nm000351 NEMAR-native dataset

Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study P)

BigP3BCI Study P is a P300-based brain-computer interface dataset comprising EEG recordings from 19 healthy subjects across 2 sessions each, using a 9x8 character grid spelling paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 montage, annotated with target and non-target visual stimulus events. This derivative dataset is part of the largest public P300 BCI dataset collection, and is optimized for machine learning applications in BCI research.

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/nm000351), 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 nm000351
cd nm000351 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000351/ — 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.nm000351

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Files

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