nm000239 NEMAR-native dataset
P-ary m-sequence-based c-VEP dataset from Martínez-Cagigal et al. (2023)
This dataset comprises EEG recordings from 16 healthy participants performing a code-modulated visual evoked potential (c-VEP) brain-computer interface task using p-ary m-sequences. The study investigates non-binary m-sequence stimulation patterns to enhance user comfort in c-VEP-based BCIs. Data were collected across 5 sessions per subject with 8 runs per session at 256 Hz sampling rate using 16 EEG channels, providing a comprehensive resource for BCI paradigm development and evaluation.
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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
What it is
- Modalities
- EEG
- Participants
- 16
- Size
- 1.71 GB
- Tasks
- cvep
License and terms
- License
- CC-BY-NC-SA-4.0
- Note
- Non-commercial use only (CC-BY-NC-SA-4.0).
- Recommended citation
- Martínez-Cagigal, V., Santamaría-Vázquez, E., Pérez-Velasco, S., Marcos-Martínez, D., Moreno-Calderón, S., & Hornero, R. (2026). P-ary m-sequence-based c-VEP dataset from Martínez-Cagigal et al. (2023) (Version v1.0.4) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000239
- Reference 1
- https://doi.org/10.71569/025s-eq10
- Reference 2
- https://doi.org/10.1016/j.eswa.2023.120815
- Reference 3
- https://doi.org/10.1088/1741-2552/ac38cf
- Reference 4
- https://doi.org/10.1016/j.cmpb.2023.107357
- Reference 5
- https://doi.org/10.21105/joss.01896
- Reference 6
- https://doi.org/10.1038/s41597-019-0104-8
- Reference 7
- https://doi.org/10.35376/10324/70945
Where the bytes are
- Latest version (always current)
- https://data.nemar.org/nm000239/latest/
- This version (v1.0.4)
- https://data.nemar.org/nm000239/v1.0.4/
How to download
- The dataset
-
nemar dataset download nm000239Clones 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 nm000239 --subjects sub-01,02Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude. - A subset, step 1
-
nemar dataset clone nm000239Clones git-annex pointers only; fetches no file content. Creates ./nm000239. - A subset, step 2
-
cd nm000239The 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/nm000239/v1.0.4/participants.tsv A direct HTTPS fetch works for any single file.
Assess fit without downloading
- Participants table
- https://data.nemar.org/nm000239/v1.0.4/participants.tsv
- Dataset description
- https://data.nemar.org/nm000239/v1.0.4/dataset_description.json
- Directory listing
- https://data.nemar.org/nm000239/v1.0.4/?format=json
- Catalog record
- https://api.nemar.org/datasets/nm000239