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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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Abnormal dynamic connectivity patterns in self-limited epilepsy with centrotemporal spikes.

Xu Chen¹, Linfeng Song¹, Jiaren Zhang¹

¹Department of Radiology, The Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi), Huichuang District, Zunyi, Guizhou, China.

Brain Research Bulletin

|December 4, 2025

Summary

Children with self-limited epilepsy with centrotemporal spikes (SeLECTS) exhibit altered brain network dynamics, specifically reduced connectivity in attention networks. These findings suggest an excitation-inhibition imbalance and offer insights into functional reorganization in SeLECTS.

Keywords:

Brain network Dynamic functional network connectivity Hidden markov model Self-limited epilepsy with centrotemporal spikes

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Area of Science:

Neuroscience
Pediatric Neurology
Medical Imaging

Background:

Self-limited epilepsy with centrotemporal spikes (SeLECTS) is a common childhood epilepsy syndrome.
Understanding the neural underpinnings of SeLECTS is crucial for developing targeted interventions.
Dynamic functional network connectivity (dFNC) offers a novel approach to investigate brain function in epilepsy.

Purpose of the Study:

To characterize dFNC patterns in children with SeLECTS.
To identify abnormalities in neural regulation and functional impairments associated with SeLECTS.
To explore the relationship between dFNC alterations and cognitive function.

Main Methods:

Resting-state functional magnetic resonance imaging (rs-fMRI) data from 61 children with SeLECTS and 69 healthy controls (HCs).
Analysis using Independent Component Analysis (ICA), sliding window approach, and Hidden Markov Modeling (HMM) to assess dFNC.
Comparison of dFNC properties between the SeLECTS and HC groups.

Main Results:

Four distinct dFNC states were identified, with significant differences in connectivity patterns between SeLECTS and HCs.
Children with SeLECTS showed reduced connectivity within the dorsal attention network (DAN) across states.
Temporal variability of functional connectivity between DAN and visual network (VIS) was reduced in SeLECTS and correlated with intelligence.

Conclusions:

Abnormal dynamic brain network connectivity patterns were observed in children with SeLECTS.
These abnormalities may indicate an underlying excitation-inhibition imbalance in neural networks.
The findings provide insights into brain functional reorganization and neurobiological mechanisms in SeLECTS.