moabb.datasets.BNCI2015_008

class moabb.datasets.BNCI2015_008

BNCI 2015-008 Center Speller P300 dataset.

Dataset summary

#Subj	13
#Chan	63
#Trials / class	varies NT / T
Trials length	1 s
Freq	250 Hz
#Sessions	2

Participants

• Population: healthy

• Age: 30.5 (range: 16-45) years

• Handedness: 12 right-handed, 1 left-handed

• BCI experience: 2 experienced (1 author, 1 from precursor study), 11 naive

Equipment

• Amplifier: Brain Products

• Electrodes: active electrode

• Montage: 10-10

• Reference: Car

Preprocessing

• Data state: continuous EEG with event markers

• Steps: BBCI Matlab toolbox preprocessing

• Re-reference: car

Data Access

• DOI: 10.1088/1741-2560/8/6/066003

• Data URL: bbci/bbci_public

• Repository: GitHub

Experimental Protocol

• Paradigm: p300

• Feedback: none

• Stimulus: rsvp

Dataset summary

Name	#Subj	#Chan	#Trials/class	Trials length	Sampling Rate	#Sessions
BNCI2015_008	13	63	~1180 T / ~5900 NT	1.0s	250Hz	2

Dataset from [1], also known as Treder2011.

Dataset Description

This dataset contains P300 evoked potentials recorded during a gaze-independent two-stage visual speller paradigm called the “Center Speller”. Unlike traditional matrix spellers that require gaze fixation on target cells, the Center Speller allows users to focus on the screen center while covertly attending to peripheral stimuli.

The paradigm uses a two-stage selection process where users first select a group of characters, then select individual characters within that group. This design enables efficient spelling without requiring eye movements, making it suitable for users with severe motor disabilities affecting eye control.

Participants

• 13 healthy subjects

• BCI experience: Previous experience with P300-based BCIs

• Location: Machine Learning Laboratory, TU Berlin, Germany

Recording Details

• Channels: 63 EEG electrodes (standard 10-10 system)

• Sampling rate: 250 Hz

• Reference: Nose reference

Data Organization

• Subject codes: iac, iba, ibb, ibc, ibd, ibe, ibf, ibg, ibh, ibi, ibj, ica, saf

• Two runs per subject (calibration + online)

• Data URL: http://doc.ml.tu-berlin.de/bbci/BNCIHorizon2020-CenterSpeller/

Event Codes

• Target (1): Target stimulus presented (attended)

• NonTarget (2): Non-target stimulus presented (not attended)

References

[1]

Treder, M. S., Schmidt, N. M., & Blankertz, B. (2011). Gaze-independent brain-computer interfaces based on covert attention and feature attention. Journal of Neural Engineering, 8(6), 066003. https://doi.org/10.1088/1741-2560/8/6/066003

Notes

Added in version 1.2.0.