Mixture of LLP and EM for a visual matrix speller (ERP) dataset from
This dataset comprises EEG recordings from a P300 visual matrix speller study comparing three unsupervised learning methods (Expectation-Maximization, Learning from Label Proportions, and their combination MIX) for brain-computer interface decoding. Twelve healthy participants performed a copy-spelling task using a modified 6×6 character grid extended with 10 # symbols as visual blanks (46 total symbols), recorded at 1000 Hz from 31 EEG channels. The study demonstrates that unsupervised learning methods can achieve performance comparable to supervised approaches without requiring calibration data.
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
What it is
- Modalities
- EEG
- Participants
- 12
- Size
- 4.81 GB
- Tasks
- p300
License and terms
- License
- CC-BY-4.0
- Recommended citation
- Hübner, D., Verhoeven, T., Müller, K., Kindermans, P., & Tangermann, M. (2026). Mixture of LLP and EM for a visual matrix speller (ERP) dataset from (Version v1.0.2) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000195
Where the bytes are
- Latest version (always current)
- https://data.nemar.org/nm000195/latest/
- This version (v1.0.2)
- https://data.nemar.org/nm000195/v1.0.2/
How to download
- The dataset
-
nemar dataset download nm000195Clones 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 nm000195 --subjects sub-01,02Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude. - A subset, step 1
-
nemar dataset clone nm000195Clones git-annex pointers only; fetches no file content. Creates ./nm000195. - A subset, step 2
-
cd nm000195The 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/nm000195/v1.0.2/participants.tsv A direct HTTPS fetch works for any single file.
Assess fit without downloading
- Participants table
- https://data.nemar.org/nm000195/v1.0.2/participants.tsv
- Dataset description
- https://data.nemar.org/nm000195/v1.0.2/dataset_description.json
- Directory listing
- https://data.nemar.org/nm000195/v1.0.2/?format=json
- Catalog record
- https://api.nemar.org/datasets/nm000195