A generalized method to estimate waveforms common across trials from EEGs

We propose a generalized method to estimate waveforms common across trials from electroencephalographic (EEG) data. From single/multi-channel EEGs, the proposed method estimates the number of waveforms common across trials, their delays in individual trials, and all of the waveforms. After verifying the performance of this method by a number of simulation tests with artificial EEGs, we apply it to EEGs during a Go/NoGo task. This method can be used in general situations where the number and the delays of EEG waveforms common across trials are unknown.