This repository contains the implementation of an end-to-end signal processing and RNN-based deep learning pipeline for single-trial decoding of the presence and absence of error-related potentials from recorded scalp EEG.
RNN_ErrP_main.ipynb: Python script of a high-performing EEG ErrP Decoding RNN Pipeline (preprocessing, features engineering, model building, hyperparameter tuning and evaluation)
clean_requirements.txt: Dependencies for this project