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# BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects)

BigP3BCI Study M — 9x8 adaptive/checkerboard (21 ALS subjects).

## Dataset Overview

- **Code**: Mainsah2025-M
- **Paradigm**: p300
- **DOI**: 10.13026/0byy-ry86
- **Subjects**: 21
- **Sessions per subject**: 1
- **Events**: Target=2, NonTarget=1
- **Trial interval**: [0, 1.0] s

## Acquisition

- **Sampling rate**: 256.0 Hz
- **Number of channels**: 16
- **Channel types**: eeg=16
- **Montage**: standard_1020
- **Hardware**: g.USBamp (g.tec)
- **Line frequency**: 60.0 Hz

## Participants

- **Number of subjects**: 21
- **Health status**: healthy

## Experimental Protocol

- **Paradigm**: p300
- **Number of classes**: 2
- **Class labels**: Target, NonTarget

## HED Event Annotations

Schema: HED 8.4.0 | Browse: https://www.hedtags.org/hed-schema-browser

```
  Target
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Target

  NonTarget
    ├─ Sensory-event
    ├─ Experimental-stimulus
    ├─ Visual-presentation
    └─ Non-target

```
## Paradigm-Specific Parameters

- **Detected paradigm**: p300

## Signal Processing

- **Feature extraction**: P300_ERP_detection

## Cross-Validation

- **Method**: calibration-then-test
- **Evaluation type**: within_subject

## BCI Application

- **Applications**: speller
- **Environment**: laboratory
- **Online feedback**: True

## Tags

- **Modality**: visual
- **Type**: perception

## Documentation

- **Description**: BigP3BCI: the largest public P300 BCI dataset, containing EEG recordings from ~267 subjects across 20 studies using 6x6 or 9x8 character grids with various stimulus paradigms.
- **DOI**: 10.13026/0byy-ry86
- **License**: CC-BY-4.0
- **Investigators**: Boyla Mainsah, Chance Fleeting, Thomas Balmat, Eric Sellers, Leslie Collins
- **Institution**: Duke University; East Tennessee State University
- **Country**: US
- **Repository**: PhysioNet
- **Data URL**: https://physionet.org/content/bigp3bci/1.0.0/
- **Publication year**: 2025

## References

Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Hochenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896

Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103. https://doi.org/10.1038/s41597-019-0104-8

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