nm000130 NEMAR-native dataset

Liu2022 – eldBETA SSVEP benchmark dataset for elderly population

This dataset (eldBETA) provides 64-channel SSVEP-BCI EEG recordings from 100 elderly participants (aged 51-81, mean 63.17 years) performing a 9-target speller task using joint frequency and phase modulation (JFPM) stimuli. Each subject completed 7 sessions of 7 blocks with 9 trials each, recorded at 1000 Hz using a Synamps2 (Neuroscan) amplifier with a Cz reference. The dataset is intended as a benchmark for SSVEP-BCI algorithms in aging populations and has been converted to BIDS format with HED event annotations for use in the MOABB benchmarking framework.

EEG Zarr verified
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) — 33.1 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 nm000130
  3. DataLad

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

    datalad clone https://github.com/nemarDatasets/nm000130 nm000130
cd nm000130 && datalad get .
  4. git-annex

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

    git clone https://github.com/nemarDatasets/nm000130 nm000130
cd nm000130 && 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/nm000130/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/nm000130), 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 nm000130
cd nm000130 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000130/ — 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
    100
    Size
    34.8 GB
    Tasks
    ssvep
    HED version
    8.4.0

    License and terms

    License
    CC BY 4.0
    Recommended citation
    Liu, B., Wang, Y., Gao, X., & Chen, X. (2026). Liu2022 – eldBETA SSVEP benchmark dataset for elderly population (Version v1.0.3) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000130
    Reference 1
    https://doi.org/10.6084/m9.figshare.18032669
    Reference 2
    https://doi.org/10.21105/joss.01896
    Reference 3
    https://doi.org/10.1038/s41597-019-0104-8

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000130/latest/
    This version (v1.0.3)
    https://data.nemar.org/nm000130/v1.0.3/

    How to download

    The dataset
    nemar dataset download nm000130 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 nm000130 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000130 Clones git-annex pointers only; fetches no file content. Creates ./nm000130.
    A subset, step 2
    cd nm000130 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/nm000130/v1.0.3/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/nm000130/v1.0.3/participants.tsv
    Dataset description
    https://data.nemar.org/nm000130/v1.0.3/dataset_description.json
    Directory listing
    https://data.nemar.org/nm000130/v1.0.3/?format=json
    Catalog record
    https://api.nemar.org/datasets/nm000130

    Working with the Zarr copy

    1. Start at the index
    https://zarr.nemar.org/nm000130/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/nm000130/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).