ArticleNeurosurgery2020
Resting-State SEEG May Help Localize Epileptogenic Brain Regions.
Article in Neurosurgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- Antiseizure Networks.Epilepsy currents · 2026Article
- Alteration of functional connectivity and network properties after stereo-electroencephalography guided radiofrequency thermocoagulation.Chinese neurosurgical journal · 2026Article
- Static and dynamic intracerebral signal analysis reveals protective networks against seizures in drug-resistant focal epilepsy.Brain communications · 2026Article
- Multi-modal connectome analysis of the stereoelectroencephalography implantation effect: a case report.Clinical neurophysiology practice · 2026Article
- Deep learning on brief interictal intracranial recordings can accurately characterize seizure onset zones.Epilepsia · 2025Article
- Very High-Frequency Oscillations in Mesial Temporal Lobe Epilepsy: Identifying the Epileptogenic Zone.Annals of clinical and translational neurology · 2025Article
- Advancements in Surgical Therapies for Drug-Resistant Epilepsy: A Paradigm Shift towards Precision Care.Neurology and therapy · 2025Review
- The network neuropsychology of juvenile myoclonic epilepsy.Cortex; a journal devoted to the study of the nervous system and behavior · 2025Article
- Groupwise registration of infant brain diffusion tensor images using intermediate subgroup templates.PloS one · 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
- The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy.Brain : a journal of neurology · 2024Article
- Multi-scale analysis of acupuncture mechanisms for motor and sensory cortex activity based on SEEG data.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery.Neurosurgery clinics of North America · 2024Review
- Article
- Intracranial EEG Structure-Function Coupling and Seizure Outcomes After Epilepsy Surgery.Neurology · 2023Article
- The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence.Brain : a journal of neurology · 2023Article
- Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy.Scientific reports · 2023Article
- Non-invasive mapping of epileptogenic networks predicts surgical outcome.Brain : a journal of neurology · 2023Article
- Time-resolved correlation of distributed brain activity tracks E-I balance and accounts for diverse scale-free phenomena.Cell reports · 2023Article
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Authors and funding
11 authors.
Funding
Abstract
backgroundStereotactic electroencephalography (SEEG) is a minimally invasive neurosurgical method to localize epileptogenic brain regions in epilepsy but requires days in the hospital with interventions to trigger several seizures.
objectiveTo make initial progress in the development of network analysis methods to identify epileptogenic brain regions using brief, resting-state SEEG data segments, without requiring seizure recordings.
methodsIn a cohort of 15 adult focal epilepsy patients undergoing SEEG, we evaluated functional connectivity (alpha-band imaginary coherence) across sampled regions using brief (2 min) resting-state data segments. Bootstrapped logistic regression was used to generate a model to predict epileptogenicity of individual regions.
resultsCompared to nonepileptogenic structures, we found increased functional connectivity within epileptogenic regions (P < .05) and between epileptogenic areas and other structures (P < .01, paired t-tests, corrected). Epileptogenic areas also demonstrated higher clustering coefficient (P < .01) and betweenness centrality (P < .01), and greater decay of functional connectivity with distance (P < .05, paired t-tests, corrected). Our functional connectivity model to predict epileptogenicity of individual regions demonstrated an area under the curve of 0.78 and accuracy of 80.4%.
conclusionOur study represents a preliminary step towards defining resting-state SEEG functional connectivity patterns to help localize epileptogenic brain regions ahead of neurosurgical treatment without requiring seizure recordings.
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