on006647
NEMAR copy of ds006647

Poetry Assessment EEG Dataset 2

This dataset comprises 64-channel EEG recordings and behavioral ratings from 4 participants (P105, P141, P142, P146; anonymized as sub-001 to sub-004 in BIDS format) who evaluated 210 short English-language texts (70 Haiku, 70 Senryu, and 70 control texts) on five subjective dimensions: Aesthetic Appeal, Vivid Imagery, Being Moved, Originality, and Creativity. IMPORTANT: These 4 participants were EXCLUDED from primary analyses due to segmented EEG recordings acquired in multiple sessions and subsequently concatenated during preprocessing, which introduced potential artifacts. This is a companion dataset to Poetry Assessment EEG Dataset 1 (47 participants with validated continuous recordings used in primary analyses). Poetry Assessment EEG Dataset 2 is included for completeness and transparency, enabling users to apply their own quality control pipelines if desired. The dataset includes resting-state EEG (trigger codes: 65285, 65286 for pre-experiment; 65287, 65288 for post-experiment), trial-by-trial behavioral ratings, and psychometric responses (PANAS, Openness, Curiosity, VVIQ, AVIQ, MAAS, AReA), enabling investigation of neural correlates of aesthetic and creative cognition during poetic language processing. All preprocessing steps, event markers, and metadata structures were applied identically across both Poetry Assessment EEG datasets.

EEG
Issues GitHub OpenNeuro ds006647

Download this dataset

Pick a method. Large datasets skip the zip and use the streaming methods below — all resumable. Full download guide →

  1. Download archive (.zip) — 3.8 GB

    A single zip of the published version. Best for small/medium datasets.

    Download zip

  2. NEMAR CLI recommended

    Pulls the pinned version + annexed data and resumes cleanly. Install nemar-cli → 

    nemar dataset download on006647
  3. DataLad

    Clone the dataset repo and fetch file content on demand. Docs → 

    datalad clone https://github.com/nemarDatasets/on006647 on006647
cd on006647 && datalad get .
  4. git-annex

    Plain git + git-annex against the dataset repo. Docs → 

    git clone https://github.com/nemarDatasets/on006647 on006647
cd on006647 && git annex get .
  5. Direct files (wget / curl / rclone)

    Every file with a stable, range-resumable URL from the manifest. Needs curl, jq, wget (or rclone/aria2c). Docs → 

    curl -s https://data.nemar.org/on006647/v1.0.0/manifest.json | jq -r '.[].bytes_url' > urls.txt
wget -xc -i urls.txt

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/on006647), 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 on006647
cd on006647 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/on006647/ — 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.

Citations

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