pyprep is a python implementation of the Preprocessing Pipeline (PREP) for EEG data, working with MNE-Python for EEG data processing and analysis. Also contains a function to detect outlier epochs inspired by the FASTER algorithm.


pyprep requires Python version 3.6 or higher to run properly. It is furthermore recommended to run pyprep in a dedicated virtual environment (using e.g., conda).

For installing the stable version of pyprep, simply call pip install pyprep. This should install dependencies automatically. You can also install the dependencies yourself by running pip install -r requirements.txt from the project root.

For installation of the development version use:

git clone
cd pyprep
pip install -r requirements.txt
pip install -r requirements-dev.txt
pip install -e .


Contributions are welcome! You should have read the references below. After that, feel free to submit pull requests. Be sure to always include tests for all new code that you introduce (whenever possible).


  1. Bigdely-Shamlo, N., Mullen, T., Kothe, C., Su, K.-M., & Robbins, K. A. (2015). The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Frontiers in Neuroinformatics, 9, 16. doi: 10.3389/fninf.2015.00016
  2. Nolan, H., Whelan, R., & Reilly, R. B. (2010). FASTER: fully automated statistical thresholding for EEG artifact rejection. Journal of neuroscience methods, 192(1), 152-162. doi: 10.1016/j.jneumeth.2010.07.015