--- pretty_name: "Wang et al. 2024 — Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli" license: cc-by-4.0 tags: - ieeg - neuroscience - eegdash - brain-computer-interface - pytorch size_categories: - n<1K task_categories: - other --- # Wang et al. 2024 — Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli **Dataset ID:** `nm000253` _Wang2024_et_al_Brain_ **Canonical aliases:** `BrainTreeBank` > **At a glance:** IEEG · 10 subjects · 26 recordings · CC BY 4.0 ## Load this dataset This repo is a **pointer**. The raw EEG data lives at its canonical source (OpenNeuro / NEMAR); [EEGDash](https://github.com/eegdash/EEGDash) streams it on demand and returns a PyTorch / braindecode dataset. ```python # pip install eegdash from eegdash import EEGDashDataset ds = EEGDashDataset(dataset="nm000253", cache_dir="./cache") print(len(ds), "recordings") ``` You can also load it by canonical alias — these are registered classes in `eegdash.dataset`: ```python from eegdash.dataset import BrainTreeBank ds = BrainTreeBank(cache_dir="./cache") ``` If the dataset has been mirrored to the HF Hub in braindecode's Zarr layout, you can also pull it directly: ```python from braindecode.datasets import BaseConcatDataset ds = BaseConcatDataset.pull_from_hub("EEGDash/nm000253") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 10 | | **Recordings** | 26 | | **Tasks (count)** | 1 | | **Channels** | 164 (×8), 156 (×3), 166 (×3), 190 (×3), 136 (×3), 248 (×2), 218 (×2), 108 (×1), 158 (×1) | | **Sampling rate (Hz)** | 2048 (×26) | | **Total duration (h)** | 1.8 | | **Size on disk** | 257.3 GB | | **Recording type** | IEEG | | **Source** | nemar | | **License** | CC BY 4.0 | ## Links - **DOI:** [10.48550/arXiv.2411.08343](https://doi.org/10.48550/arXiv.2411.08343) - **NEMAR:** [nm000253](https://nemar.org/dataexplorer/detail?dataset_id=nm000253) - **Browse 700+ datasets:** [EEGDash catalog](https://huggingface.co/spaces/EEGDash/catalog) - **Docs:** - **Code:** --- _Auto-generated from [dataset_summary.csv](https://github.com/eegdash/EEGDash/blob/main/eegdash/dataset/dataset_summary.csv) and the [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/nm000253). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._