MEG Center, Departments of Pediatrics and Neurology, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH 45229, USA.
Neuroscience Graduate Program, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.
J Integr Neurosci. 2022 Aug 16;21(5):145. doi: 10.31083/j.jin2105145.
Magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs) opens up new opportunities for brain research. However, OPM recordings are associated with artifacts. We describe a new artifact reduction method, frequency specific signal space classification (FSSSC), to improve the signal-to-noise ratio of OPM recordings.
FSSSC was based on time-frequency analysis and signal space classification (SSC). SSC was accomplished by computing the orthogonality of the brain signal and artifact. A dipole phantom was used to determine if the method could remove artifacts and improve accuracy of source localization. Auditory evoked magnetic fields (AEFs) from human subjects were used to assess the usefulness of artifact reduction in the study of brain function because bilateral AEFs have proven a good benchmark for testing new methods. OPM data from empty room recordings were used to estimate magnetic artifacts. The effectiveness of FSSSC was assessed in waveforms, spectrograms, and covariance domains.
MEG recordings from phantom tests show that FSSSC can remove artifacts, normalize waveforms, and significantly improve source localization accuracy. MEG signals from human subjects show that FSSC can reveal auditory evoked magnetic responses overshadowed and distorted by artifacts. The present study demonstrates FSSSC is effective at removing artifacts in OPM recordings. This can facilitate the analyses of waveforms, spectrograms, and covariance. The accuracy of source localization of OPM recordings can be significantly improved by FSSSC.
Brain responses distorted by artifacts can be restored. The results of the present study strongly support that artifact reduction is very important in order for OPMs to become a viable alternative to conventional MEG.
基于光泵磁强计（OPM）的脑磁图（MEG）为脑研究开辟了新的机会。然而，OPM 记录与伪影有关。我们描述了一种新的减少伪影的方法，即频率特定信号空间分类（FSSSC），以提高 OPM 记录的信噪比。
FSSSC 基于时频分析和信号空间分类（SSC）。SSC 通过计算脑信号和伪影的正交性来完成。使用偶极子模拟体来确定该方法是否可以去除伪影并提高源定位的准确性。使用来自人类受试者的听觉诱发磁场（AEF）来评估减少伪影在脑功能研究中的有用性，因为双侧 AEF 已被证明是测试新方法的良好基准。使用空房间记录的 OPM 数据来估计磁场伪影。在波形、频谱和协方差域中评估 FSSSC 的有效性。
来自模拟测试的 MEG 记录表明，FSSSC 可以去除伪影、归一化波形，并显著提高源定位的准确性。来自人类受试者的 MEG 信号表明，FSSC 可以揭示被伪影掩盖和扭曲的听觉诱发磁场反应。本研究表明 FSSSC 可有效地去除 OPM 记录中的伪影。这可以促进波形、频谱和协方差的分析。FSSSC 可以显著提高 OPM 记录的源定位准确性。
可以恢复被伪影扭曲的脑反应。本研究的结果强烈支持，为了使 OPM 成为传统 MEG 的可行替代方案，减少伪影非常重要。
