脑磁图
磁强计
磁场
电磁屏蔽
计算机科学
声学
物理
光谱密度
脑电图
电信
心理学
量子力学
精神科
作者
Stephanie Mellor,Tim M. Tierney,George O'Neill,Nicholas A Alexander,Robert A. Seymour,Niall Holmes,José David López,Ryan M. Hill,Elena Boto,Molly Rea,Gillian Roberts,James Leggett,Richard Bowtell,Matthew J. Brookes,Eleanor A. Maguire,Matthew Walker,Gareth R. Barnes
标识
DOI:10.1101/2021.05.25.444975
摘要
Abstract Background Optically pumped magnetometers (OPMs) have made moving, wearable magnetoencephalography (MEG) possible. The OPMs typically used for MEG require a low background magnetic field to operate, which is achieved using both passive and active magnetic shielding. However, the background magnetic field is never truly zero Tesla, and so the field at each of the OPMs changes as the participant moves. This leads to position and orientation dependent changes in the measurements, which manifest as low frequency artefacts in MEG data. Objective We modelled the spatial variation in the magnetic field and used the model to predict the movement artefact found in a dataset. Methods We demonstrate a method for modelling this field with a triaxial magnetometer, then showed that we can use the same technique to predict the movement artefact in a real OPM-based MEG (OP-MEG) dataset. Results Using an 86-channel OP-MEG system, we found that this modelling method maximally reduced the power spectral density of the data by 26.2 ± 0.6 dB at 0 Hz, when applied over 5 s non-overlapping windows. Conclusion The magnetic field inside our state-of-the art magnetically shielded room can be well described by low-order spherical harmonic functions. We achieved a large reduction in movement noise when we applied this model to OP-MEG data. Significance Real-time implementation of this method could reduce passive shielding requirements for OP-MEG recording and allow the measurement of low-frequency brain activity during natural participant movement.
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