Pre-training on long-context MEG data enables data-efficient word decoding from brain signals that matches supervised baselines with roughly 50 times less data.
The output embeddings from model backbones are sliced according to their alignment with word stimuli and pooled in the time dimension before being flattened and concatenated
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MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training
Pre-training on long-context MEG data enables data-efficient word decoding from brain signals that matches supervised baselines with roughly 50 times less data.