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Related Concept Videos

Epilepsy and Seizures: Overview01:24

Epilepsy and Seizures: Overview

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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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Seizures: Classification01:13

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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: Dec 14, 2025

Performing Behavioral Tasks in Subjects with Intracranial Electrodes
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Seizure localization using EEG analytical signals.

Mark H Myers1, Akaash Padmanabha2, Gavin M Bidelman3

  • 1Department of Anatomy and Neurobiology, University of Tennessee Health Sciences Center, Memphis, TN, USA.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology
|July 19, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a new, automated method for pinpointing epileptic seizure origins on the scalp using electroencephalogram (EEG) data, achieving high precision and sensitivity.

Keywords:
Analytic amplitude (AA)Analytic phase (AP)Electroencephalograph (EEG)Seizure onset zone (SOZ)

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Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
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Area of Science:

  • Neuroscience
  • Medical Signal Processing
  • Computational Biology

Background:

  • Epileptic seizures are characterized by abnormal cortical electrical activity.
  • Accurate localization of seizure onset from scalp electroencephalogram (EEG) data is challenging.
  • Current methods for seizure localization can be complex and computationally intensive.

Purpose of the Study:

  • To develop a novel, robust, and automated method for localizing epileptic seizures on the scalp using clinical EEG data.
  • To improve the precision and sensitivity of seizure localization compared to existing techniques.
  • To provide a more straightforward and less computationally demanding alternative to methods like inverse source modeling.

Main Methods:

  • EEG data from seizure patients was decomposed using the Hilbert Transform.
  • Analytic amplitude (AA) was sorted in time, and maximum amplitude was located across channels.
  • Cross-correlation of amplitude values over time and channels identified the seizure origin.

Main Results:

  • The automated method achieved 93.3% precision and 100% sensitivity in localizing seizure events.
  • The approach effectively distinguished seizure-related neural activity from common EEG noise artifacts.
  • Performance was validated using both phase and energy characteristics of EEG signals.

Conclusions:

  • The developed algorithm provides high-performance scalp localization of seizure events.
  • The method is more straightforward and less computationally intensive than traditional approaches.
  • This technique has the potential to significantly aid clinicians in patient diagnosis and management.