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Large EEG databases and automated processing solutions for scientific discovery and deep learning| title | Large EEG databases and automated processing solutions for scientific discovery and deep learning |
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| start_date | 2025/06/02 |
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| schedule | 11h-12h |
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| online | no |
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| location_info | salle des Voûtes |
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| summary | This study reviews publicly available EEG databases, focusing on NEMAR (Neuroelectromagnetic Data Archive and Tools Resource), and evaluates their accessibility, data quality, and potential for reuse. We examine the broader ecosystem of shared EEG resources, emphasizing the adoption of the BIDS (Brain Imaging Data Structure) framework as a standard for data organization and metadata annotation. Cloud-based processing solutions are assessed for their ability to support scalable and reproducible EEG analysis, particularly in conjunction with NEMAR. Additionally, we investigate EEGDash as a user-friendly interface that facilitates integration of EEG data with deep learning workflows, enabling efficient application of AI methods in neuroimaging research. |
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| responsibles | Basques |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2025/05/30 07:59 UTC |
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