Indications for network regularization during absence seizures: weighted and unweighted graph theoretical analyses

Area of Science:

• Neuroscience
• Epilepsy Research
• Brain Network Analysis

Background:

• Previous intracranial studies linked random functional brain network structures to seizure generation.
• Generalized absence seizures are a common epilepsy syndrome in children, characterized by brief lapses of awareness.
• Understanding the network dynamics during absence seizures is crucial for developing targeted therapies.

Purpose of the Study:

• To investigate changes in functional brain network topology during generalized absence seizures using surface EEG.
• To determine if weighted and unweighted network analyses reveal similar alterations in network structure.
• To compare ictal (seizure) network characteristics with pre-ictal (before seizure) states.

Main Methods:

• Retrospective analysis of EEG recordings from eleven children with absence seizures.
• Functional neural networks were constructed using coherence and synchronization likelihood (SL) from 21 EEG signals.
• Network topology was assessed by calculating clustering coefficient (C) and path length (L), comparing them to random networks (C-s, L-s).

Main Results:

• Increased synchronization was observed across all frequency bands during absence seizures, particularly in SL-based networks.
• Functional network topology shifted towards a more ordered pattern during seizures, indicated by increased C/C-s and L/L-s ratios.
• Both weighted and unweighted network analyses demonstrated a regularization of network structure during the ictal period compared to the pre-ictal state.

Conclusions:

• This study supports the hypothesis that functional neural network dynamics change significantly during generalized absence seizures.
• The findings suggest that absence seizures are associated with a transition from a more randomized pre-ictal network to a more regularized ictal network.
• Surface EEG analysis can reveal topological changes in brain networks during absence seizures, offering insights into seizure generation mechanisms.