moabb.datasets.BNCI2015_006#

class moabb.datasets.BNCI2015_006(subjects=None, sessions=None)[source]#

BNCI 2015-006 Music BCI dataset.

Dataset summary

#Subj

11

#Chan

64

#Trials / class

~875 NT / ~856 T

Trials length

1 s

Freq

200 Hz

#Sessions

1

Participants

  • Population: Healthy

  • Age: 28 (range: 21-50) years

  • Handedness: all but one right-handed

  • BCI experience: naive

Equipment

  • Amplifier: Brain Products

  • Electrodes: active electrode

  • Montage: 10-10

  • Reference: left mastoid

Preprocessing

  • Data state: epoched

  • Steps: downsampling, lowpass filtering, epoching, baseline correction, artifact rejection

  • Notes: Artifact rejection applied only to training set, preserved in test set. Passbands: 42 Hz, stopbands: 49 Hz for Chebyshev filter.

Data Access

  • DOI: 10.1088/1741-2560/11/2/026009

  • Data URL: bbci/bbci_public

  • Repository: GitHub

Experimental Protocol

  • Paradigm: p300

  • Task type: auditory oddball

  • Tasks: selective auditory attention, deviant counting

  • Feedback: none

  • Stimulus: musical oddball

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Dataset from [1].

Dataset Description

This dataset investigates the suitability of musical stimuli for use in a P300 paradigm. 11 subjects listened to polyphonic music clips featuring three instruments playing together. A multi-streamed oddball paradigm was used.

References

[1]

Treder, M. S., Purwins, H., Miklody, D., Sturm, I., & Blankertz, B. (2014). Decoding auditory attention to instruments in polyphonic music using single-trial EEG classification. Journal of Neural Engineering, 11(2), 026009. https://doi.org/10.1088/1741-2560/11/2/026009

Notes

Added in version 1.2.0.

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

Return the data paths of the dataset.