on003774
NEMAR copy of ds003774

Music Listening- Genre EEG dataset (MUSIN-G)

This dataset contains electroencephalography (EEG) recordings from 20 Indian participants who listened to 12 songs spanning genres from Indian Classical to Goth Rock. After each song, participants rated their familiarity with and enjoyment of it on a 5-point scale. The data support research on music perception, genre, and affective responses to music.

EEG
Issues GitHub OpenNeuro ds003774

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) — 9.6 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 on003774
  3. DataLad

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

    datalad clone https://github.com/nemarDatasets/on003774 on003774
cd on003774 && datalad get .
  4. git-annex

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

    git clone https://github.com/nemarDatasets/on003774 on003774
cd on003774 && 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/on003774/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/on003774), 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 on003774
cd on003774 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/on003774/ — 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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    Files

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    Signal viewer
    How to use the data (for agentic research) license, citation, download commands

    What it is

    Modalities
    EEG
    Participants
    20
    Size
    10.1 GB
    Tasks
    MusicListening

    License and terms

    License
    CC0
    Recommended citation
    Miyapuram, K. P., Pandey, P., Ahmad, N., Shiraguppi, B. R., Sharma, E., Lawhatre, P., Sonawane, D., & Lomas, D. (2026). Music Listening- Genre EEG dataset (MUSIN-G) (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on003774

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/on003774/latest/
    This version (v1.0.0)
    https://data.nemar.org/on003774/v1.0.0/

    How to download

    The dataset
    nemar dataset download on003774 Clones and fetches in one step. Content under stimuli/ and derivatives/ is skipped by default because those trees can be large; add --stimuli --derivatives for the whole thing.
    A subset, one step
    nemar dataset download on003774 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone on003774 Clones git-annex pointers only; fetches no file content. Creates ./on003774.
    A subset, step 2
    cd on003774 The get command below reads the clone's annex, so it only works from inside the clone.
    A subset, step 3
    nemar dataset get <files> Pulls the files you actually need. Skips stimuli/ and derivatives/ unless the path you ask for is under one of them.
    One small file
    https://data.nemar.org/on003774/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/on003774/v1.0.0/participants.tsv
    Dataset description
    https://data.nemar.org/on003774/v1.0.0/dataset_description.json
    Directory listing
    https://data.nemar.org/on003774/v1.0.0/?format=json
    Catalog record
    https://api.nemar.org/datasets/on003774