moabb.datasets.Kojima2024A#

class moabb.datasets.Kojima2024A(subjects=None, sessions=None)[source]#

Class for Kojima2024A dataset management. P300 dataset.

Dataset summary

#Subj

11

#Chan

64

#Trials / class

~130 NT / ~65 T

Trials length

1 s

Freq

1000 Hz

#Sessions

1

Participants

  • Population: healthy

  • Age: 22.5 (range: 22-23) years

Equipment

  • Amplifier: Brain Amp DC (Brain Products GmbH, Germany) and MR plus (Brain Products GmbH, Germany)

  • Electrodes: eeg

  • Montage: standard_1020

  • Reference: right earlobe

Preprocessing

  • Data state: raw

  • Bandpass filter: 0.1-100 Hz

  • Notes: Hardware filters applied during acquisition: bandpass 0.1 Hz to 100 Hz

Data Access

Experimental Protocol

  • Paradigm: p300

  • Task type: auditory selective attention

  • Tasks: attend to Stream 1, attend to Stream 2, attend to Stream 3

  • Feedback: no feedback

  • Stimulus: auditory musical tones

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Dataset description

This dataset [1] originates from a study investigating a three-class auditory BCI based on auditory stream segregation (ASME-BCI) [2].

In the experiment, participants focused on one of three auditory streams, leveraging auditory stream segregation to selectively attend to stimuli in the target stream. Each stream contained a two-stimulus oddball sequence composed of one deviant stimulus and one standard stimulus.

The sequence below illustrates an example trial. For instance, when D2 is the target stimulus, the participant attended to Stream2 and selectively listened for D2. In this case, D2 is the target, and D1 and D3 are considered non-target stimuli.

Stream3  ----- S3 -------- S3 -------- S3 -------- D3 -------- S3 -----
Stream2  -- S2 -------- S2 -------- D2 -------- S2 -------- S2 --------
Stream1  S1 -------- D1 -------- S1 -------- S1 -------- S1 -----------

Each participant completed 1 session consisting of 6 runs. Each run lasted approximately 5 minutes. In each run, all deviant stimuli (D1–D4) were presented approximately 60 times.

Recording Details:

  • EEG signals were recorded using a BrainAmp system (Brain Products, Germany) at a sampling rate of 1000 Hz.

  • Data were collected in Tokyo, Japan, where the power line frequency is 50 Hz.

  • EEG was recorded from 64 scalp electrodes according to the international 10–20 system: Fp1, Fp2, AF7, AF3, AFz, AF4, AF8, F7, F5, F3, F1, Fz, F2, F4, F6, F8, FT9, FT7, FC5, FC3, FC1, FCz, FC2, FC4, FC6, FT8, FT10, T7, C5, C3, C1, Cz, C2, C4, C6, T8, TP9, TP7, CP5, CP3, CP1, CPz, CP2, CP4, CP6, TP8, TP10, P7, P5, P3, P1, Pz, P2, P4, P6, P8, PO7, PO3, POz, PO4, PO8, O1, Oz, O2

    EEG signals were referenced to the right mastoid and grounded to the left mastoid.

  • EOG was recorded using 2 electrodes (vEOG and hEOG), placed above/below and lateral to one eye.

References

[1]

Kojima, S. (2024). Replication Data for: An auditory brain-computer interface based on selective attention to multiple tone streams. Harvard Dataverse, V1. DOI: https://doi.org/10.7910/DVN/MQOVEY

[2]

Kojima, S. & Kanoh, S. (2024). An auditory brain-computer interface based on selective attention to multiple tone streams. PLoS ONE 19(5): e0303565. DOI: https://doi.org/10.1371/journal.pone.0303565

convert_subject_to_subject_id(subjects)[source]#

Convert subject number(s) to subject ID(s). (In this dataset, subject IDs are encoded using alphabet letters.)

Parameters:

subjects (int or list of int) – Subject number(s) to convert.

Returns:

subject_id – Converted subject ID(s).

Return type:

str or list of str

data_path(subject, path=None)[source]#

Return the data paths of a single subject.

Parameters:

  • subject (int) – The subject number to fetch data for.

  • path (None | str) – Location of where to look for the data storing location. If None, the environment variable or config parameter MNE_(dataset) 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.

Returns:

A list containing the Path object for the subject’s data file.

Return type:

list

download_by_subject(subject, path=None)[source]#

Download and extract the dataset.

Parameters:

  • subject (int) – The subject number to download the dataset for.

  • path (str | None) – The path to the directory where the dataset should be downloaded. If None, the default directory is used.

Returns:

path – The dataset path.

Return type:

str