moabb.datasets.MartinezCagigal2023Checker#
- class moabb.datasets.MartinezCagigal2023Checker(conditions=('c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8'), subjects=None, sessions=None, **kwargs)[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
Found an issue with this dataset?
If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!
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.