nm000365 NEMAR-native dataset

Du-IN Chinese word-reading sEEG (Zheng et al., NeurIPS 2024): authors' preprocessed 3-s epochs, 12 subjects, 61 words

Preprocessed stereo-EEG (sEEG) recordings from 12 epilepsy patients reading 61 Chinese words aloud, packaged in BIDS from the Du-IN release (Zheng et al., NeurIPS 2024). The data are the authors' band-pass filtered, resampled, bipolar-referenced 3-second word-labelled epochs, stored back to back in BrainVision files, with word labels and English translations in the events files. The dataset supports research on speech decoding from intracranial neural signals.

IEEG
Issues GitHub

Download this dataset

dataset 130.5 GB exceeds 100.0 GB archive limit; use direct download. Use one of the streaming methods below — all resumable. Full download guide →

  1. NEMAR CLI recommended

    Pulls the pinned version + annexed data and resumes cleanly. Install nemar-cli → 

    nemar dataset download nm000365
  2. DataLad

    Clone the dataset repo and fetch file content on demand. Docs → 

    datalad clone https://github.com/nemarDatasets/nm000365 nm000365
cd nm000365 && datalad get .
  3. git-annex

    Plain git + git-annex against the dataset repo. Docs → 

    git clone https://github.com/nemarDatasets/nm000365 nm000365
cd nm000365 && git annex get .
  4. Direct files (wget / curl / rclone)

    Every file with a stable, range-resumable URL from the manifest. Needs curl, jq, wget (or rclone/aria2c). Docs → 

    curl -s https://data.nemar.org/nm000365/v1.0.0/manifest.json | jq -r '.[].bytes_url' > urls.txt
wget -xc -i urls.txt

Compute on this dataset

Two routes today, with a third (in-browser one-click submission) landing soon.

  1. NeuroScience Gateway (NSG) portal.

    NSG runs EEGLAB / Brainstorm / MNE pipelines on supercomputing time donated by SDSC. Create an account, point a job at this dataset's S3 prefix (s3://nemar/nm000365), and submit.
    nsgportal.org →

  2. Local processing with nemar-cli.

    Pull the dataset to your machine and run any toolbox locally. Honors the published version pinning. 

    npm install -g nemar-cli
nemar dataset clone nm000365
cd nm000365 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000365/ — the manifest carries presigned S3 URLs.

Direct compute access is coming soon. One-click NSG submission from this page is scoped for a follow-up phase. Tracked on nemarOrg/website#6.

Citations

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    Files

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    Signal viewer
    How to use the data (for agentic research) license, citation, download commands

    What it is

    Modalities
    IEEG
    Participants
    12
    Size
    130 GB
    Tasks
    wordreading

    License and terms

    License
    CC-BY-4.0
    Recommended citation
    Zheng, H., Wang, H., Jiang, W., Chen, Z., He, L., Lin, P., Wei, P., Zhao, G., & Liu, Y. (2026). Du-IN Chinese word-reading sEEG (Zheng et al., NeurIPS 2024): authors' preprocessed 3-s epochs, 12 subjects, 61 words (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000365

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000365/latest/
    This version (v1.0.0)
    https://data.nemar.org/nm000365/v1.0.0/

    How to download

    The dataset
    nemar dataset download nm000365 Clones and fetches in one step. Content under stimuli/ and derivatives/ is skipped by default because those trees can be large; add --stimuli --derivatives for the whole thing.
    A subset, one step
    nemar dataset download nm000365 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000365 Clones git-annex pointers only; fetches no file content. Creates ./nm000365.
    A subset, step 2
    cd nm000365 The get command below reads the clone's annex, so it only works from inside the clone.
    A subset, step 3
    nemar dataset get <files> Pulls the files you actually need. Skips stimuli/ and derivatives/ unless the path you ask for is under one of them.
    One small file
    https://data.nemar.org/nm000365/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/nm000365/v1.0.0/participants.tsv
    Dataset description
    https://data.nemar.org/nm000365/v1.0.0/dataset_description.json
    Directory listing
    https://data.nemar.org/nm000365/v1.0.0/?format=json
    Catalog record
    https://api.nemar.org/datasets/nm000365