The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, China; Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China.
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Brain Res Bull. 2024 Oct 15;217:111064. doi: 10.1016/j.brainresbull.2024.111064. Epub 2024 Sep 2.
The diversity of electrode placement systems brought the problem of channel location harmonization in large-scale electroencephalography (EEG) applications to the forefront. Therefore, our goal was to resolve this problem by introducing and assessing the reference electrode standardization technique (REST) to transform EEGs into a common electrode distribution with computational zero reference at infinity offline.
Simulation and eye-closed resting-state EEG datasets were used to investigate the performance of REST for EEG signals and power configurations.
REST produced small errors (the root mean square error (RMSE): 0.2936-0.4583; absolute errors: 0.2343-0.3657) and high correlations (>0.9) between the estimated signals and true ones. The comparison of configuration similarities in power among various electrode distributions revealed that REST induced infinity reference could maintain a perfect performance similar (>0.9) to that of true one.
These results demonstrated that REST transformation could be adopted to resolve the channel location harmonization problem in large-scale EEG applications.
电极放置系统的多样性使得在大规模脑电图（EEG）应用中需要解决通道位置协调的问题。因此，我们的目标是通过引入参考电极标准化技术（REST）来解决这个问题，该技术可以离线将 EEG 转换为具有计算零参考的通用电极分布。
使用模拟和闭眼静息状态 EEG 数据集来研究 REST 对 EEG 信号和功率配置的性能。
REST 产生的误差较小（均方根误差（RMSE）：0.2936-0.4583；绝对误差：0.2343-0.3657），并且估计信号与真实信号之间具有高度相关性（>0.9）。在各种电极分布之间的功率配置相似性比较中，REST 诱导的无穷远参考可以保持与真实参考相似的完美性能（>0.9）。
这些结果表明，REST 转换可以用于解决大规模 EEG 应用中的通道位置协调问题。
