Gallego-Rudolf Jonathan, Corsi-Cabrera María, Concha Luis, Ricardo-Garcell Josefina, Pasaye-Alcaraz Erick
Unidad de Resonancia Magnética, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico.
Laboratorio de Sueño, Facultad de Psicología, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Front Neurosci. 2022 Dec 23;16:951321. doi: 10.3389/fnins.2022.951321. eCollection 2022.
Electroencephalographic (EEG) data quality is severely compromised when recorded inside the magnetic resonance (MR) environment. Here we characterized the impact of the ballistocardiographic (BCG) artifact on resting-state EEG spectral properties and compared the effectiveness of seven common BCG correction methods to preserve EEG spectral features. We also assessed if these methods retained posterior alpha power reactivity to an eyes closure-opening (EC-EO) task and compared the results from EEG-informed fMRI analysis using different BCG correction approaches.
Electroencephalographic data from 20 healthy young adults were recorded outside the MR environment and during simultaneous fMRI acquisition. The gradient artifact was effectively removed from EEG-fMRI acquisitions using Average Artifact Subtraction (AAS). The BCG artifact was corrected with seven methods: AAS, Optimal Basis Set (OBS), Independent Component Analysis (ICA), OBS followed by ICA, AAS followed by ICA, PROJIC-AAS and PROJIC-OBS. EEG signal preservation was assessed by comparing the spectral power of traditional frequency bands from the corrected rs-EEG-fMRI data with the data recorded outside the scanner. We then assessed the preservation of posterior alpha functional reactivity by computing the ratio between the EC and EO conditions during the EC-EO task. EEG-informed fMRI analysis of the EC-EO task was performed using alpha power-derived BOLD signal predictors obtained from the EEG signals corrected with different methods.
The BCG artifact caused significant distortions (increased absolute power, altered relative power) across all frequency bands. Artifact residuals/signal losses were present after applying all correction methods. The EEG reactivity to the EC-EO task was better preserved with ICA-based correction approaches, particularly when using ICA feature extraction to isolate alpha power fluctuations, which allowed to accurately predict hemodynamic signal fluctuations during the EEG-informed fMRI analysis.
Current software solutions for the BCG artifact problem offer limited efficiency to preserve the EEG spectral power properties using this particular EEG setup. The state-of-the-art approaches tested here can be further refined and should be combined with hardware implementations to better preserve EEG signal properties during simultaneous EEG-fMRI. Existing and novel BCG artifact correction methods should be validated by evaluating signal preservation of both ERPs and spontaneous EEG spectral power.
在磁共振（MR）环境中进行脑电图（EEG）数据记录时，数据质量会受到严重影响。在此，我们描述了心冲击图（BCG）伪迹对静息态EEG频谱特性的影响，并比较了七种常见的BCG校正方法在保留EEG频谱特征方面的有效性。我们还评估了这些方法是否保留了闭眼 - 睁眼（EC - EO）任务中后部α波功率反应性，并比较了使用不同BCG校正方法进行EEG辅助功能磁共振成像（fMRI）分析的结果。
记录了20名健康年轻成年人在MR环境外以及同时进行fMRI采集时的脑电图数据。使用平均伪迹减法（AAS）有效地从EEG - fMRI采集中去除梯度伪迹。用七种方法校正BCG伪迹：AAS、最优基集（OBS）、独立成分分析（ICA）、OBS后接ICA、AAS后接ICA、PROJIC - AAS和PROJIC - OBS。通过比较校正后的静息态EEG - fMRI数据中传统频段的频谱功率与在扫描仪外记录的数据，评估EEG信号的保留情况。然后，通过计算EC - EO任务期间EC和EO条件之间的比率，评估后部α波功能反应性的保留情况。使用从用不同方法校正的EEG信号中获得的α波功率衍生的BOLD信号预测因子，对EC - EO任务进行EEG辅助fMRI分析。
BCG伪迹在所有频段均引起了显著失真（绝对功率增加，相对功率改变）。应用所有校正方法后均存在伪迹残留/信号损失。基于ICA的校正方法能更好地保留EEG对EC - EO任务的反应性，特别是在使用ICA特征提取来分离α波功率波动时，这使得在EEG辅助fMRI分析期间能够准确预测血流动力学信号波动。
针对BCG伪迹问题的当前软件解决方案在使用这种特定的EEG设置保留EEG频谱功率特性方面效率有限。此处测试的最先进方法可以进一步改进，并且应该与硬件实现相结合，以便在同步EEG - fMRI期间更好地保留EEG信号特性。现有的和新颖的BCG伪迹校正方法应通过评估事件相关电位（ERP）和自发EEG频谱功率的信号保留情况来进行验证。
