on007870
NEMAR copy of ds007870

Appleseed Audiobook MEG

This dataset contains magnetoencephalography (MEG) recordings from 12 participants listening to continuous narrative speech (an audiobook), plus an empty-room recording. It was collected to investigate how the brain integrates local and unified predictive linguistic models during incremental speech processing, examining neural signatures of sublexical, word-level, and sentence-level predictive representations. The dataset includes stimulus files (audio-derived gammatone features, TextGrid annotations) and derivatives (FreeSurfer outputs, MNE processing files, predictors).

MEG
Issues GitHub OpenNeuro ds007870

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) — 36.0 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 on007870
  3. DataLad

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

    datalad clone https://github.com/nemarDatasets/on007870 on007870
cd on007870 && datalad get .
  4. git-annex

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

    git clone https://github.com/nemarDatasets/on007870 on007870
cd on007870 && 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/on007870/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/on007870), 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 on007870
cd on007870 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/on007870/ — 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
    MEG
    Participants
    13
    Size
    41.6 GB
    Tasks
    Appleseed, Tone, noise

    License and terms

    License
    CC0
    Recommended citation
    Brodbeck, C., Bhattasali, S., Cruz Heredia, A. A., Resnik, P., Simon, J. Z., & Lau, E. (2026). Appleseed Audiobook MEG (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on007870

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/on007870/latest/
    This version (v1.0.0)
    https://data.nemar.org/on007870/v1.0.0/

    How to download

    The dataset
    nemar dataset download on007870 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 on007870 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone on007870 Clones git-annex pointers only; fetches no file content. Creates ./on007870.
    A subset, step 2
    cd on007870 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/on007870/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/on007870/v1.0.0/participants.tsv
    Dataset description
    https://data.nemar.org/on007870/v1.0.0/dataset_description.json
    Directory listing
    https://data.nemar.org/on007870/v1.0.0/?format=json
    Catalog record
    https://api.nemar.org/datasets/on007870