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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...

Epilepsy ll: Types

Epilepsy ll: Types

Recurrent seizures, stemming from abnormal electrical activity in the brain, are the defining characteristic of epilepsy, a chronic neurological condition. Because seizure features vary greatly, epilepsy is classified using two systems: by seizure type and by epilepsy syndromes. These classifications enable clinicians to describe seizure patterns and select suitable treatment strategies.I. Classification by Seizure Type1. Focal EpilepsyFocal epilepsy begins in one hemisphere of the brain.

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Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy

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Epileptic EEG: a comprehensive study of nonlinear behavior.

Moayed Daneshyari¹, L Lily Kamkar, Matin Daneshyari

¹Department of Technology, Elizabeth City State University, Elizabeth City, NC 27909, USA. mdaneshyari@mail.ecsu.edu

Advances in Experimental Medicine and Biology

|September 25, 2010

Summary

This study reveals that epileptic seizures alter brain activity, making it less chaotic than normal brain function. Nonlinear analysis of electroencephalograph (EEG) signals quantifies these differences.

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Last Updated: Jun 8, 2026

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Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Published on: December 6, 2016

Area of Science:

Neuroscience
Nonlinear Dynamics
Biomedical Engineering

Background:

Electroencephalograph (EEG) signals reflect brain activity.
Epileptic seizures represent abnormal brain electrical activity.
Nonlinear dynamics offers tools to analyze complex biological signals.

Purpose of the Study:

To investigate the nonlinear properties of EEG signals in epileptic versus healthy brain activity.
To quantitatively assess the chaotic behavior of brain activity during seizures.

Main Methods:

Utilized nonlinear theory measures: Lyapunov exponent, correlation dimension, Hurst exponent, fractal dimension, and Kolmogorov entropy.
Compared EEG signals from epileptic and healthy subjects.
Analyzed phase-space diagrams.

Main Results:

Statistical analysis of nonlinear measures showed significant differences between epileptic and healthy groups.
Epileptic brain activity exhibited limited trajectories in state space compared to healthy brains.
Brain activity during epileptic seizures was found to be less chaotic.

Conclusions:

Nonlinear analysis of EEG signals can differentiate between epileptic and healthy brain states.
Epileptic seizures are associated with reduced chaotic behavior in brain dynamics.
Findings contribute to understanding the nonlinear dynamics of epilepsy.