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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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Related Experiment Video

Updated: May 7, 2026

Author Spotlight: Unraveling Seizure Dynamics and Novel Therapeutics for Status Epilepticus Using CMOS High-Density Microelectrode Array Systems

Author Spotlight: Unraveling Seizure Dynamics and Novel Therapeutics for Status Epilepticus Using CMOS High-Density Microelectrode Array Systems

Published on: September 27, 2024

Modeling seizure self-prediction: an e-diary study.

Sheryl R Haut¹, Charles B Hall, Thomas Borkowski

¹Montefiore-Einstein Epilepsy Center, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, New York, U.S.A; Department of Neurology, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, New York, U.S.A.

|October 12, 2013

Summary

This summary is machine-generated.

Some individuals with epilepsy can accurately predict their seizures, with predictions being most reliable within a 6-hour window. This self-awareness of mood and prodromal symptoms aids in seizure prediction, paving the way for preemptive therapies.

Keywords:

Electronic diary Localization-related epilepsy Premonitory symptoms Seizure diary Seizure precipitants Seizure prediction Self-prediction

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Published on: July 8, 2025

Area of Science:

Neurology
Epilepsy Research
Predictive Medicine

Background:

A subset of epilepsy patients can self-predict seizures using paper diaries.
Understanding prodromal features and prediction time windows is crucial for developing interventions.

Purpose of the Study:

To confirm seizure prediction precedes seizures using an electronic diary.
To characterize prodromal features and time windows for self-prediction in epilepsy.

Main Methods:

Adults with localization-related epilepsy (LRE) used an e-diary to report daily data, including mood, premonitory symptoms, and seizures.
Self-prediction accuracy was assessed using a 5-point Likert scale.
Poisson models with log-normal random effects analyzed the odds of seizure occurrence based on prediction and other factors.

Main Results:

Nineteen subjects reported 244 seizures; "almost certain" prediction within 6 hours yielded an odds ratio (OR) of 9.31.
Prediction remained significant up to 12 hours, with the best predictors achieving 50% average sensitivity.
Older age, self-prediction, improved mood, and increased premonitory symptoms were significant factors in multivariate seizure occurrence modeling.

Conclusions:

Self-prediction of seizures is feasible in some individuals with epilepsy.
Positive predictions significantly increase seizure likelihood, are robust, and linked to mood and premonitory symptoms.
The identified 6-hour prediction window is suitable for developing preemptive therapeutic strategies.