NEMAR copy of ds004998
You're viewing the NEMAR copy at v1.0.0.
Each OpenNeuro pull is a NEMAR major bump
(vN.0.0); intermediate versions are NEMAR-side fixes.
Exploring the electrophysiology of Parkinson's disease - magnetoencephalography combined with deep brain recordings from the subthalamic nucleus.
This dataset contains simultaneous magnetoencephalography (MEG) and subthalamic nucleus local field potential (STN LFP) recordings from externalized deep brain stimulation (DBS) patients with Parkinson's disease. Recordings were acquired with and without dopaminergic medication during rest, static forearm extension (hold), and self-paced fist-clenching (move). The project aimed to characterize basal ganglia-cortex loop neurophysiology and how it is modulated by movement and medication.
AI-generated description, may include mistakesLoading demographics…
Coming soon. Per-file data-quality summaries are precomputed by the NEMAR processing pipeline. The static aggregate is on the way — tracked at nemar-cli#511.
Files
How to use the data (for agentic research) license, citation, download commands, Zarr access
What it is
- Modalities
- MEG
- Participants
- 20
- Size
- 162 GB
- Tasks
- HoldL, HoldR, MoveL, MoveR, Rest, noise
License and terms
- License
- CC0
- Recommended citation
- Rassoulou, F., Steina, A., Hartmann, C. J., Vesper, J., Butz, M., Schnitzler, A., & Hirschmann, J. (2026). Exploring the electrophysiology of Parkinson's disease - magnetoencephalography combined with deep brain recordings from the subthalamic nucleus. (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on004998
- Reference 1
- https://doi.org/10.21105/joss.01896
- Reference 2
- https://doi.org/10.1038/sdata.2018.110
Where the bytes are
- Latest version (always current)
- https://data.nemar.org/on004998/latest/
- This version (v1.0.0)
- https://data.nemar.org/on004998/v1.0.0/
How to download
- The dataset
-
nemar dataset download on004998Clones 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 on004998 --subjects sub-01,02Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude. - A subset, step 1
-
nemar dataset clone on004998Clones git-annex pointers only; fetches no file content. Creates ./on004998. - A subset, step 2
-
cd on004998The 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/on004998/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.
Assess fit without downloading
- Participants table
- https://data.nemar.org/on004998/v1.0.0/participants.tsv
- Dataset description
- https://data.nemar.org/on004998/v1.0.0/dataset_description.json
- Directory listing
- https://data.nemar.org/on004998/v1.0.0/?format=json
- Catalog record
- https://api.nemar.org/datasets/on004998
Working with the Zarr copy
- 1. Start at the index
- https://zarr.nemar.org/on004998/zarr/index.json The mandatory entry point. Never hardcode a bucket path.
- 2. Pick a store entry
-
stores[].zarr, stores[].groups[].nameThese 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/on004998/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 + offsetscale 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.jsonOnly 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=1This 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).