on000117
NEMAR copy of ds000117

Multisubject, multimodal face processing

This dataset comprises multi-subject, multimodal neuroimaging data (structural MRI, fMRI, MEG, and EEG) collected during a face processing task, in which participants viewed famous, unfamiliar, and scrambled faces presented under initial, immediate repeat, and delayed repeat conditions. It is a BIDS-formatted subset of the original Wakeman & Henson (2015) dataset, designed to support research on multimodal integration of brain imaging data and studies of face recognition and repetition effects.

ANAT BEH DWI FMAP FUNC MEG
Issues GitHub OpenNeuro ds000117

Download this dataset

Archive (>100 GB) removed to save space; use the per-file direct download (#752).. Use one of the streaming methods below — all resumable. Full download guide →

  1. NEMAR CLI recommended

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

    nemar dataset download on000117
  2. DataLad

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

    datalad clone https://github.com/nemarDatasets/on000117 on000117
cd on000117 && datalad get .
  3. git-annex

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

    git clone https://github.com/nemarDatasets/on000117 on000117
cd on000117 && git annex get .
  4. 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/on000117/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/on000117), 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 on000117
cd on000117 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/on000117/ — 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
    ANAT, BEH, DWI, FMAP, FUNC, MEG
    Participants
    17
    Size
    169 GB
    Tasks
    facerecognition, noise

    License and terms

    License
    CC0
    Recommended citation
    Wakeman, D. G., & Henson, R. N. (2026). Multisubject, multimodal face processing (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on000117

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/on000117/latest/
    This version (v1.0.0)
    https://data.nemar.org/on000117/v1.0.0/

    How to download

    The dataset
    nemar dataset download on000117 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 on000117 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone on000117 Clones git-annex pointers only; fetches no file content. Creates ./on000117.
    A subset, step 2
    cd on000117 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/on000117/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.

    Assess fit without downloading

    Participants table
    https://data.nemar.org/on000117/v1.0.0/participants.tsv
    Dataset description
    https://data.nemar.org/on000117/v1.0.0/dataset_description.json
    Directory listing
    https://data.nemar.org/on000117/v1.0.0/?format=json
    Catalog record
    https://api.nemar.org/datasets/on000117