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Research questionHow can MEG foundation models become reusable across subjects, sites, and tasks despite limited training data?MEG foundation-model development is constrained by a small number of models, modest pretraining corpora, and limited benchmarks. These constraints make it difficult to determine which design choices support transfer across people, recording sites, tasks, and clinical settings.
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Evaluation & Benchmarks
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Machine Learning
Multimodal Models
Research Paper
Latest papersRecent research connected to this question, newest first.A Roadmap for MEG Foundation ModelsThe source surveys MEG-specific and multimodal models, sensor- and source-space representations, sensor-geometry encoding, architectures, self-supervised objectives, pretraining data, transfer from EEG and generic time-series models, and integration with other modalities. It provides a field roadmap rather than evidence from a single controlled model comparison, while also discussing dataset reuse, evaluation, consent, privacy, access, and governance.research paper · Sep 3, 2026
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