Add bciciv-2a and sleep-edf public data

Two new EEG deep-learning benchmark tasks:
- bciciv-2a: BCI Competition IV Dataset 2a (motor imagery, 9 subj, session-T training set)
- sleep-edf: Sleep-EDF Cassette (sleep staging, subj 0-15 main + 16-19 LOSO supplement)

All tarballs are deterministic (mtime/uid pinned) and referenced by sha256 from BrainPilotBench task data.lock files.

README.md

@@ -39,6 +39,8 @@ Tasks-Data-Public/
 |------------------------|----------------------------------------------|----------------------------------------------------------------------------------------------------|
 | `neuro-rsc-place-cell` | `VRBeltReframe.mat`                          | Mouse RSC Ca²⁺ imaging + VR belt behavior (MATLAB v5, 203 MB)                                        |
 | `tops-fmri`            | `study3_train.mat`, `public_support.tar.zst` | Study3 tonic-pain FC + Fan 279 atlas + one example participant (~ 966 MB). Held-out lives in Private. |
+| `bciciv-2a`            | `public.tar.zst`                             | BCI Competition IV 2a session-T GDF for 9 subjects + manifests + loader (~ 194 MB). Held-out session-E in Private. |
+| `sleep-edf`            | `public-main.tar.zst`, `loso-supplement.tar.zst` | Sleep-EDF Cassette PSG + Hypnogram for subjects 0-15 (main, ~ 934 MB) + optional subjects 16-19 for LOSO (~ 235 MB). Held-out 16-19 test in Private. |
 
 ## How to consume
 

bciciv-2a/README.md

@@ -0,0 +1,34 @@
+# bciciv-2a — public training data
+
+Public-side data for BrainPilotBench task
+[`tasks/bciciv-2a`](https://github.com/NeuroAIHub/BrainPilotBench/tree/main/tasks/bciciv-2a).
+
+Held-out session-E evaluation GDF files and their true labels live in the
+gated companion dataset
+[`BrainPilot-Bench/Tasks-Data-Private`](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Private)
+and never appear here.
+
+## Files
+
+| File | Contents | Size |
+|---|---|---|
+| `public.tar.zst` | `gdf/A0[1-9]T.gdf` (9 subjects × session-T training GDF), `manifests/{subjects.json,protocol.json}`, `get_subject_data.py`, `label_mapping.json`, `README.md` | ~ 194 MB |
+
+`public.tar.zst` is pinned by sha256 in the task's `data.lock`; the agent's
+`env/setup-agent.sh` untars it into the workspace `public_data/`.
+
+## Task summary
+
+BCI Competition IV Dataset 2a — 4-class motor imagery decoding (left hand /
+right hand / feet / tongue). 9 subjects × 22 EEG channels × 288 trials per
+session. The agent submits a PyTorch `MIAgentModel` module; the benchmark
+scorer trains one model per subject on session T (230/58 stratified train/val
+split, fixed seed 42) and evaluates on session E (288-trial blind test).
+
+See the task README in the main repo for the full contract.
+
+## Provenance & license
+
+GDF files come from the BCI Competition IV Dataset 2a (Graz). License
+Apache-2.0 (see repo `LICENSE`). See
+<https://www.bbci.de/competition/iv/> for the original release.

bciciv-2a/public.tar.zst

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+size 202714474

sleep-edf/README.md

@@ -0,0 +1,37 @@
+# sleep-edf — public training data
+
+Public-side data for BrainPilotBench task
+[`tasks/sleep-edf`](https://github.com/NeuroAIHub/BrainPilotBench/tree/main/tasks/sleep-edf).
+
+Held-out subject 16-19 evaluation recordings live in the gated companion
+dataset
+[`BrainPilot-Bench/Tasks-Data-Private`](https://huggingface.co/datasets/BrainPilot-Bench/Tasks-Data-Private)
+and never appear as "test" here.
+
+## Files
+
+| File | Contents | Size |
+|---|---|---|
+| `public-main.tar.zst` | `sleep-cassette/SC4[0-1][0-5][12]E[0-9]-PSG.edf` + `-Hypnogram.edf` (subjects **0–15**, 32 files), `manifests/{subjects.json,default_split.json,loso_folds.json}`, `get_fold_data.py`, `label_mapping.json`, `README.md` | ~ 934 MB |
+| `loso-supplement.tar.zst` | Additional PSG+Hypnogram for subjects **16-19** (16 files) — **only** for agents that want to run the 20-fold LOSO protocol over all 20 subjects. Do NOT use as test data under the default split. | ~ 235 MB |
+
+`public-main.tar.zst` is the default fetch and pinned in the task's
+`data.lock`. `loso-supplement.tar.zst` is optional and only needed for LOSO
+runs; the task's data.lock exposes it as an opt-in dataset (`bp-bench fetch
+sleep-edf --extra loso`).
+
+## Task summary
+
+Sleep-EDF Expanded — Sleep Cassette. 5-class sleep stage classification
+(Wake / N1 / N2 / N3 / REM) on 30-second Fpz-Cz EEG epochs. 20 subjects
+split by subject boundary: train subjects 0-13, validation 14-15, test
+16-19 (private). The agent submits a PyTorch `SleepAgentModel` module; the
+benchmark scorer trains one model on subjects 0-13, uses 14-15 for early
+stopping, and blind-tests on 16-19.
+
+See the task README in the main repo for the full contract.
+
+## Provenance & license
+
+Sleep-EDF Database Expanded v1.0.0 — <https://physionet.org/content/sleep-edfx/1.0.0/>.
+Files are re-hosted under the same open license as PhysioNet.

sleep-edf/loso-supplement.tar.zst

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+size 246263414

sleep-edf/public-main.tar.zst

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