moabb.datasets.MartinezCagigal2023Checker#
- class moabb.datasets.MartinezCagigal2023Checker(conditions=('c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8'))[source]#
Checkerboard m-sequence-based c-VEP dataset from Martínez-Cagigal et al. (2025) and Fernández-Rodríguez et al. (2023).
Dataset summary
#Subj
16
#Chan
16
#Trials / class
2-30
Trials length
4.2 s
Freq
256 Hz
#Sessions
8
#Trial classes
16
#Epochs classes
2
#Epochs / class
11904/12288
Codes
m-sequence
Presentation rate
120 Hz
Dataset Description
This dataset, accessible at [1], was originally recorded for study [2], which evaluated 8 different stimuli in a c-VEP circular shifting paradigm using binary m-sequences. The conditions were tested in a 9-command speller. The stimulus was composed of a black-background checkerboard (BB-CB) pattern, i.e. event 1 was encoded with a checkerboard pattern and event 0 with a white flash. The stimuli were encoded using circularly shifting versions of a 63-bit binary m-sequence. The different conditions evaluated different spatial frequency variations of the BB-CB pattern (i.e., the number of squares inside the checkerboard pattern).
The evaluated conditions were:
c1: C001 (0 c/º, 1x1 squares).
c2: C002 (0.15 c/º, 2x2 squares).
c3: C004 (0.3 c/º, 4x4 squares).
c4: C008 (0.6 c/º, 8x8 squares).
c5: C016 (1.2 c/º, 16x16 squares).
c6: C032 (2.4 c/º, 32x32 squares).
c7: C064 (4.79 c/º, 64x64 squares).
c8: C128 (9.58 c/º, 128x128 squares).
The dataset includes recordings from 16 healthy subjects performing a copy-spelling task under each condition. The evaluation was conducted in a single session, during which each participant completed:
A calibration phase consisting of 30 trials using the original m-sequence (divided into two recordings of 15 trials each), and
An online copy-spelling task of 18 trials (in one run).
Each trial consisted of 8 cycles (i.e., repetitions of the same code). Additionally, participants completed questionnaires to assess satisfaction and perceived eyestrain for each m-sequence condition. Questionnaire results are available in [1].
The encoding was displayed at a 120 Hz refresh rate. EEG signals were recorded using a g.USBamp amplifier (g.Tec, Guger Technologies, Austria) with 16 active electrodes and a sampling rate of 256 Hz. Electrodes were placed at: Oz, F3, Fz, F4, I1, I2, C3, Cz, C4, CPz, P3, Pz, P4, PO7, POz, PO8, grounded at AFz and referenced to the earlobe.
The experimental paradigm was executed using the MEDUSA© software [3].
- Parameters:
conditions (tuple of str, optional) – Which conditions to load. Default is all conditions: (“c1”, “c2”, “c3”, “c4”, “c5”, “c6”, “c7”, “c8”). Each condition corresponds to a different spatial frequency of the checkerboard pattern.
References
[1] (1,2)Martínez Cagigal, V. (2025). Dataset: Influence of spatial frequency in visual stimuli for cVEP-based BCIs: evaluation of performance and user experience. https://doi.org/10.71569/7c67-v596
[2]Fernández-Rodríguez, Á., Martínez-Cagigal, V., Santamaría-Vázquez, E., Ron-Angevin, R., & Hornero, R. (2023). Influence of spatial frequency in visual stimuli for cVEP-based BCIs: evaluation of performance and user experience. Frontiers in Human Neuroscience, 17, 1288438. https://doi.org/10.3389/fnhum.2023.1288438
[3]Santamaría-Vázquez, E., Martínez-Cagigal, V., Marcos-Martínez, D., Rodríguez-González, V., Pérez-Velasco, S., Moreno-Calderón, S., & Hornero, R. (2023). MEDUSA©: A novel Python-based software ecosystem to accelerate brain–computer interface and cognitive neuroscience research. Computer Methods and Programs in Biomedicine, 230, 107357. https://doi.org/10.1016/j.cmpb.2023.107357
Notes
Although the dataset was recorded in a single session, each condition is stored as a separate session to match the MOABB structure. Within each session, three runs are available (two for training, one for testing).
Added in version 1.2.0.