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Portable synthetic-data / EEG-foundation-model study

This directory is the complete transfer payload: archive, upload, or copy the whole directory as-is. No transfer-time allowlist or exclusion rule is needed.

It is self-contained except for the licensed TUH EEG datasets. Put them at:

  • test/AB: TUAB
  • test/EV: TUEV
  • test/SZ: TUSZ

Selected foundation models are NeuroLM-B, NeuroLM-L, NeuroLM-XL, ST-EEGFormer-Large and LUNA-Huge. Selected generators are conditional diffusion, conditional EEG WGAN-GP and JET.

The study evaluates the influence of synthetic data on both native self-supervised foundation-model training and fixed real-only downstream linear probes. All jobs use frozen, shared evaluation indices and report confidence intervals.

Experiment tracking is entirely local; no result is sent to W&B. Start with docs/RUNBOOK.md and docs/WANDB_AND_COMBINATION_RUNBOOK.md (the legacy filename now documents console logging): rebuild the isolated environment, validate all assets with env/runtime/bin/python src/validate_bundle.py --deep-hash --require-trained-generators, then use one of the 75 GPU-selectable combination scripts indexed by configs/combination_scripts.tsv.

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