“Bad channels” are common phenomena during scalp electroencephalography (EEG) recording that arise due to various technique-related reasons, and reconstructing signals from bad channels is an inevitable choice in EEG processing. However, current interpolation methods are all based on purely mathematical interpolation theory, ignoring the neurophysiological basis of the EEG signals, and their performance needs to be further improved, especially when there are many scattered or adjacent bad channels. Therefore, a new interpolation method, named the reference electrode standardization interpolation technique (RESIT), was developed for interpolating scalp EEG channels. Resting-state and event-related EEG datasets were used to investigate the performance of the RESIT. The main results showed that (1) assuming 10% bad channels, RESIT can reconstruct the bad channels well; (2) as the percentage of bad channels increased (from 2% to 85%), the absolute and relative errors between the true and RESIT-reconstructed signals generally increased, and the correlations between the true and RESIT signals decreased; (3) for a range of bad channel percentages (2% ~ 85%), the RESIT had lower absolute error (approximately 2.39% ~ 33.5% reduction), lower relative errors (approximately 1.3% ~ 35.7% reduction) and higher correlations (approximately 2% ~ 690% increase) than traditional interpolation methods, including neighbor interpolation (NI) and spherical spline interpolation (SSI). In addition, the RESIT was integrated into the EEG preprocessing pipeline on the WeBrain cloud platform (https://webrain.uestc.edu.cn/). These results suggest that the RESIT is a promising interpolation method for both separate and simultaneous EEG preprocessing that benefits further EEG analysis, including event-related potential (ERP) analysis, EEG network analysis, and strict group-level statistics.

“坏通道”是头皮脑电图（EEG）记录期间的常见现象，由于各种与技术相关的原因而出现，从坏通道重建信号是EEG处理中的必然选择。然而，当前的插值方法都是基于纯数学插值理论的，忽略了EEG信号的神经生理学基础，其性能有待进一步提高，特别是当存在许多分散或相邻的不良通道时。因此，开发了一种新的插值方法，称为参考电极标准化插值技术（RESIT），用于插值头皮EEG通道。静息状态和与事件有关的EEG数据集用于调查RESIT的性能。主要结果表明：（1）假设有10％的不良频道，RESIT可以很好地重建不良通道；（2）随着不良信道百分比的增加（从2％增加到85％），真实信号和RESIT重构信号之间的绝对和相对误差通常会增加，真实信号和RESIT信号之间的相关性会降低；（3）对于一系列不良的频道百分比（2％〜85％），RESIT的绝对误差较低（约2.39％〜33.5％降低），相对误差较低（约1.3％〜35.7％降低）和相关性较高（比传统的插值方法（包括邻居插值（NI）和球面样条插值（SSI））大约增加了2％〜690％。此外，RESIT已集成到WeBrain云平台（https://webrain.uestc.edu.cn/）上的EEG预处理管道中。