nm000127 NEMAR-native dataset

Kim2025 – 40-class beta-range SSVEP speller dataset

A 40-class steady-state visually evoked potential (SSVEP) brain-computer interface speller dataset acquired from 40 healthy subjects using beta-range stimulation frequencies (14.0–21.8 Hz) to reduce visual fatigue. The dataset comprises 33-channel EEG recordings (31 scalp + 2 mastoid references) sampled at 1024 Hz across 6 sessions per subject, with 240 trials total using the joint frequency-phase modulation (JFPM) approach. This resource supports the development and benchmarking of low-fatigue BCI applications for communication interfaces.

EEG

Issues GitHub

Download this dataset

Pick a method. Large datasets skip the zip and use the streaming methods below — all resumable. Full download guide →

Download archive (.zip) — 14.9 GB
A single zip of the published version. Best for small/medium datasets.

Download zip
NEMAR CLI recommended
Pulls the pinned version + annexed data and resumes cleanly. Install nemar-cli →
```
nemar dataset download nm000127
```

DataLad

Clone the dataset repo and fetch file content on demand. Docs →

datalad clone https://github.com/nemarDatasets/nm000127 nm000127
cd nm000127 && datalad get .

git-annex

Plain git + git-annex against the dataset repo. Docs →

git clone https://github.com/nemarDatasets/nm000127 nm000127
cd nm000127 && git annex get .

Direct files (wget / curl / rclone)
Every file with a stable, range-resumable URL from the manifest. Needs curl, jq, wget (or rclone/aria2c). Docs →
```
curl -s https://data.nemar.org/nm000127/v1.0.2/manifest.json | jq -r '.[].bytes_url' > urls.txt
wget -xc -i urls.txt
```

Compute on this dataset

Two routes today, with a third (in-browser one-click submission) landing soon.

NeuroScience Gateway (NSG) portal.
NSG runs EEGLAB / Brainstorm / MNE pipelines on supercomputing time donated by SDSC. Create an account, point a job at this dataset's S3 prefix (s3://nemar/nm000127), and submit.
nsgportal.org →
Local processing with nemar-cli.
Pull the dataset to your machine and run any toolbox locally. Honors the published version pinning.
```
npm install -g nemar-cli
nemar dataset clone nm000127
cd nm000127 && nemar dataset get
```
Just the files.
rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000127/ — the manifest carries presigned S3 URLs.

Direct compute access is coming soon. One-click NSG submission from this page is scoped for a follow-up phase. Tracked on nemarOrg/website#6.

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Files

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How to use the data (for agentic research) license, citation, download commands

What it is

Modalities: EEG
Participants: 40
Size: 16.5 GB
Tasks: ssvep

License and terms

License: CC BY 4.0
Recommended citation: Kim, H., Won, K., Ahn, M., & Jun, S. C. (2026). Kim2025 – 40-class beta-range SSVEP speller dataset (Version v1.0.2) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000127
Reference: https://doi.org/10.6084/m9.figshare.28806815.v2

Where the bytes are

Latest version (always current): https://data.nemar.org/nm000127/latest/
This version (v1.0.2): https://data.nemar.org/nm000127/v1.0.2/

How to download

The dataset: nemar dataset download nm000127 Clones 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 nm000127 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
A subset, step 1: nemar dataset clone nm000127 Clones git-annex pointers only; fetches no file content. Creates ./nm000127.
A subset, step 2: cd nm000127 The 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/nm000127/v1.0.2/participants.tsv A direct HTTPS fetch works for any single file.

Assess fit without downloading

Participants table: https://data.nemar.org/nm000127/v1.0.2/participants.tsv
Dataset description: https://data.nemar.org/nm000127/v1.0.2/dataset_description.json
Directory listing: https://data.nemar.org/nm000127/v1.0.2/?format=json
Catalog record: https://api.nemar.org/datasets/nm000127