NEMAR copy of ds004504
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.
A dataset of EEG recordings from: Alzheimer's disease, Frontotemporal dementia and Healthy subjects
This dataset comprises resting-state, eyes-closed scalp EEG recordings from 88 subjects: 36 with Alzheimer's disease, 23 with Frontotemporal Dementia, and 29 healthy controls. Recordings were acquired using a Nihon Kohden EEG 2100 device with 19 electrodes at 500 Hz sampling rate, totaling approximately 1164 minutes of data. The dataset includes both raw and preprocessed versions with artifact correction, supporting machine learning and clinical research in dementia diagnosis and neurophysiological characterization.
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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
- EEG
- Participants
- 88
- Size
- 5.38 GB
- Tasks
- eyesclosed
License and terms
- License
- CC0
- Recommended citation
- Miltiadous, A., Tzimourta, K. D., Afrantou, T., Ioannidis, P., Grigoriadis, N., Tsalikakis, D. G., Angelidis, P., Tsipouras, M. G., Glavas, E., Giannakeas, N., & Tzallas, A. T. (2026). A dataset of EEG recordings from: Alzheimer's disease, Frontotemporal dementia and Healthy subjects (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on004504
Where the bytes are
- Latest version (always current)
- https://data.nemar.org/on004504/latest/
- This version (v1.0.0)
- https://data.nemar.org/on004504/v1.0.0/
How to download
- The dataset
-
nemar dataset download on004504Clones 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
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nemar dataset download on004504 --subjects sub-01,02Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude. - A subset, step 1
-
nemar dataset clone on004504Clones git-annex pointers only; fetches no file content. Creates ./on004504. - A subset, step 2
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cd on004504The 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/on004504/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.
Assess fit without downloading
- Participants table
- https://data.nemar.org/on004504/v1.0.0/participants.tsv
- Dataset description
- https://data.nemar.org/on004504/v1.0.0/dataset_description.json
- Directory listing
- https://data.nemar.org/on004504/v1.0.0/?format=json
- Catalog record
- https://api.nemar.org/datasets/on004504
Working with the Zarr copy
- 1. Start at the index
- https://zarr.nemar.org/on004504/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
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s3://nemar/on004504/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
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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
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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
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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
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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
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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
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root.attrs["nemar"]The store carries its own dataset id, DOI, license, citation and source commit. - 10. Filter for pipelines
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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).