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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...

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Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue

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Published on: January 19, 2019

Simulating epileptic seizures using the bidomain model.

Jakob Schreiner^1,2, Kent-Andre Mardal^3,4,5

¹Simula Research Laboratory, Oslo, 0164, Norway. jakob@xal.no.

Scientific Reports

|June 17, 2022

Summary

This study models epileptic seizures on a whole-brain scale using the Bidomain model. Simulated electric potentials in brain models exhibit power-law distributions, offering new insights into seizure dynamics.

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

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Last Updated: Sep 7, 2025

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Using a Bipolar Electrode to Create a Temporal Lobe Epilepsy Mouse Model by Electrical Kindling of the Amygdala

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

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

Published on: June 6, 2015

Area of Science:

Computational neuroscience
Biophysics
Medical imaging analysis

Background:

Epileptic seizures result from excessive, synchronous neural activity.
Scaling neuronal seizure models to whole-brain complexity is challenging.
Brain activity measurements often follow power-law distributions, with altered exponents during seizures.

Purpose of the Study:

To extend neuronal seizure models to a whole-brain scale using the Bidomain model.
To evaluate the proposed modeling approach by analyzing power-law distributions of simulated brain activity.
To investigate the applicability of the Bidomain model for whole-brain seizure simulation.

Main Methods:

Utilized the Bidomain model, previously successful in cardiac modeling, for brain electrical activity.
Simulated electric potentials in 7 idealized 2D and 3 patient-specific 3D models derived from MRI.
Analyzed the frequency-dependent power-law distributions of computed electric potentials.

Main Results:

Simulated electric potentials in whole-brain models followed power-law distributions.
Observed power-law slopes ranging from 2 to 5 for frequencies above 10-30 Hz.
Demonstrated the potential of the Bidomain model for whole-brain seizure dynamics.

Conclusions:

The Bidomain model can be extended for whole-brain seizure modeling.
Power-law distributions provide a valuable metric for evaluating seizure models.
This approach offers a novel framework for understanding large-scale epileptic dynamics.