moabb.datasets.BI2015a#

class moabb.datasets.BI2015a(subjects=None, sessions=None)[source]#

P300 dataset BI2015a from a “Brain Invaders” experiment.

PapersWithCode leaderboard: https://paperswithcode.com/dataset/braininvaders2015a-moabb

Dataset summary

#Subj

43

#Chan

32

#Trials / class

4131 NT / 825 T

Trials length

1 s

Freq

512 Hz

#Sessions

3

Participants

  • Population: healthy

  • Age: 23.7 years

  • BCI experience: mostly students and young researchers

Equipment

  • Amplifier: g.USBamp (g.tec, Schiedlberg, Austria)

  • Electrodes: wet electrodes

  • Montage: 10-10

  • Reference: right earlobe

Preprocessing

  • Data state: raw EEG with synchronized USB tagging (reduced jitter using USB digital-to-analog converter)

  • Notes: no digital filter applied during acquisition; tags synchronized with EEG signals to reduce jitter; consistent tagging latency across Brain Invaders databases

Data Access

Experimental Protocol

  • Paradigm: p300

  • Task type: target detection

  • Feedback: visual (game interface with real-time adaptive Riemannian RMDM classifier)

  • Stimulus: oddball paradigm on grid of 36 symbols (1 Target, 35 Non-Target) flashed pseudo-randomly

Found an issue with this dataset?

If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!

Report an Issue on GitHub

This dataset contains electroencephalographic (EEG) recordings of 43 subjects playing to a visual P300 Brain-Computer Interface (BCI) videogame named Brain Invaders. The interface uses the oddball paradigm on a grid of 36 symbols (1 Target, 35 Non-Target) that are flashed pseudo-randomly to elicit the P300 response. EEG data were recorded using 32 active wet electrodes with three conditions: flash duration 50ms, 80ms or 110ms. The experiment took place at GIPSA-lab, Grenoble, France, in 2015. A full description of the experiment is available at [1]. The ID of this dataset is BI2015a.

Investigators:

Eng. Louis Korczowski, B. Sc. Martine Cederhout

Technical Support:

Eng. Anton Andreev, Eng. Grégoire Cattan, Eng. Pedro. L. C. Rodrigues, M. Sc. Violette Gautheret

Scientific Supervisor:

Ph.D. Marco Congedo

Notes

Note

BI2015a was previously named bi2015a. bi2015a will be removed in version 1.1.

Added in version 0.4.6.

References

[1]

Korczowski, L., Cederhout, M., Andreev, A., Cattan, G., Rodrigues, P. L. C., Gautheret, V., & Congedo, M. (2019). Brain Invaders calibration-less P300-based BCI with modulation of flash duration Dataset (BI2015a) https://hal.archives-ouvertes.fr/hal-02172347

data_path(subject, path=None, force_update=False, update_path=None, verbose=None)[source]#

Get path to local copy of a subject data.

Parameters:

  • subject (int) – Number of subject to use

  • path (None | str) – Location of where to look for the data storing location. If None, the environment variable or config parameter MNE_DATASETS_(dataset)_PATH is used. If it doesn’t exist, the “~/mne_data” directory is used. If the dataset is not found under the given path, the data will be automatically downloaded to the specified folder.

  • force_update (bool) – Force update of the dataset even if a local copy exists.

  • update_path (bool | None Deprecated) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted.

  • verbose (bool, str, int, or None) – If not None, override default verbose level (see mne.verbose()).

Returns:

path – Local path to the given data file. This path is contained inside a list of length one, for compatibility.

Return type:

list of str