nm000204 NEMAR-native dataset

Bluetooth speaker experiment (14 subjects, 6 classes, 31 EEG ch)

A P300-based brain-computer interface dataset for home appliance control, comprising EEG recordings from 14 healthy subjects performing a visual oddball task with 31-channel recordings at 500 Hz sampling rate. The dataset includes 50 training and 30 testing blocks per subject, with target and non-target stimulus classifications presented via LCD display in an online BCI paradigm.

AI-generated description, may include mistakes
Issues GitHub

Download this dataset

Pick a method. Large datasets skip the zip and use the streaming methods below — all resumable. Full download guide →

  1. Download archive (.zip) — 0.6 GB

    A single zip of the published version. Best for small/medium datasets.

    Download zip

  2. NEMAR CLI recommended

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

    nemar dataset download nm000204
  3. DataLad

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

    datalad clone https://github.com/nemarDatasets/nm000204 nm000204
    cd nm000204 && datalad get .
  4. git-annex

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

    git clone https://github.com/nemarDatasets/nm000204 nm000204
    cd nm000204 && git annex get .
  5. 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/nm000204/v1.0.3/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/nm000204), 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 nm000204
    cd nm000204 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000204/ — 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
    EEG
    Participants
    14
    Size
    644 MB
    Tasks
    p300

    License and terms

    License
    CC-BY-4.0
    Recommended citation
    Lee, J., Kim, M., Heo, D., Kim, J., Kim, M., Lee, T., Park, J., Kim, H., Hwang, M., Kim, L., & Kim, S. (2026). Bluetooth speaker experiment (14 subjects, 6 classes, 31 EEG ch) (Version v1.0.3) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000204

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000204/latest/

    How to download

    The dataset
    nemar dataset download nm000204 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 nm000204 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000204 Clones git-annex pointers only; fetches no file content. Creates ./nm000204.
    A subset, step 2
    cd nm000204 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/nm000204/v1.0.3/participants.tsv A direct HTTPS fetch works for any single file.