Concepts

Core concepts for MEGPrep

This section introduces the underlying principles of MEGPrep.

MEGPrep uses a combination of advanced preprocessing techniques based on established neuroimaging research. The pipeline is designed to handle various preprocessing steps, including:

Filtering and cleaning the raw MEG data. Performing artifact rejection methods, which helps identify and remove noise from the data. Implementing automatic ICA components detection to separate brain signals from artifacts effectively. Conducting automatic co-registration to align brain images from different modalities (MRI and MEG). These concepts form the foundation of the MEGPrep pipeline, enabling reproducible, efficient, and accurate preprocessing of MEG data for further analysis.