moabb.datasets.Thielen2015#
- class moabb.datasets.Thielen2015[source]#
c-VEP dataset from Thielen et al. (2015)
Dataset [1] from the study on reconvolution for c-VEP [2].
Dataset summary
Name
#Subj
#Sessions
Sampling rate
#Chan
Trials length
#Trial classes
#Trials / class
#Epoch classes
#Epochs / class
Codes
Presentation rate
Thielen2015
12
1
2048Hz
64
4.2s
36
3
2
27216 NT / 27216 T
Gold codes
120Hz
Dataset description
EEG recordings were obtained with a sampling rate of 2048 Hz, using a setup comprising 64 Ag/AgCl electrodes, and amplified by a Biosemi ActiveTwo EEG amplifier. Electrode placement followed the international 10-10 system.
During the experimental sessions, participants actively operated a 6 x 6 visual speller brain-computer interface (BCI) with real-time feedback, encompassing 36 distinct classes. Each cell within the symbol grid underwent luminance modulation at full contrast, achieved through the application of pseudo-random noise-codes derived from a set of modulated Gold codes. These binary codes have a balanced distribution of ones and zeros while adhering to a limited run-length pattern, with a maximum run-length of 2 bits. Codes were presented at a rate of 120 Hz. Given that one cycle of these modulated Gold codes comprises 126 bits, the duration of a complete cycle spans 1.05 seconds.
Throughout the experiment, participants underwent four distinct blocks: an initial practice block consisting of two runs, followed by a training block of one run. Subsequently, they engaged in a copy-spelling block comprising six runs, and finally, a free-spelling block consisting of one run. Between the training and copy-spelling block, a classifier was calibrated using data from the training block. This calibrated classifier was then applied during both the copy-spelling and free-spelling runs. Additionally, during calibration, the stimulation codes were tailored and optimized specifically for each individual participant.
Among the six copy-spelling runs, there were three fixed-length runs. Trials in these runs started with a cueing phase, where the target symbol was highlighted in a green hue for 1 second. Participants maintained their gaze fixated on the target symbol as all symbols flashed in sync with their corresponding pseudo-random noise-codes for a duration of 4.2 seconds (equivalent to 4 code cycles). Immediately following this stimulation, the output of the classifier was shown by coloring the cell blue for 1 second. Each run consisted of 36 trials, presented in a randomized order.
Here, our focus is solely on the three copy-spelling runs characterized by fixed-length trials lasting 4.2 seconds (equivalent to four code cycles). The other three runs utilized a dynamic stopping procedure, resulting in trials of varying durations, rendering them unsuitable for benchmarking purposes. Similarly, the practice and free-spelling runs included dynamic stopping and are ignored in this dataset. The training dataset, comprising 36 trials, used a different noise-code set, and is therefore also ignored in this dataset. In total, this dataset should contain 108 trials of 4.2 seconds each, with 3 repetitions for each of the 36 codes.
References
[1]Thielen, J. (Jordy), Jason Farquhar, Desain, P.W.M. (Peter) (2023): Broad-Band Visually Evoked Potentials: Re(con)volution in Brain-Computer Interfacing. Version 2. Radboud University. (dataset). DOI: https://doi.org/10.34973/1ecz-1232
[2]Thielen, J., Van Den Broek, P., Farquhar, J., & Desain, P. (2015). Broad-Band visually evoked potentials: re(con)volution in brain-computer interfacing. PLOS ONE, 10(7), e0133797. DOI: https://doi.org/10.1371/journal.pone.0133797
Notes
New in version 1.0.0.