Wu Dan
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China.
The Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, China.
Front Neurosci. 2018 Mar 13;12:148. doi: 10.3389/fnins.2018.00148. eCollection 2018.
If the scalp potential signals, the electroencephalogram (EEG), are due to neural "singers" in the brain, how could we listen to them with less distortion? One crucial point is that the data recording on the scalp should be faithful and accurate, thus the choice of reference electrode is a vital factor determining the faithfulness of the data. In this study, music on the scalp derived from data in the brain using three different reference electrodes were compared, including approximate zero reference-reference electrode standardization technique (REST), average reference (AR), and linked mastoids reference (LM). The classic music pieces in waveform format were used as simulated sources inside a head model, and they were forward calculated to scalp as standard potential recordings, i.e., waveform format music from the brain with true zero reference. Then these scalp music was re-referenced into REST, AR, and LM based data, and compared with the original forward data (true zero reference). For real data, the EEG recorded in an orthodontic pain control experiment were utilized for music generation with the three references, and the scale free index (SFI) of these music pieces were compared. The results showed that in the simulation for only one source, different references do not change the music/waveform; for two sources or more, REST provide the most faithful music/waveform to the original ones inside the brain, and the distortions caused by AR and LM were spatial locations of both source and scalp electrode dependent. The brainwave music from the real EEG data showed that REST and AR make the differences of SFI between two states more recognized and found the frontal is the main region that producing the music. In conclusion, REST can reconstruct the true signals approximately, and it can be used to help to listen to the true voice of the neural singers in the brain.
如果头皮电位信号，即脑电图（EEG），是由大脑中的神经“歌手”产生的，那么我们如何能以较小的失真来聆听它们呢？关键的一点是头皮上的数据记录应该真实准确，因此参考电极的选择是决定数据真实性的一个重要因素。在本研究中，比较了使用三种不同参考电极从大脑数据中导出的头皮音乐，包括近似零参考——参考电极标准化技术（REST）、平均参考（AR）和联合乳突参考（LM）。以波形格式的经典音乐片段作为头部模型内的模拟源，并将它们正向计算到头皮作为标准电位记录，即来自大脑的具有真正零参考的波形格式音乐。然后将这些头皮音乐重新参考为基于REST、AR和LM的数据，并与原始正向数据（真正零参考）进行比较。对于真实数据，利用正畸疼痛控制实验中记录的脑电图，通过这三种参考来生成音乐，并比较这些音乐片段的无标度指数（SFI）。结果表明，在仅一个源的模拟中，不同参考不会改变音乐/波形；对于两个或更多源，REST提供的音乐/波形与大脑内部的原始音乐/波形最接近，而AR和LM引起的失真取决于源和头皮电极的空间位置。来自真实脑电图数据的脑波音乐表明，REST和AR使两种状态之间的SFI差异更易识别，并发现额叶是产生音乐的主要区域。总之，REST可以近似地重建真实信号，并且可用于帮助聆听大脑中神经“歌手”的真实声音。
