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Sink into the epileptogenic zone: findings from directed SEEG functional connectivity decomposition.
Brain
September 2024
Epileptology and Cerebral Rhythmology Department (member of the ERN EpiCARE Network), APHM, Timone Hospital, 13005 Marseille, France.
Source-sink connectivity: a novel interictal EEG marker for seizure localization.
Brain
November 2022
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist.
View Article and Find Full Text PDFLocalizing epileptogenic tissues in epilepsy: are we losing (the) focus?
Brain
November 2022
Department of Neurology, Perlman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
This scientific commentary refers to ‘Source-sink connectivity: a novel interictal EEG marker for seizure localization’ by Gunnarsdottir . (https://doi.org/10.
View Article and Find Full Text PDFSources and Sinks in Interictal iEEG Networks: An iEEG Marker of the Epileptogenic Zone.
Annu Int Conf IEEE Eng Med Biol Soc
November 2021
Around 30% of epilepsy patients have seizures that cannot be controlled with medication. The most effective treatments for medically resistant epilepsy are interventions that surgically remove the epileptogenic zone (EZ), the regions of the brain that initiate seizure activity. A precise identification of the EZ is essential for surgical success but unfortunately, current success rates range from 20-80%.
View Article and Find Full Text PDFMachine learning approach to detect focal-onset seizures in the human anterior nucleus of the thalamus.
J Neural Eng
November 2020
Department of Neurology, University of Alabama at Birmingham, CIRC 312, 1719 6th Avenue South, Birmingham, AL 35294, United States of America.
There is an unmet need to develop seizure detection algorithms from brain regions outside the epileptogenic cortex. The study aimed to demonstrate the feasibility of classifying seizures and interictal states from local field potentials (LFPs) recorded from the human thalamus-a subcortical region remote to the epileptogenic cortex. We tested the hypothesis that spectral and entropy-based features extracted from LFPs recorded from the anterior nucleus of the thalamus (ANT) can distinguish its state of ictal recruitment from other interictal states (including awake, sleep).
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