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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:

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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Related Experiment Video

Updated: Mar 15, 2026

Investigating the Function of Deep Cortical and Subcortical Structures Using Stereotactic Electroencephalography: Lessons from the Anterior Cingulate Cortex

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Published on: April 15, 2015

Virtual Cortical Resection Reveals Push-Pull Network Control Preceding Seizure Evolution.

Ankit N Khambhati¹, Kathryn A Davis², Timothy H Lucas³

¹Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA.

|August 30, 2016

Summary

This summary is machine-generated.

Researchers identified key brain regions controlling seizure spread in epilepsy. Understanding these network dynamics can help constrain seizure activity and offers potential for broader brain network research.

Keywords:

epileptic network network neuroscience push-pull control seizure spread synchronizability

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Published on: March 14, 2022

Area of Science:

Neuroscience
Computational Neuroscience
Systems Neuroscience

Background:

Epilepsy affects millions with drug-resistant seizures originating from dysfunctional brain networks.
Seizure spread disrupts normal brain function, posing significant clinical challenges.

Purpose of the Study:

To identify network control mechanisms regulating seizure spread in epilepsy.
To develop a novel computational tool for pinpointing critical brain regions within epileptic networks.

Main Methods:

Developed a method to simulate the virtual resection of brain regions.
Measured the impact of simulated resections on network synchronization in an epileptic network model.
Applied the technique to time-varying functional brain networks.

Main Results:

Identified specific brain regions that synchronize and desynchronize epileptic networks.
Demonstrated that antagonistic interactions between synchronizing and desynchronizing regions constrain seizure spread.
Validated the computational tool's effectiveness in mapping functional drivers of brain dynamics.

Conclusions:

Antagonistic interactions within brain networks are crucial for controlling seizure spread.
The developed methodology is generalizable to studying other brain network dynamics in health and disease.
This approach offers a new way to map functional drivers of complex brain activity.