Python Noise-Tagging Brain-Computer Interfacing (PyNTBCI)

The PyntBCI library contains custom software to setup a code-modulated evoked response BCI. For instance, it contains routines to create stimulus sequences (i.e., noise codes) and to analyse and decode code-modulated evoked potentials (e.g., c-VEP).

PyNTBCI can be easily installed from PyPI:

pip install pyntbci

Using PyntBCI is easy, adopting the scikit-learn API:

import pyntbci
rcca = pyntbci.classifiers.rCCA(stimulus=stimulus, fs=fs)
rcca.fit(X_trn, y_trn)
yh = rcca.predict(X_tst)