moabb.paradigms.CVEP#

class moabb.paradigms.CVEP(fmin=1.0, fmax=45.0, **kwargs)[source]#

Single bandpass c-VEP paradigm for epoch-level decoding.

c-VEP paradigm with only one bandpass filter (default 1 to 45 Hz) Metric is ‘roc-auc’ if 2 classes and ‘accuracy’ if more. This paradigm is meant to be used for epoch-level decoding of c-VEP datasets; this means that the goal of the classifiers with this paradigm is to predict, for every stimulation one by one, the amplitude of the target code. The code value is between 0 (i.e., stimulation off) and 1 (i.e., maximal stimulation).

Parameters:

  • fmin (float (default 1.0)) – cutoff frequency (Hz) for the highpass filter

  • fmax (float (default 45.0)) – cutoff frequency (Hz) for the lowpass filter

  • events (List of str | None (default None)) – Event to use for epoching. Note, we stick to a convention where the intensity level is encoded as float. For example, a binary sequence would have events 1.0 (i.e., on) and 0.0 (i.e., off). If None, default to all events defined in the dataset.

  • n_classes (int or None (default None)) – Number of classes each dataset must have. All dataset classes if None

  • tmin (float (default 0.0)) – Start time (in second) of the epoch, relative to the dataset specific task interval e.g. tmin = 1 would mean the epoch will start 1 second after the beginning of the task as defined by the dataset.

  • tmax (float | None, (default None)) – End time (in second) of the epoch, relative to the beginning of the dataset specific task interval. tmax = 5 would mean the epoch will end 5 second after the beginning of the task as defined in the dataset. If None, use the dataset value.

  • baseline (None | tuple of length 2 (default None)) – The time interval to consider as “baseline” when applying baseline correction. If None, do not apply baseline correction. If a tuple (a, b), the interval is between a and b (in seconds), including the endpoints. Correction is applied by computing the mean of the baseline period and subtracting it from the data (see mne.Epochs)

  • channels (list of str | None (default None)) – List of channel to select. If None, use all EEG channels available in the dataset.

  • resample (float | None (default None)) – If not None, resample the eeg data with the sampling rate provided.