Predicting seizure onset zones from interictal intracranial EEG using functional connectivity and machine learning. Sci Rep 2025 May 22;15(1):17801
Date
05/23/2025Pubmed ID
40404720Pubmed Central ID
PMC12098728DOI
10.1038/s41598-025-02679-4Scopus ID
2-s2.0-105005808353 (requires institutional sign-in at Scopus site)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 epileptic spikes and high-frequency oscillations (HFOs). Using interictal iEEG data from 26 patients, we estimated FC across eight frequency bands (4-290 Hz) using amplitude envelope correlation (AEC) and phase locking value (PLV). From the resulting FC-matrices, we estimated two graph metrics each to derive 32 FC-based features. We also extracted features related to spikes, HFOs, and power spectral densities (PSD). A trained support vector machine (SVM) classifier predicted seizure onset zones (SOZs) with an area under the ROC curve (AUC) of 0.91 for node-level 4-fold cross-validation (CV), 0.69 for patient-level 4-fold CV, and 0.73 for patient-level leave-one-out CV. Notably, gamma-band graph features from AECs outperformed spikes and HFOs in SOZ prediction when using an equivalent number of features. Our results strongly suggest that AEC-based features may provide more information about epileptogenicity compared to PLV-based features. Furthermore, machine learning provides a robust approach for identifying useful FC-based features and integrating information from putative biomarkers of epilepsy to better localize epileptogenic networks.
Author List
Pilet J, Beardsley SA, Carlson C, Anderson CT, Ustine C, Lew S, Mueller W, Raghavan MAuthors
Scott Beardsley PhD Associate Professor in the Biomedical Engineering department at Marquette UniversityChad Carlson MD Interim Chair, Professor in the Neurology department at Medical College of Wisconsin
Sean Lew MD Chief, Professor in the Neurosurgery department at Medical College of Wisconsin
Wade M. Mueller MD Professor in the Neurosurgery department at Medical College of Wisconsin
Manoj Raghavan MD, PhD Professor in the Neurology department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
AdolescentAdult
Drug Resistant Epilepsy
Electrocorticography
Electroencephalography
Female
Humans
Machine Learning
Male
Middle Aged
ROC Curve
Seizures
Support Vector Machine
Young Adult
