Precision magnetic field modelling and control for wearable magnetoencephalography

Area of Science:

• Biophysics
• Neuroscience
• Sensor Technology

Background:

• Optically-pumped magnetometers (OPMs) are sensitive, compact magnetic field sensors.
• OPMs present a promising alternative to superconducting quantum interference devices (SQUIDs) for magnetoencephalography (MEG).
• Achieving high-quality MEG data with OPMs necessitates precise control of background magnetic fields, even within optimized passive shielding.

Purpose of the Study:

• To develop and validate a magnetic field mapping technique to mitigate motion-induced artifacts in OPM-MEG.
• To demonstrate the effectiveness of active magnetic field compensation in reducing low-frequency interference caused by head movement.
• To enhance the data quality for OPM-MEG experiments, particularly those focusing on low-frequency neural oscillations.

Main Methods:

• A magnetic field mapping technique was implemented using a wearable sensor array to sample background fields within a passive shield.
• Participant head movements were used to derive coefficients for uniform and gradient magnetic field components.
• Derived coefficients were used to control a bi-planar electromagnetic coil system for active field compensation.

Main Results:

• The magnetic field mapping technique accurately reconstructed known magnetic field magnitudes.
• Active field compensation reduced the uniform magnetic field from 1.3±0.3 nT to 0.29±0.07 nT.
• A five-fold reduction in motion artifacts at 0–2 Hz was achieved during a visual steady-state evoked response experiment.

Conclusions:

• Head movement introduces significant low-frequency artifacts in OPM-MEG data, even in highly shielded environments.
• The developed magnetic field mapping and active compensation technique effectively reduces these motion artifacts.
• This technique holds potential for improving OPM-MEG data quality, especially for low-frequency analyses and studies involving subject movement.