nm000379 NEMAR-native dataset

Rapid coordination of effective learning by the human hippocampus: intracranial EEG during scene recognition with eye tracking

Stereo-EEG recordings from six patients with medically refractory epilepsy performing a scene recognition memory task with concurrent EyeLink eye tracking. The dataset accompanies a study of how the human hippocampus rapidly coordinates effective learning, and is a lossless iEEG-BIDS re-packaging of the authors' public Zenodo release. It includes electrode MNI coordinates, behavioural arrays, eye-tracking files and the authors' analysis code in sourcedata.

IEEG
Issues GitHub

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) — 19.2 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 nm000379
  3. DataLad

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

    datalad clone https://github.com/nemarDatasets/nm000379 nm000379
cd nm000379 && datalad get .
  4. git-annex

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

    git clone https://github.com/nemarDatasets/nm000379 nm000379
cd nm000379 && 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/nm000379/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/nm000379), 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 nm000379
cd nm000379 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000379/ — 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
    IEEG
    Participants
    6
    Size
    41.7 GB
    Tasks
    scenerecognition

    License and terms

    License
    CC-BY-4.0
    Recommended citation
    Kragel, J. E., Schuele, S., VanHaerents, S., Rosenow, J. M., & Voss, J. L. (2026). Rapid coordination of effective learning by the human hippocampus: intracranial EEG during scene recognition with eye tracking (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000379

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000379/latest/
    This version (v1.0.0)
    https://data.nemar.org/nm000379/v1.0.0/

    How to download

    The dataset
    nemar dataset download nm000379 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 nm000379 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000379 Clones git-annex pointers only; fetches no file content. Creates ./nm000379.
    A subset, step 2
    cd nm000379 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/nm000379/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/nm000379/v1.0.0/participants.tsv
    Dataset description
    https://data.nemar.org/nm000379/v1.0.0/dataset_description.json
    Directory listing
    https://data.nemar.org/nm000379/v1.0.0/?format=json
    Catalog record
    https://api.nemar.org/datasets/nm000379