ML) techniques to investigate the dynamic evolution of IES morphology within individual hippocampal channels across sleep-wake states and postictal periods in patients with drug-resistant temporal lobe epilepsy (TLE).
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CIIRC_2RP_43_Machine Learning Analysis Reveals.pdf
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Additional details
References
- Funded by the European Union. This work was supported by the European Union (CLARA project No.101136607) and National Institutes of Health grant number: R01NS09288203 to R01-NS092882