BrainPro: Process-conditioned Pretraining with Topographic Retrieval for Large EEG Models
Read the original on arXiv Machine Learning →BrainPro is a process‑conditioned self‑supervised pretraining framework for large EEG models that addresses two underexplored challenges: the underuse of mental‑process cues in masked pretraining and the variability of electrode montages across datasets. It maps dataset‑specific montages to a universal channel‑region template, retrieves spatial filters to create a topographically aligned basis, and learns a shared encoder along with process‑specific branches conditioned on protocol cues. Experiments on nine public BCI benchmarks show that BrainPro outperforms baselines, with ablations indicating that topographic retrieval and process‑conditioned representation learning jointly enhance EEG decoding.
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