ArticleNetwork neuroscience (Cambridge, Mass.)2024
Brain sodium MRI-derived priors support the estimation of epileptogenic zones using personalized model-based methods in epilepsy.
Article in Network neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- AI in epilepsy neuroimaging.Current opinion in neurology · 2026Review
- Virtual brain twins for stimulation in epilepsy.Nature computational science · 2025Article
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8 authors.
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Abstract
Patients presenting with drug-resistant epilepsy are eligible for surgery aiming to remove the regions involved in the production of seizure activities, the so-called epileptogenic zone network (EZN). Thus the accurate estimation of the EZN is crucial. Data-driven, personalized virtual brain models derived from patient-specific anatomical and functional data are used in Virtual Epileptic Patient (VEP) to estimate the EZN via optimization methods from Bayesian inference. The Bayesian inference approach used in previous VEP integrates priors, based on the features of stereotactic-electroencephalography (SEEG) seizures' recordings. Here, we propose new priors, based on quantitative
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