Objective

Simultaneous recording of the electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) allows a combination of eletrophysiological and haemodynamic information to be used to form a more complete picture of cerebral dynamics. However, EEG recorded within the MRI scanner is contaminated by both imaging artifacts and physiological artifacts. The majority of the techniques used to pre-process such EEG focus on removal of the imaging and balistocardiogram artifacts, with some success, but don’t remove all other physiological artifacts.

Methods

We propose a new offline EEG artifact removal method based upon a combination of independent component analysis and fMRI-based head movement estimation to aid the removal of physiological artifacts from EEG recorded during EEG-fMRI recordings. Our method makes novel use of head movement trajectories estimated from the fMRI recording in order to assist with identifying physiological artifacts in the EEG and is designed to be used after removal of the fMRI imaging artifact from the EEG.

Results

We evaluate our method on EEG recorded during a joint EEG-fMRI session from healthy adult participants. Our method significantly reduces the influence of all types of physiological artifacts on the EEG. We also compare our method with a state-of-the-art physiological artifact removal method and demonstrate superior performance removing physiological artifacts.

Conclusions

Our proposed method is able to remove significantly more physiological artifact components from the EEG, recorded during a joint EEG-fMRI session, than other state-of-the-art methods.

Significance

Our proposed method represents a marked improvement over current processing pipelines for removing physiological noise from EEG recorded during a joint EEG-fMRI session.

中文翻译：

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从同步 EEG 和 fMRI 记录中去除生理伪影

客观的

脑电图 (EEG) 和功能磁共振成像 (fMRI) 的同时记录允许结合使用电生理学和血液动力学信息来形成更完整的脑动力学图像。然而，MRI 扫描仪内记录的 EEG 受到成像伪影和生理伪影的污染。用于预处理此类 EEG 的大多数技术侧重于去除成像和心搏动图伪影，取得了一些成功，但并未去除所有其他生理伪影。

方法

我们提出了一种新的离线 EEG 伪影去除方法，该方法基于独立分量分析和基于 fMRI 的头部运动估计的组合，以帮助从 EEG-fMRI 记录期间记录的 EEG 中去除生理伪影。我们的方法新颖地使用了从 fMRI 记录中估计的头部运动轨迹，以帮助识别 EEG 中的生理伪影，并且旨在从 EEG 中去除 fMRI 成像伪影后使用。

结果

我们评估了我们在健康成年参与者的联合 EEG-fMRI 会议期间记录的 EEG 的方法。我们的方法显着降低了所有类型的生理伪影对 EEG 的影响。我们还将我们的方法与最先进的生理伪影去除方法进行了比较，并展示了去除生理伪影的卓越性能。

结论

与其他最先进的方法相比，我们提出的方法能够从联合 EEG-fMRI 会话期间记录的 EEG 中去除更多的生理伪影成分。

意义

我们提出的方法代表了对当前处理管道的显着改进，用于从联合 EEG-fMRI 会话期间记录的 EEG 中去除生理噪声。