nm000323 NEMAR-native dataset

Lee et al. 2019 (ERP) — EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy

This dataset comprises EEG recordings from 54 healthy participants performing a P300-based brain-computer interface speller task, designed to investigate BCI illiteracy. The study includes 62 EEG channels and 4 EMG channels sampled at 1000 Hz, with participants completing offline training and online test phases using a 36-symbol row-column speller paradigm. The dataset achieved 96.7% accuracy with an 11.1% BCI illiteracy rate, providing a comprehensive resource for evaluating P300-based BCI performance and individual differences in BCI competence.

EEG
Issues GitHub

Download this dataset

dataset 131.7 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 nm000323
  2. DataLad

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

    datalad clone https://github.com/nemarDatasets/nm000323 nm000323
cd nm000323 && datalad get .
  3. git-annex

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

    git clone https://github.com/nemarDatasets/nm000323 nm000323
cd nm000323 && 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/nm000323/v1.0.4/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/nm000323), 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 nm000323
cd nm000323 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000323/ — 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

    Loading demographics…

    Files

    Loading file index…

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

    What it is

    Modalities
    EEG
    Participants
    54
    Size
    132 GB
    Tasks
    p300
    HED version
    8.4.0

    License and terms

    License
    GPL-3.0
    Recommended citation
    Lee, M., Kwon, O., Kim, Y., Kim, H., Lee, Y., Williamson, J., Fazli, S., & Lee, S. (2026). Lee et al. 2019 (ERP) — EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy (Version v1.0.4) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000323

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000323/latest/
    This version (v1.0.4)
    https://data.nemar.org/nm000323/v1.0.4/

    How to download

    The dataset
    nemar dataset download nm000323 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 nm000323 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000323 Clones git-annex pointers only; fetches no file content. Creates ./nm000323.
    A subset, step 2
    cd nm000323 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/nm000323/v1.0.4/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/nm000323/v1.0.4/participants.tsv
    Dataset description
    https://data.nemar.org/nm000323/v1.0.4/dataset_description.json
    Directory listing
    https://data.nemar.org/nm000323/v1.0.4/?format=json
    Catalog record
    https://api.nemar.org/datasets/nm000323

    Working with the Zarr copy

    1. Start at the index
    https://zarr.nemar.org/nm000323/zarr/index.json The mandatory entry point. Never hardcode a bucket path.
    2. Pick a store entry
    stores[].zarr, stores[].groups[].name These two fields exist in every index format version, so a recipe that keys on them works against the whole catalog while the back conversion is still in flight.
    3. Build the store URI
    s3://nemar/nm000323/zarr/{store.zarr} Derivable from the store entry alone. An index at format_version 3 or later also publishes contract_base, data_base and s3_uri; use them when they are there, never require them.
    4. Open the store anonymously
    zarr.open_group(store=..., mode="r", zarr_format=3) Anonymous FsspecStore.from_url in region us-east-2, no credentials. zarr_format=3 is required: without it zarr-python probes for Zarr v2 sidecars, and because anonymous ListBucket is denied, S3 answers a missing key with 403 rather than 404 and the open raises.
    5. Read the level-0 array
    root[store.groups[0].name]["0"] Level 0 is the full-rate signal. Never read a view/ array for inference; those exist for display.
    6. Dequantize the samples
    physical = digital * scale + offset scale and offset are attributes of the level-0 array, one entry per channel; the unit is on the group's channels attribute.
    7. Slice, don't download
    signal[0:4, 0:500] Stream a window of channels and samples; download only when you will touch most of the array.
    8. Know the HTTP contract
    index.json Only index.json is always proxied and edge-cached. A plain GET for a store object, manifest.json or events.parquet 302s to the public S3 object for non-browser clients, so follow redirects, and HEAD is never redirected.
    9. Read the attribution before reuse
    root.attrs["nemar"] The store carries its own dataset id, DOI, license, citation and source commit.
    10. Filter for pipelines
    has_zarr=1 This is the converted filter. has_zarr_verified is the stricter one, and its result set can be empty until the daily fidelity sweep reaches a dataset; verification is reported, never a precondition for serving (nemar-cli ADR 0005).