nm000126 NEMAR-native dataset

Wang2016 – SSVEP Wang 2016 dataset

A benchmark steady-state visual evoked potential (SSVEP) dataset comprising EEG recordings from 34 healthy subjects performing a 40-target brain-computer interface speller task using joint frequency and phase modulation. The dataset includes 64-channel EEG data sampled at 250 Hz with visual stimuli flickering at frequencies ranging from 8 to 15.8 Hz, designed to facilitate development and evaluation of SSVEP-based BCI algorithms.

EEG
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) — 6.5 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 nm000126
  3. DataLad

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

    datalad clone https://github.com/nemarDatasets/nm000126 nm000126
cd nm000126 && datalad get .
  4. git-annex

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

    git clone https://github.com/nemarDatasets/nm000126 nm000126
cd nm000126 && 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/nm000126/v1.0.2/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/nm000126), 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 nm000126
cd nm000126 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000126/ — 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

    What it is

    Modalities
    EEG
    Participants
    34
    Size
    6.48 GB
    Tasks
    ssvep

    License and terms

    License
    CC-BY-4.0
    Recommended citation
    Wang, Y., Chen, X., Gao, X., & Gao, S. (2026). Wang2016 – SSVEP Wang 2016 dataset (Version v1.0.2) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000126

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000126/latest/
    This version (v1.0.2)
    https://data.nemar.org/nm000126/v1.0.2/

    How to download

    The dataset
    nemar dataset download nm000126 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 nm000126 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000126 Clones git-annex pointers only; fetches no file content. Creates ./nm000126.
    A subset, step 2
    cd nm000126 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/nm000126/v1.0.2/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/nm000126/v1.0.2/participants.tsv
    Dataset description
    https://data.nemar.org/nm000126/v1.0.2/dataset_description.json
    Directory listing
    https://data.nemar.org/nm000126/v1.0.2/?format=json
    Catalog record
    https://api.nemar.org/datasets/nm000126