A statistically robust EEG re-referencing procedure to mitigate reference effect.

A statistically robust EEG re-referencing procedure to mitigate reference effect.
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DOI:
10.1016/j.jneumeth.2014.05.008
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发表时间:
2014-09-30
影响因子:
3
通讯作者:
Chu, Catherine J.
Chu, Catherine J.
中科院分区:
医学4区
文献类型:
--
作者:
Lepage, Kyle Q.;Kramer, Mark A.;Chu, Catherine J.

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脑电图(EEG)仍然是临床神经病学中诊断异常脑活动和神经科学研究中人体神经生理学活体记录的主要工具。在EEG数据采集中,在头皮上相对于参考电极的位置处测量电压。当该参考电极响应电活动或伪影时,所有电极都会受到影响。EEG数据的成功分析通常涉及修改记录的迹线并寻求最小化参考电极活动对原始EEG记录的功能的影响的重新参考过程。我们提供了一种新的,统计上稳健的程序,适应一个强大的最大似然型估计的参考估计的问题,减少神经活动的影响,从重新引用操作,并保持良好的性能在各种各样的经验方案。所提出的和现有的重新引用程序的性能进行了验证,在模拟和EEG记录的例子。为了便于这种比较,信道到信道的相关性进行了研究理论和仿真。所提出的方法避免了使用被神经信号污染的数据,并且在物理参考、公共平均参考(CAR)和参考估计标准化技术(REST)不是最佳的记录场景中保持无偏。所提出的方法简单,快速,并避免了潜在的实质性偏差时,分析低密度EEG数据。
The electroencephalogram (EEG) remains the primary tool for diagnosis of abnormal brain activity in clinical neurology and for in vivo recordings of human neurophysiology in neuroscience research. In EEG data acquisition, voltage is measured at positions on the scalp with respect to a reference electrode. When this reference electrode responds to electrical activity or artifact all electrodes are affected. Successful analysis of EEG data often involves re-referencing procedures that modify the recorded traces and seek to minimize the impact of reference electrode activity upon functions of the original EEG recordings. We provide a novel, statistically robust procedure that adapts a robust maximum-likelihood type estimator to the problem of reference estimation, reduces the influence of neural activity from the re-referencing operation, and maintains good performance in a wide variety of empirical scenarios. The performance of the proposed and existing re-referencing procedures are validated in simulation and with examples of EEG recordings. To facilitate this comparison, channel-to-channel correlations are investigated theoretically and in simulation. The proposed procedure avoids using data contaminated by neural signal and remains unbiased in recording scenarios where physical references, the common average reference (CAR) and the reference estimation standardization technique (REST) are not optimal. The proposed procedure is simple, fast, and avoids the potential for substantial bias when analyzing low-density EEG data.
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