UniBCI is a unified pretrained model for invasive neural spike data that uses CST tokenization, IAA attention, and self-supervised masked reconstruction to achieve SOTA downstream performance with better generalization and efficiency.
Walking naturally after spinal cord injury using a brain–spine interface.Nature, 618(7963):126–133
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Pretrained scalp-EEG foundation models can be transferred to ECoG via adapters and fine-tuning to match or exceed subject-specific baselines on regression tasks while requiring far less per-patient data.
citing papers explorer
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UniBCI: Towards a Unified Pretrained Model for Invasive Brain-Computer Interfaces
UniBCI is a unified pretrained model for invasive neural spike data that uses CST tokenization, IAA attention, and self-supervised masked reconstruction to achieve SOTA downstream performance with better generalization and efficiency.
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CORTEG: Foundation Models Enable Cross-Modality Representation Transfer from Scalp to Intracranial Brain Recordings
Pretrained scalp-EEG foundation models can be transferred to ECoG via adapters and fine-tuning to match or exceed subject-specific baselines on regression tasks while requiring far less per-patient data.