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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:

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Updated: May 2, 2026

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

Electroencephalographic Resting-State Microstates are Unstable in Visual Snow Syndrome.

Sarah A Aeschlimann^1,2, Antonia Klein¹, Frédéric Zubler^3,4

¹Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.

Brain and Behavior

|March 14, 2025

Summary

Visual snow syndrome (VSS) involves unstable brain network activity, shown by shorter and less intense electroencephalography (EEG) microstates. Aberrant transitions between microstate classes suggest disturbed large-scale network function in VSS patients.

Keywords:

EEG microstates large‐scale network processing neural network activity resting‐state EEG visual snow

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Area of Science:

Neuroscience
Clinical Neurology
Medical Imaging

Background:

Visual snow syndrome (VSS) presents with visual disturbances like flickering dots.
VSS is linked to migraine and tinnitus and is considered a network disorder.
The underlying pathophysiology of VSS remains largely unknown.

Purpose of the Study:

To investigate large-scale network processing in VSS using resting-state electroencephalography (EEG) microstate analysis.
To compare microstate parameters between VSS patients and matched controls, with and without migraine.

Main Methods:

A case-control study involving 21 VSS patients and 21 controls.
Resting-state EEG recordings were analyzed using canonical microstate Classes A-D.
Parameters such as duration, amplitude, and transition probabilities between microstates were assessed.

Main Results:

VSS patients exhibited significantly shorter microstate durations and lower mean amplitudes compared to controls.
Aberrant microstate syntax was observed in VSS, specifically more transitions from Class A to Class B and fewer to Class C.
These findings indicate unstable microstates and altered transition probabilities in VSS.

Conclusions:

VSS is a complex disorder characterized by widespread neural network activity disturbances.
EEG microstate analysis reveals unstable microstates and aberrant transition probabilities in VSS.
Microstate dynamics analysis offers high temporal resolution insights into VSS pathophysiology and may inform future treatments.