nm000198 NEMAR-native dataset

BNCI 2015-008 Center Speller P300 dataset

A P300-based brain-computer interface dataset comprising EEG recordings from 13 healthy participants performing a visual speller task using covert spatial attention and feature attention mechanisms. The dataset includes data from three speller variants (Hex-o-Spell, Cake Speller, and Center Speller) with preprocessed 63-channel EEG signals. For offline ERP analysis, data were downsampled to 250 Hz and lowpass filtered below 49 Hz. For online classification, data were downsampled to 100 Hz. This derivative dataset was processed through the Mother of All BCI Benchmarks (MOABB) framework. Original study: Treder, M. S., Schmidt, N. M., & Blankertz, B. (2011). Gaze-independent brain-computer interfaces based on covert attention and feature attention. Journal of Neural Engineering, 8(6), 066003.

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/nm000198), 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 nm000198
cd nm000198 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000198/ — 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.nm000198

Loading demographics…

Files

Loading file index…