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Epilepsy and Seizures: Overview

Epilepsy and Seizures: Overview

Epilepsy is a chronic neurological disease marked by recurrent, unpredictable seizures. These seizures are caused by abnormal electrical discharges in the brain, leading to behavior, sensation, or consciousness alterations. They can also cause transient impairment of awareness, interfering with daily activities.
Various factors can trigger epilepsy, including genetic factors, brain damage, metabolic causes, and unknown etiology. Diagnosis of epilepsy involves electroencephalography (EEG), which...

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Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

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The ENIGMA-Epilepsy working group: Mapping disease from large data sets.

Sanjay M Sisodiya^1,2, Christopher D Whelan³, Sean N Hatton⁴

¹Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.

Human Brain Mapping

|May 30, 2020

Summary

This summary is machine-generated.

ENIGMA-Epilepsy enhances neuroscience research by increasing sample sizes for epilepsy studies. This collaborative effort utilizes advanced MRI techniques to better understand brain processes and improve patient care for this common neurological disorder.

Keywords:

DTI MRI covariance deep learning event-based modeling gene expression genetics imaging quantitative rsfMRI

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Area of Science:

Neuroscience
Neurology
Medical Imaging

Background:

Epilepsy is a prevalent neurological disorder with diverse presentations.
Magnetic Resonance Imaging (MRI) is crucial for understanding epilepsy pathophysiology.
Previous smaller studies identified key imaging phenomena.

Purpose of the Study:

To strengthen epilepsy neuroscience through large-scale collaborative research.
To leverage existing ENIGMA Consortium infrastructure and methods.
To foster collaboration among scientists and clinicians for robust epilepsy research.

Main Methods:

Utilizing structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI).
Employing advanced analytical techniques like structural covariance and event-based modeling.
Reviewing published, current, and future ENIGMA-Epilepsy projects.

Main Results:

Focus on age of onset and duration-related imaging features.
Phenomena-specific research on epilepsy syndromes and phenotypes.
Multimodal analyses and deep learning approaches for disease progression.

Conclusions:

ENIGMA-Epilepsy aims to significantly advance the understanding of epilepsy.
The project encourages broader participation to expand research capabilities.
Future work will focus on multimodal data and advanced computational methods.