BCI Report Research previewP300 target ERP
The cBCI Matrix Multimodal Dataset (OpenNeuro ds006593) contains EEG and eye-tracking calibration recordings from 21 control participants performing a single-character-presentation matrix speller task in BciPy, recorded at Northeastern University in 2023 with a DSI-24 dry-electrode cap. Released on OpenNeuro in 2025 by Celik et al.
Also known as ds006593 · cBCI Matrix Multimodal Dataset · Multimodal Sensor Fusion for EEG-Based BCI Typing Systems · on006593
Description sources openneuro.org · nemar.org
Every figure below is copied from a reviewed download, not recomputed for this page. Read each group with its protocol on the linked page.
| Method | Condition | Metric | Value | People |
|---|---|---|---|---|
| Spectral ridge | Visual target versus nontarget events | Balanced accuracy | 51.0%49.6%–52.4% | 21 |
| Temporal ridge | Visual target versus nontarget events | Balanced accuracy | 53.8%51.9%–55.6% | 21 |
| LaBraM | Visual target versus nontarget events | Balanced accuracy | 49.4%47.7%–51.2% | 21 |
| CBraMod | Visual target versus nontarget events | Balanced accuracy | 55.0%53.3%–56.7% | 21 |
| EEGNet | Visual target versus nontarget events | Balanced accuracy | 53.3%51.7%–54.9% | 21 |
Credit OpenNeuro ds006593 contributors · version 1.0.0, doi:10.18112/openneuro.ds006593.v1.0.0; original author credits retained at the linked source.
BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data belong to the people credited.