| --- |
| license: apache-2.0 |
| library_name: braindecode |
| tags: |
| - braindecode |
| - pytorch |
| - safetensors |
| - ieeg |
| - seeg |
| - mapa |
| --- |
| |
| # mapa-pretrained |
|
|
| Weights of the MAPA encoder `mapa_vits384` (d_model 384, 12 blocks, 21,335,424 |
| parameters), for |
| [`braindecode.models.MAPA`](https://braindecode.org/stable/generated/braindecode.models.MAPA.html), |
| converted from the authors' release. The classification head is not pretrained (seeded random init); fine-tune or linear-probe before use. |
| |
| ```python |
| from braindecode.models import MAPA |
| model = MAPA.from_pretrained("braindecode/mapa-pretrained", n_outputs=2, chs_info=raw.info["chs"], regions=regions) |
| ``` |
| |
| Channel names are read as clinical contact labels (`"LA7"` is contact 7 of |
| array `LA`); `regions` are DKT names from `braindecode.models.mapa.MAPA_DKT_REGIONS`. |
| The montage in `config.json` (4 channels, no regions) is only a default. Input is |
| expected at 2048 Hz, or as the session-normalized spectrogram with |
| `normalization="session"`, `sfreq=32`. |
| |
| ## Source and conversion |
| |
| - Source: [bentang18/MAPA](https://huggingface.co/bentang18/MAPA) at revision |
| `988efbf31a7d1f38533b848c993a719d6f900b1f`, file `mapa_vits384.pt` |
| (sha256 `2d236089a2f1a3cc2827e3f150c4a2ba14c51bbfaf0ce0888f84b92a6eb25a7a`), |
| Apache-2.0. The authors' `NOTICE` is copied in this repository. |
| - `convert_mapa_checkpoint.py` (in this repository) renames the feed-forward |
| `encoder.blocks.{i}.mlp.fc1`/`fc2` to `mlp.0`/`mlp.3` (braindecode's |
| `FeedForwardBlock`), keeps every other key, and writes `config.json`, |
| `model.safetensors` and `pytorch_model.bin` with `save_pretrained`. |
| - The converted model's outputs equal braindecode's loading of the original |
| file (max-abs difference 0.0). |
| - Requires a braindecode version newer than 1.8.1. |
| - The ablation checkpoints (`no_region`, `no_relpos`, `no_priors`) are not |
| re-hosted; they remain at the source repository. |
| |
| ## Citation |
| |
| ```bibtex |
| @misc{tang2026pretraining, |
| title = {Pretraining for Sample-Efficient Neural Interfaces}, |
| author = {Ben Tang and Zachary Spalding and Gregory B. Cogan}, |
| year = {2026}, |
| eprint = {2609.13507}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.LG}, |
| url = {https://arxiv.org/abs/2609.13507}, |
| } |
|
|
| @article{aristimunha2025braindecode, |
| title = {Braindecode: a deep learning library for raw electrophysiological data}, |
| author = {Aristimunha, Bruno and others}, |
| journal = {Zenodo}, |
| year = {2025}, |
| doi = {10.5281/zenodo.17699192}, |
| } |
| ``` |
| |
| ## License |
| |
| Apache-2.0, as the original MAPA release. The checkpoint was pretrained on the |
| Brain Treebank dataset (CC BY 4.0, https://braintreebank.dev/); see `NOTICE`. |
| |
