Understanding the Influences of EEG Reference: A Large-Scale Brain Network Perspective.
Understanding the Influences of EEG Reference: A Large-Scale Brain Network Perspective.
复制标题
DOI：
10.3389/fnins.2017.00205
复制
发表时间：
2017
影响因子：
4.3
通讯作者：
Liao K
中科院分区：
文献类型：
--
作者：
Lei X;Liao K
参照物的影响是脑电和事件相关电位研究中的一个关键问题。然而，以前的研究较少集中在系统神经科学水平上的来源位置。我们的目标是从人脑功能的一个共同网络部分中检测与位置相关的EEG信号，为EEG参考的影响提供一个系统的视角。在我们的仿真中，我们采用了均匀分布在八个大规模脑网络中的顶点来生成头皮脑电。大脑网络包括视觉网络、躯体运动网络、背侧注意网络、腹侧注意网络、边缘网络、额顶网络、默认网络和大脑深层结构。根据铅场矩阵计算了每个网络的最灵敏电极和中性电极的分布。最敏感的电极具有网络特有的对称模式，而头皮表面的电极成为最中性的电极的机会大致相同。模拟数据参考参考电极标准化技术(REST)获得的FCz、Oz、平均乳突(MM)、平均(AVE)和无穷远参考值。有趣的是，相对误差遵循Rest<；Ave<；MM<；(FCz，Oz)模式，与电极数量和信噪比无关。我们的发现表明，对于所有大规模网络，REST可能是更好的参考，并且在几种情况下实际上表现为REST。由于在同一行为领域内的EEG和ERPs实验总是在特定的大脑网络中被激活，因此本文的比较可能为临床和基础研究中的参考选择提供有价值的建议。
The influence of reference is a critical issue for the electroencephalography (EEG) and event-related potentials (ERPs) studies. However, previous investigations concentrated less on the location of source at a systematic neuroscience level. Our goal was to examine the EEG signal associated with the locations from a common network parcellation of the human brain function, offering a system perspective of the influence of EEG reference. In our simulation, vertices uniformly distributed in eight large-scale brain networks were adopted to generate the scalp EEG. The brain networks contain the visual, somatomotor, dorsal attention, ventral attention, limbic, frontoparietal, default networks, and the deep brain structure. The distributions of the most sensitive and neutral electrodes were calculated for each network based on the lead-field matrix. While the most sensitive electrode had a network-specific symmetric pattern, the electrodes in scalp surface had approximately equal chance to be the most neutral electrode. Simulated data were referenced at the FCz, the Oz, the mean mastoids (MM), the average (AVE), and the infinity reference obtained by the reference electrode standardization technique (REST). Intriguingly, the relative error followed the pattern REST<AVE<MM<(FCz, Oz), regardless of the number of electrodes and signal-to-noise ratios. Our findings suggested that REST was a potentially preferable reference for all large-scale networks and AVE virtually performed as REST under several conditions. As EEG and ERPs experiments within the same behavioral domain always have activations in some specific brain networks, the comparisons revealed here may provide a valuable recommendation for reference selection in clinical and basic researches.