Tutorials

The notebooks below are self-contained and use simulated signals, so they can be run without an EEG recording or private stimulus files. Figures generated by the notebook cells are rendered directly in the HTML documentation.

A complete TRF walkthrough

A gentle introduction to temporal response functions (TRFs)

Loading Word-level features

from pyeeg.io import AlignedSpeech
speech = AlignedSpeech(onset=0., srate=125, path_audio='path/to/audio/file')

Loading Word vectors

from pyeeg.io import WordLevelFeatures
wlf = wfeats = WordLevelFeatures(path_praat_env=dur_path, path_wordonsets=surp_path, path_surprisal=surp_path)

Loading processed EEG (processed by EEGLAB)

To load EEG data from .set files, the code would be:

from pyeeg.io import eeglab2mne
eeg = eeglab2mne(filepath)

Older, data-dependent examples

These examples are retained for now. They require local EEG/audio files and may need adaptation to current APIs.