nm000259 NEMAR-native dataset

Speier et al. 2017 — A comparison of stimulus types in online classification of the P300 speller using language models

This dataset comprises EEG recordings from 10 healthy participants performing a P300 speller task using a 6×6 character matrix. The study compares two stimulus conditions—famous faces and inverting—to evaluate their effects on online P300 classification performance using language models. Data were collected across 2 sessions per subject with 3 runs per session, sampled at 256 Hz from 32 EEG channels.

EEG

Download zip Issues GitHub

Compute on this dataset

Two routes today, with a third (in-browser one-click submission) landing soon.

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/nm000259), and submit.
nsgportal.org →
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 nm000259
cd nm000259 && nemar dataset get
```
Just the files.
rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000259/ — 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.nm000259

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Files

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