nm000127 NEMAR-native dataset

Kim2025 – 40-class beta-range SSVEP speller dataset

A 40-class steady-state visually evoked potential (SSVEP) brain-computer interface dataset designed to reduce visual fatigue through beta-range frequency stimulation (14.0–21.8 Hz). The dataset comprises 33-channel EEG recordings from 40 healthy participants performing a speller task across 6 sessions, with stimuli presented using the joint frequency-phase modulation (JFPM) approach. This resource supports the development and benchmarking of low-fatigue BCI applications.

EEG
Download zip Issues GitHub

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/nm000127), 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 nm000127
cd nm000127 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000127/ — 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.
DOI 10.82901/nemar.nm000127

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Files

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