ERP-FM is an EEG foundation model pretrained on event-related potential recordings only: its paper lists the task-level ERP datasets it used. On this site the two ERP protocols, P300 target and semantic target, are in its design; the other six are negative controls outside it, and the ERP windows here have no pre-stimulus baseline, so this is not a test of ERP-FM in its own setting. The weights are CC BY-NC-SA 4.0, for non-commercial use.
What was run, as the v9 release records it: each checkpoint’s revision and SHA-256, its encoder parameters, the footnote its rows carry and its weights licence. No weights, adapted weights or LoRA deltas were kept or shared, and no endorsement by the model’s authors is implied.
ERP-FM Base
Panel
A row beside the core matrix on every protocol page
Encoder parameters
2.02M
Revision
Google Drive file 1IXYnCOpDmY6raIn0M8_ggBOVey_A27l1 (no revision id; sha256 is the identity)
CC BY-NC-SA 4.0 (non-commercial; aggregate scores only)
Licence note
CC BY-NC-SA 4.0: non-commercial; aggregate scores only; attribution required; no weights redistributed.
Rights review
Non-commercial share-alike weights. This site is personal noncommercial research and publishes aggregate scores only, with attribution; no weights are redistributed.
Row footnote
In design: p300-target and semantic-target. The other six protocols are negative controls outside the model's design. ERP windows have no pre-stimulus baseline.
EEGMAT adaptation
not run by design: ERP-FM is frozen probes only and EEGMAT arithmetic is outside the ERP design
Pretraining exposure, by dataset
Whether each core dataset is in the model authors’ published pretraining list, checked on 2026-10-04 and linked to the source. A dataset absent from the list is not proof that its recordings were never seen; recording-level audits were not done.
BCI Report