Welcome!#
Hello everyone, and welcome to this MEGqc tutorial. MEGqc is a Python-based pipeline for quality control of MEG data. It was developed as Evgeniia Gapontseva’s Master Thesis (2023) within the Applied Neurocognitive Psychology Lab (ANCP Lab).
Learning Objectives#
Learn more about MEGqc and its reports
Get to install MEGqc and analyze an MEG dataset
Get to produce an MEGqc HTML report
Requirements for this tutorial#
Some familiarity with MEG data
Access to a Linux terminal/shell
A working version of Python3
Basic understanding of BASH commands (such as ls and cd).
Some familiarity with GitHub
I’ve got a question!#
If you have any questions or encounter difficulties while working with MEGqc, please don’t hesitate a single second to get in touch with us. A great way to do this is to via e-mail @ aaron.reer@uol.de.
Acknowledgements#
This tutorial was made possible through the dedicated work of the Jupyter community, specifically, the Executable/Jupyter Book.