ArticleScientific reports2022
Network analysis of preictal iEEG reveals changes in network structure preceding seizure onset.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Directed graph neural networks with partial directed coherence for seizure prediction and epileptogenic network characterization.iScience · 2026Article
- A multimodal epilepsy dataset of paired 3-Tesla and 7-Tesla MRI and intracranial EEG.Scientific data · 2026Article
- Dynamic excitation/inhibition balance preceding seizure onset and its link to functional and structural brain architecture.BMC medicine · 2025Article
- Intersection of epilepsy and cardiac health: Insights from electrocardiography and syndromic associations.Epilepsia · 2025Review
- Personalized preictal EEG pattern characterization: do timing and localization matter?Frontiers in neuroscience · 2025Article
- Preictal connectivity dynamics: Exploring inflow and outflow in iEEG networks.Frontiers in network physiology · 2025Article
- The Pre-Interictal Network State in Idiopathic Generalized Epilepsies.Brain sciences · 2023Article
- The seizure severity score: a quantitative tool for comparing seizures and their response to therapy.Journal of neural engineering · 2023Article
- Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy.Scientific reports · 2023Article
- The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives.Frontiers in network physiology · 2023Review
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2 authors.
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Abstract
Seizures likely result from aberrant network activity and synchronization. Changes in brain network connectivity may underlie seizure onset. We used a novel method of rapid network model estimation from intracranial electroencephalography (iEEG) data to characterize pre-ictal changes in network structure prior to seizure onset. We analyzed iEEG data from 20 patients from the iEEG.org database. Using 10 s epochs sliding by 1 s intervals, a multiple input, single output (MISO) state space model was estimated for each output channel and time point with all other channels as inputs, generating sequential directed network graphs of channel connectivity. These networks were assessed using degree and betweenness centrality. Both degree and betweenness increased at seizure onset zone (SOZ) channels 37.0 ± 2.8 s before seizure onset. Degree rose in all channels 8.2 ± 2.2 s prior to seizure onset, with increasing connections between the SOZ and surrounding channels. Interictal networks showed low and stable connectivity. A novel MISO model-based network estimation method identified changes in brain network structure just prior to seizure onset. Increased connectivity was initially isolated within the SOZ and spread to non-SOZ channels before electrographic seizure onset. Such models could help confirm localization of SOZ regions.
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