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on005028 NEMAR · OpenNeuro mirror

Comparing P300 Flashing paradigms in online typing with language models

Imported from OpenNeuro ds005028

Download zip Issues GitHub OpenNeuro ds005028

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/on005028), 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 on005028
cd on005028 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/on005028/ — 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.on005028

NEMAR-curated copy of OpenNeuro ds005028

This is the NEMAR-curated copy. We pull from OpenNeuro periodically; each pull is a major version bump (vN.0.0). Versions between pulls (vN.x.y) are NEMAR-side fixes and improvements.

NEMAR DOI
on005028 10.82901/nemar.on005028
OpenNeuro DOI
unknown
View original on OpenNeuro View as-imported mirror (v1.0.0)

![DOI](https://doi.org/10.82901/nemar.on005028)

This dataset was created using BCI2000. The goal of this study was to explore the online typing performance of the P300 speller using language models and various flashing paradigms. For more information see Chandravadia et al. (https://www.medrxiv.org/content/10.1101/2022.06.24.22276882v1).

If you reference this dataset in your publications, please acknowledge its authors.

This dataset is made available under CC0.

Note: subject 5 was not included in the analysis because the testing stage did not include all three flashing paradigms.

Files

15 top-level entries · 1.46 GB total