Predicting seizure onset zones from interictal intracranial EEG using functional connectivity and machine learning

Predicting seizure onset zones from interictal intracranial EEG using functional connectivity and machine learning

Abstract Functional connectivity (FC) analyses of intracranial EEG (iEEG) signals can potentially improve the mapping of epileptic networks in drug-resistant focal epilepsy. However, it remains unclear whether FC-based metrics provide additional value beyond established epilepsy biomarkers such as e...

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Bibliographic Details
Main Authors: Jared Pilet, Scott A. Beardsley, Chad Carlson, Christopher T. Anderson, Candida Ustine, Sean Lew, Wade Mueller, Manoj Raghavan
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Machine learning
Intracranial EEG
Functional connectivity
Seizure onset zone
Epileptogenicity
Biomarkers
Online Access:https://doi.org/10.1038/s41598-025-02679-4
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https://doi.org/10.1038/s41598-025-02679-4

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