MNE-Python Analysis Guide

Purpose

This skill encodes expert methodological knowledge for analyzing neurophysiological data (EEG, MEG, sEEG, ECoG, NIRS, eye-tracking) using MNE-Python (Gramfort et al., 2013; Gramfort et al., 2014). It covers the complete analysis pipeline with recommended parameters, code examples, and common pitfall warnings.

When to Use This Skill

Activate when the user:

• Asks about EEG/MEG/sEEG/ECoG/NIRS data analysis in Python
• Mentions MNE, MNE-Python, epochs, evoked, Raw, source estimate, ICA, ERP, ERF
• Wants to load neurophysiological data files (.fif, .edf, .bdf, .set, .vhdr, .mff, .cnt, .snirf)
• Needs preprocessing, time-frequency, source localization, decoding, or statistical testing guidance
• Wants to create MNE objects from numpy arrays or simulate data

Research Planning Protocol