ArticleNeuroImage. Clinical2019
High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.
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Who cites it
42 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Directed graph neural networks with partial directed coherence for seizure prediction and epileptogenic network characterization.iScience · 2026Article
- Predicting surgical outcome in drug-resistant epilepsy by combining interictal biomarkers within a machine learning framework.Scientific reports · 2026Article
- Intrinsic and extrinsic connectivity of the seizure onset zone at rest and during stimulation.medRxiv : the preprint server for health sciences · 2026Article
- Predicting Surgical Outcome in Drug-Resistant Epilepsy by Combining Interictal Biomarkers within a Machine Learning Framework.Research square · 2026Article
- Effective Connectivity Predicts Surgical Outcomes in Temporal Lobe Epilepsy: A SEEG Study.CNS neuroscience & therapeutics · 2025Article
- Identifying the epileptic network by linking interictal functional and structural connectivity.Scientific reports · 2025Article
- Machine learning on interictal intracranial EEG predicts surgical outcome in drug resistant epilepsy.NPJ digital medicine · 2025Article
- Preictal connectivity dynamics: Exploring inflow and outflow in iEEG networks.Frontiers in network physiology · 2025Article
- Directionality of neural activity in and out of the seizure onset zone in focal epilepsy.Network neuroscience (Cambridge, Mass.) · 2025Article
- Quantifying hubness to predict surgical outcomes in epilepsy: Assessing resection-hub alignment in interictal intracranial EEG networks.Epilepsia · 2024Article
- Dynamic evolution of frontal-temporal network connectivity in temporal lobe epilepsy: A magnetoencephalography study.Human brain mapping · 2024Article
- Emerging Medical Technologies and Their Use in Bionic Repair and Human Augmentation.Bioengineering (Basel, Switzerland) · 2024Review
- EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes.Neurology · 2024Article
- An electroencephalogram microdisplay to visualize neuronal activity on the brain surface.Science translational medicine · 2024Article
- Interictal EEG source connectivity to localize the epileptogenic zone in patients with drug-resistant epilepsy: A machine learning approach.Epilepsia · 2024Article
- Generalisability of epileptiform patterns across time and patients.Scientific reports · 2024Article
- Connectivity of high-frequency bursts as SOZ localization biomarker.Frontiers in network physiology · 2024Article
- Utility of intracranial EEG networks depends on re-referencing and connectivity choice.Brain communications · 2024Article
- Network coupling and surgical treatment response in temporal lobe epilepsy: A proof-of-concept study.Epilepsy & behavior : E&B · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Patients with drug-resistant focal epilepsy are often candidates for invasive surgical therapies. In these patients, it is necessary to accurately localize seizure generators to ensure seizure freedom following intervention. While intracranial electroencephalography (iEEG) is the gold standard for mapping networks for surgery, this approach requires inducing and recording seizures, which may cause patient morbidity. The goal of this study is to evaluate the utility of mapping interictal (non-seizure) iEEG networks to identify targets for surgical treatment. We analyze interictal iEEG recordings and neuroimaging from 27 focal epilepsy patients treated via surgical resection. We generate interictal functional networks by calculating pairwise correlation of iEEG signals across different frequency bands. Using image coregistration and segmentation, we identify electrodes falling within surgically resected tissue (i.e. the resection zone), and compute node-level and edge-level synchrony in relation to the resection zone. We further associate these metrics with post-surgical outcomes. Greater overlap between resected electrodes and highly synchronous electrodes is associated with favorable post-surgical outcomes. Additionally, good-outcome patients have significantly higher connectivity localized within the resection zone compared to those with poorer postoperative seizure control. This finding persists following normalization by a spatially-constrained null model. This study suggests that spatially-informed interictal network synchrony measures can distinguish between good and poor post-surgical outcomes. By capturing clinically-relevant information during interictal periods, our method may ultimately reduce the need for prolonged invasive implants and provide insights into the pathophysiology of an epileptic brain. We discuss next steps for translating these findings into a prospectively useful clinical tool.
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