ArticleScientific reports2024
Combining independent component analysis and source localization for improving spatial sampling of stereoelectroencephalography in epilepsy.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- How to Recognize and Manage Missing Key Electrodes in Defining the Epileptogenic Zone.Epilepsy currents · 2026Article
- Modern Aspects of Invasive Epilepsy Monitoring: Utility for Seizure Localization and Therapeutic Decision-Making.Pediatric neurosurgery · 2026Review
- Stimulation mapping and whole-brain modeling reveal gradients of excitability and recurrence in cortical networks.Nature communications · 2025Article
- A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals.Scientific reports · 2025Article
- Intracranial Voltage Profiles from Untangled Human Deep Sources Reveal Multisource Composition and Source Allocation Bias.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Different sustained and induced alpha oscillations emerge in the human auditory cortex during sound processing.Communications biology · 2024Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Stereoelectroencephalography is a powerful intracerebral EEG recording method for the presurgical evaluation of epilepsy. It consists in implanting depth electrodes in the patient's brain to record electrical activity and map the epileptogenic zone, which should be resected to render the patient seizure-free. Stereoelectroencephalography has high spatial accuracy and signal-to-noise ratio but remains limited in the coverage of the explored brain regions. Thus, the implantation might provide a suboptimal sampling of epileptogenic regions. We investigate the potential of improving a suboptimal stereoelectroencephalography recording by performing source localization on stereoelectroencephalography signals. We propose combining independent component analysis, connectivity measures to identify components of interest, and distributed source modelling. This approach was tested on two patients with two implantations each, the first failing to characterize the epileptogenic zone and the second giving a better diagnosis. We demonstrate that ictal and interictal source localization performed on the first stereoelectroencephalography recordings matches the findings of the second stereo-EEG exploration. Our findings suggest that independent component analysis followed by source localization on the topographies of interest is a promising method for retrieving the epileptogenic zone in case of suboptimal implantation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.