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Epilepsy, Absence

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Using Relevance Feedback to Distinguish the Changes in EEG During Different Absence Seizure Phases.

Clinical EEG and neuroscience
We carried out a series of statistical experiments to explore the utility of using relevance feedback on electroencephalogram (EEG) data to distinguish between different activity states in human absence epilepsy. EEG recordings from 10 patients with ...

Modeling spike-wave discharges by a complex network of neuronal oscillators.

Neural networks : the official journal of the International Neural Network Society
PURPOSE: The organization of neural networks and the mechanisms, which generate the highly stereotypical for absence epilepsy spike-wave discharges (SWDs) is heavily debated. Here we describe such a model which can both reproduce the characteristics ...

Graph-theory based degree centrality combined with machine learning algorithms can predict response to treatment with antiepileptic medications in children with epilepsy.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND AND PURPOSE: The purpose of the current study is to detect changes of graph-theory-based degree centrality (DC) and their relationship with the clinical treatment effects of anti-epileptic drugs (AEDs) for patients with childhood absence e...

An rs-fMRI based neuroimaging marker for adult absence epilepsy.

Epilepsy research
OBJECTIVE: Approximately 20-30 % of epilepsy patients exhibit negative findings on routine magnetic resonance imaging, and this condition is known as nonlesional epilepsy. Absence epilepsy (AE) is a prevalent form of nonlesional epilepsy. This study ...