MEG: Major Depression & Probabilistic Learning Task

Magnetoencephalography (MEG) recordings from participants with major depressive disorder and non-depressed controls performing a probabilistic selection reinforcement learning task. The dataset was collected to examine the Reward Positivity and related ventromedial frontal cortex activity during feedback processing. It includes 90 participants, 52 with MDD and 38 controls, all screened using the SCID interview. T1 anatomical and resting-state data are planned to be added in a later release. Associated publication: Pirrung, C.J.H., Singh, G., Hogeveen, J., Quinn, D. & Cavanagh, J.F. (2025), Hypoactivation of ventromedial frontal cortex in major depressive disorder: an MEG study of the Reward Positivity. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging.

MEG

Issues GitHub OpenNeuro ds005356

Download this dataset

dataset 162.4 GB exceeds 100.0 GB archive limit; use direct download. Use one of the streaming methods below — all resumable. Full download guide →

NEMAR CLI recommended
Pulls the pinned version + annexed data and resumes cleanly. Install nemar-cli →
```
nemar dataset download on005356
```

DataLad

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

datalad clone https://github.com/nemarDatasets/on005356 on005356
cd on005356 && datalad get .

git-annex

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

git clone https://github.com/nemarDatasets/on005356 on005356
cd on005356 && git annex get .

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/on005356/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.

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/on005356), and submit.
nsgportal.org →
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 on005356
cd on005356 && nemar dataset get
```
Just the files.
rclone, aria2c, or any HTTPS client works against data.nemar.org/on005356/ — 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.

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Files

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

What it is

Modalities: MEG
Participants: 85
Size: 162 GB
Tasks: pst

License and terms

License: CC0
Recommended citation: [Unspecified] (2026). MEG: Major Depression & Probabilistic Learning Task (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on005356

Where the bytes are

Latest version (always current): https://data.nemar.org/on005356/latest/
This version (v1.0.0): https://data.nemar.org/on005356/v1.0.0/

How to download

The dataset: nemar dataset download on005356 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 on005356 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
A subset, step 1: nemar dataset clone on005356 Clones git-annex pointers only; fetches no file content. Creates ./on005356.
A subset, step 2: cd on005356 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/on005356/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.

Assess fit without downloading

Participants table: https://data.nemar.org/on005356/v1.0.0/participants.tsv
Dataset description: https://data.nemar.org/on005356/v1.0.0/dataset_description.json
Directory listing: https://data.nemar.org/on005356/v1.0.0/?format=json
Catalog record: https://api.nemar.org/datasets/on005356