on003710
NEMAR copy of ds003710

APPLESEED Example Dataset

A longitudinal EEG dataset from 13 infants recorded at 4, 8, and 12 months of age, comprising 48 recording sessions. The dataset includes test-retest reliability assessments at 4 months (11 infants with complete longitudinal data, 2 infants with reliability data only) and was used to develop and validate APPLESEED, an automated preprocessing pipeline for estimating scale-wise entropy from pediatric EEG data. This example dataset accompanies the 2022 APPLESEED pipeline publication in Developmental Cognitive Neuroscience and demonstrates the application of entropy-based EEG analysis methods in early human development. The dataset is part of a larger longitudinal study initially described in Puglia et al. (2020).

EEG
Issues GitHub OpenNeuro ds003710

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) — 9.0 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 on003710
  3. DataLad

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

    datalad clone https://github.com/nemarDatasets/on003710 on003710
cd on003710 && datalad get .
  4. git-annex

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

    git clone https://github.com/nemarDatasets/on003710 on003710
cd on003710 && 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/on003710/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/on003710), 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 on003710
cd on003710 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/on003710/ — 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, Zarr access

    What it is

    Modalities
    EEG
    Participants
    13
    Size
    10.2 GB
    Tasks
    appleseedexample

    License and terms

    License
    CC0
    Recommended citation
    Williams, C. L., & Puglia, M. H. (2026). APPLESEED Example Dataset (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on003710

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/on003710/latest/
    This version (v1.0.0)
    https://data.nemar.org/on003710/v1.0.0/

    How to download

    The dataset
    nemar dataset download on003710 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 on003710 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone on003710 Clones git-annex pointers only; fetches no file content. Creates ./on003710.
    A subset, step 2
    cd on003710 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/on003710/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/on003710/v1.0.0/participants.tsv
    Dataset description
    https://data.nemar.org/on003710/v1.0.0/dataset_description.json
    Directory listing
    https://data.nemar.org/on003710/v1.0.0/?format=json
    Catalog record
    https://api.nemar.org/datasets/on003710

    Working with the Zarr copy

    1. Start at the index
    https://zarr.nemar.org/on003710/zarr/index.json The mandatory entry point. Never hardcode a bucket path.
    2. Pick a store entry
    stores[].zarr, stores[].groups[].name These two fields exist in every index format version, so a recipe that keys on them works against the whole catalog while the back conversion is still in flight.
    3. Build the store URI
    s3://nemar/on003710/zarr/{store.zarr} Derivable from the store entry alone. An index at format_version 3 or later also publishes contract_base, data_base and s3_uri; use them when they are there, never require them.
    4. Open the store anonymously
    zarr.open_group(store=..., mode="r", zarr_format=3) Anonymous FsspecStore.from_url in region us-east-2, no credentials. zarr_format=3 is required: without it zarr-python probes for Zarr v2 sidecars, and because anonymous ListBucket is denied, S3 answers a missing key with 403 rather than 404 and the open raises.
    5. Read the level-0 array
    root[store.groups[0].name]["0"] Level 0 is the full-rate signal. Never read a view/ array for inference; those exist for display.
    6. Dequantize the samples
    physical = digital * scale + offset scale and offset are attributes of the level-0 array, one entry per channel; the unit is on the group's channels attribute.
    7. Slice, don't download
    signal[0:4, 0:500] Stream a window of channels and samples; download only when you will touch most of the array.
    8. Know the HTTP contract
    index.json Only index.json is always proxied and edge-cached. A plain GET for a store object, manifest.json or events.parquet 302s to the public S3 object for non-browser clients, so follow redirects, and HEAD is never redirected.
    9. Read the attribution before reuse
    root.attrs["nemar"] The store carries its own dataset id, DOI, license, citation and source commit.
    10. Filter for pipelines
    has_zarr=1 This is the converted filter. has_zarr_verified is the stricter one, and its result set can be empty until the daily fidelity sweep reaches a dataset; verification is reported, never a precondition for serving (nemar-cli ADR 0005).