An Easy-to-Follow Handbook for EEG Data Analysis based on Python

  1. Zitong Lu
  2. Wanru Li
  3. Lu Nie
  4. Kuangshi Zhao
Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Now published in Brain-X doi: 10.1002/brx2.64 This easy-to-follow handbook offers a straightforward guide to EEG data analysis using Python, aimed at all EEG researchers in cognitive neuroscience and related fields. It covers the journey from single-subject data preprocessing to advanced processing techniques across subjects, with a focus on practical application using Python libraries such as NumPy, MNE-Python, SciPy, NeuroRA, etc. Designed for easy comprehension, our handbook can serve as an essential tool for anyone looking to delve into the field of EEG data analysis with Python.

Article activity feed

  1. Version published to 10.31234/osf.io/dcmke on OSF Preprints