AIMC Topic: Epilepsy, Absence

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

Epilepsy research Jun 28, 2024
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 ...
Humans Adult Male Magnetic Resonance Imaging Epilepsy, Absence Brain Mapping Putamen Sensitivity and Specificity Support Vector Machine Thalamus Female Brain Young Adult Neuroimaging
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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 Jul 26, 2021
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...
Child Magnetic Resonance Imaging Brain Epilepsy, Absence Anticonvulsants Brain Mapping Machine Learning Humans
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Modeling spike-wave discharges by a complex network of neuronal oscillators.

Neural networks : the official journal of the International Neural Network Society Dec 13, 2017
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 ...
Epilepsy, Absence Humans Thalamus Neurons Action Potentials Somatosensory Cortex Disease Models, Animal Seizures Brain Electroencephalography Animals Neural Networks, Computer
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Using Relevance Feedback to Distinguish the Changes in EEG During Different Absence Seizure Phases.

Clinical EEG and neuroscience Sep 21, 2014
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 ...
Pattern Recognition, Automated Epilepsy, Absence Feedback Diagnosis, Differential Child Male Electroencephalography Female Machine Learning Young Adult Sensitivity and Specificity Diagnosis, Computer-Assisted Humans Disease Progression Reproducibility of Results Algorithms Adolescent
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