moabb.datasets.BNCI2025_001#

class moabb.datasets.BNCI2025_001(subjects=None, sessions=None)[source]#

BNCI 2025-001 Motor Kinematics Reaching dataset.

Dataset summary

#Subj

20

#Chan

64

#Classes

16

#Trials / class

varies

Trials length

4 s

Freq

500 Hz

#Sessions

1

#Runs

1

Total_trials

varies

Participants

  • Population: Healthy

  • Age: 26.1 years

  • Handedness: {‘right’: 17, ‘left’: 3}

Equipment

  • Amplifier: BrainAmp

  • Electrodes: EEG

  • Montage: af7 af3 afz af4 af8 f7 f5 f3 f1 fz f2 f4 f6 f8 ft7 fc5 fc3 fc1 fcz fc2 fc4 fc6 ft8 t7 c5 c3 c1 cz c2 c4 c6 t8 tp7 cp5 cp3 cp1 cpz cp2 cp4 cp6 tp8 p7 p5 p3 p1 pz p2 p4 p6 p8 ppo1h ppo2h po7 po3 poz po4 po8 o1 oz o2

  • Reference: common average

Preprocessing

  • Data state: preprocessed with eye artifact correction

  • Bandpass filter: 0.3-80 Hz

  • Steps: low-pass filter at 100 Hz, notch filter at 50 Hz, downsampling to 200 Hz, bad channel rejection and interpolation, bandpass filter 0.3-80 Hz, eye artifact correction via SGEYESUB, ICA with FastICA algorithm, IC artifact removal, low-pass filter at 3 Hz, downsampling to 10 Hz, bad trial rejection, common average reference

  • Re-reference: common average

  • Notes: Frontal channels (AF7, AF3, AFz, AF4, AF8) and EOG removed prior to CAR to reduce residual eye artifacts. Final analysis used 55 channels. Eye blocks recorded separately for SGEYESUB model training. Bad trials rejected based on amplitude >200 µV or standard deviation >5SD. Movement-related bad trials rejected for incorrect direction, no movement, duration <0.2s or >4s, or movement initiated <0.5s after cue stop.

Data Access

Experimental Protocol

  • Paradigm: imagery

  • Task type: discrete reaching

  • Tasks: discrete reaching

  • Feedback: visual (cue color: green for correct, red for incorrect direction)

  • Stimulus: visual cue

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Dataset from Srisrisawang & Muller-Putz (2024) [1].

Dataset Description

This dataset investigates how the brain simultaneously encodes multiple kinematic parameters (speed, distance, and direction) during discrete reaching movements. Participants performed a four-direction center-out reaching task with varying speeds (quick/slow) and distances (near/far).

The dataset provides insight into movement planning and execution processes as measured through EEG, enabling research on brain-computer interfaces for motor control and neurorehabilitation applications.

Participants

  • 20 healthy subjects (12 male, 8 female)

  • Age: 26.1 +/- 4.1 years

  • Handedness: 17 right-handed, 3 left-handed (all used right hand)

  • Location: Institute of Neural Engineering, Graz University of Technology, Austria

Recording Details

  • Equipment: BrainAmp (Brain Products GmbH)

  • Channels: 60 EEG + 4 EOG = 64 total channels

  • Sampling rate: 500 Hz

  • Reference: Common average reference (CAR) across 55 channels

  • EOG placement: Outer canthi, above/below left eye

  • Electrode positions: Measured with ultrasonic device (ELPOS, Zebris)

Experimental Procedure

  • 4-direction center-out reaching task

  • 2 speed levels: slow, quick

  • 2 distance levels: near, far

  • 16 conditions total (4 directions x 2 speeds x 2 distances)

  • ~60 trials per condition (~960 total per subject)

  • Trial structure:

    • 1 s preparation period

    • Cue movement (0.4-2.4 s depending on condition)

    • >= 1 s waiting period

    • Movement execution

    • 1 s feedback display

    • 2 s intertrial interval

Event Codes

Events encode the combination of direction, speed, and distance: - up_slow_near (1), up_slow_far (2), up_fast_near (3), up_fast_far (4) - down_slow_near (5), down_slow_far (6), down_fast_near (7), down_fast_far (8) - left_slow_near (9), left_slow_far (10), left_fast_near (11), left_fast_far (12) - right_slow_near (13), right_slow_far (14), right_fast_near (15), right_fast_far (16)

References

[1]

Srisrisawang, N., & Muller-Putz, G. R. (2024). Simultaneous encoding of speed, distance, and direction in discrete reaching: an EEG study. Journal of Neural Engineering, 21(6). https://doi.org/10.1088/1741-2552/ada0ea

Notes

Added in version 1.3.0.

This dataset is notable for its multi-parameter kinematic design, enabling study of how multiple movement parameters are represented simultaneously in EEG activity. The paradigm uses movement execution rather than motor imagery, making it complementary to MI datasets.

The data is compatible with the MOABB motor imagery paradigm for processing purposes, though the underlying task is movement execution.

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