NEMAR copy of ds008082
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 COVID-19 survivors and close contacts EEG dataset
This dataset comprises resting-state EEG recordings from 173 individuals, including 86 healthy close contacts and 87 COVID-19 survivors, collected at the Cuban Neuroscience Center. The dataset was designed to characterize EEG signatures associated with COVID-19 survival and to compare them with a Cuban EEG normative database. Recordings were obtained using a standard 10-20 montage under resting conditions with eyes closed and alternating eyes open/closed periods.
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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
- 173
- Size
- 1.10 GB
- Tasks
- COVID
License and terms
- License
- CC0
- Recommended citation
- Calzada-Reyes, A., Aubert-Vázquez, E., Galán-García, L., Bringas-Vega, M. L., Virués-Alba, T., Charroó-Ruiz, L., Acosta-Imás, Y., Valdés-Sosa, M., Perez-Mayo, L., Gutiérrez-Gil, J., Caballero-Moreno, A., Alvarez, M. A., Santiesteban, N., Sánchez-Lopez, J. V., Valdés-Virués, A., Varona-Galindo, E. E., Méndez-Parra, E., Castro-Valiente, J., Ramos-Hernández, L., Whilby-Santiesteban, M., Carrillo-Alfonso, T. L., Yasir, S., Kin, Y., Ren, P., Yao, D., Cheng, L., Rodriguez-Labrada, R., & Valdés-Sosa, P. (2026). A COVID-19 survivors and close contacts EEG dataset (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.on008082
Where the bytes are
- Latest version (always current)
- https://data.nemar.org/on008082/latest/
- This version (v1.0.0)
- https://data.nemar.org/on008082/v1.0.0/
How to download
- The dataset
-
nemar dataset download on008082Clones 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 on008082 --subjects sub-01,02Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude. - A subset, step 1
-
nemar dataset clone on008082Clones git-annex pointers only; fetches no file content. Creates ./on008082. - A subset, step 2
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cd on008082The 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/on008082/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.
Assess fit without downloading
- Participants table
- https://data.nemar.org/on008082/v1.0.0/participants.tsv
- Dataset description
- https://data.nemar.org/on008082/v1.0.0/dataset_description.json
- Directory listing
- https://data.nemar.org/on008082/v1.0.0/?format=json
- Catalog record
- https://api.nemar.org/datasets/on008082
Working with the Zarr copy
- 1. Start at the index
- https://zarr.nemar.org/on008082/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/on008082/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).