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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...

Seizures: Classification

Seizures: Classification

Epilepsy is primarily characterized by unpredictable seizures, either provoked by an identifiable factor, such as injury or illness, or unprovoked, occurring spontaneously without apparent cause.
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types:

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Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

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Published on: December 18, 2016

Graph theory in paediatric epilepsy: A systematic review.

Raffaele Falsaperla^1,2, Giovanna Vitaliti³, Simona Domenica Marino²

¹Neonatal Intensive Care Unit, San Marco Hospital, University Hospital Policlinico "G. Rodolico-San Marco", Catania, Italy.

Dialogues in Clinical Neuroscience

|July 21, 2022

Summary

Childhood epilepsy may disrupt brain network development and cognition. Graph theory analysis of electroencephalography (EEG) data offers insights into functional dynamic connectivity in pediatric epilepsy.

Keywords:

Graph theory brain network childhood paediatric epilepsy

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Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

Area of Science:

Neuroscience
Network Science
Graph Theory

Background:

Network science and graph theory offer insights into brain function across developmental stages.
The impact of childhood epilepsy on brain network organization and cognition is not well understood.
Early-onset neurological disorders can disrupt neurodevelopment during critical maturation periods.

Purpose of the Study:

To systematically review the application of graph theory in analyzing functional dynamic connectivity in pediatric epilepsy.
To understand how early-onset epilepsy affects brain network development and cognition over time.
To explore the utility of graph theoretical analysis in childhood epilepsy research.

Main Methods:

Systematic review of studies applying graph theory to functional dynamic connectivity.
Analysis focused on electroencephalographic (EEG) data in pediatric epilepsy.
Examination of brain network organization in children with new-onset epilepsy.

Main Results:

Graph theoretical analysis is increasingly applied to understand brain networks in developmental stages.
EEG-based functional dynamic connectivity analysis using graph theory shows promise in pediatric epilepsy research.
The review highlights the potential of graph theory to detect network abnormalities in early childhood epilepsy.

Conclusions:

Graph theory provides valuable tools for investigating brain network organization in pediatric epilepsy.
Early assessment of brain networks in children with epilepsy is crucial for understanding long-term effects.
Further research using graph theory can enhance our understanding of neurodevelopmental trajectories in childhood epilepsy.