ArticleScientific reports2024
Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study.
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 8 papers.
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Who cites it
8 citing papers in PubMed.
- Optically pumped magnetometers enhance neuroimaging performance-An EEG, OPM, and SQUID-MEG study.iScience · 2026Article
- Case report: precise mapping and epilepsy surgery of the Broca's area after a comprehensive OPM-MEG investigation of Broca's area localization.Acta epileptologica · 2026Article
- Optimizing OPM-MEG Sensor Layouts Using the Sequential Selection Algorithm with Simulated Sources and Individual Anatomy.Sensors (Basel, Switzerland) · 2026Article
- Model-based cardiac field artefact correction for OP-MEG.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Liver X Receptor Beta Regulates Glial Dynamics and Cortical Network Remodeling in a Freezing Lesion-Cortical Dysplasia Model.CNS neuroscience & therapeutics · 2025Article
- SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025Review
- Detection of Epileptogenic Focal Cortical Dysplasia Using Graph Neural Networks: A MELD Study.JAMA neurology · 2025Article
- Inferring laminar origins of MEG signals with optically pumped magnetometers (OPMs): A simulation study.Imaging neuroscience (Cambridge, Mass.) · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
When planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant's potential lesion sites provided the best compromise of robustness against modelling or measurement error.
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