Signal-space separation (SSS) and Maxwell filtering — MNE 0.22.0 documentation

This tutorial covers reducing environmental noise and compensating for head movement with SSS and Maxwell filtering.

Note Go to the end to download the full example code. This tutorial covers reducing environmental noise and compensating for head movement with SSS and Maxwell filtering. As usual, we’ll start by importing the modules we need, loading some example data, and cropping it to save on memory: # Authors: The MNE-Python contributors. # License: BSD-3-Clause # Copyright the MNE-Python contributors. General Filename(s) sample_audvis_raw.fif MNE object type Raw Measurement date 2002-12-03 at 19:01:10 UTC Participant Unknown Experimenter MEG Acquisition Duration 00:01:01 (HH:MM:SS)…

related reading

• An underleveraged modality in neuroscience | Abhi Upadhyayaxu.sh
• We have AE at homebrainhack.vercel.app
• EEG Artifacts: Types, Detection, and Removal Techniques Bitbrainbitbrain.com
• [2606.29698] Clear Mind: Meditation and the Brain's Signal-to-Noise Ratioarxiv.org
• A robust adaptive denoising framework for real-time artifact removal in scalp EEG measurements - IOPscienceiopscience.iop.org
• Signal Processingarxiv.org
• Kalman filter - Wikipediaen.wikipedia.org
• Filter (signal processing)en.wikipedia.org
• How Many EEG Channels Should I Use In My Research? [Less Than You Think!] | Mentalabmentalab.com
• Techniques of EMG signal analysis: detection, processing, classification and applications - PMCncbi.nlm.nih.gov
• Repairing artifacts with ICA — MNE 1.13.2 documentationmne.tools
• Simulations improve MEG spatial resolution – Physics Worldphysicsworld.com