Quian Quiroga R, Garcia H
Sloan-Swartz Center for Theoretical Neurobiology, California Institute of Technology, Pasadena 91125, USA.
Clin Neurophysiol. 2003 Feb;114(2):376-90. doi: 10.1016/s1388-2457(02)00365-6.
The application of a recently proposed denoising implementation for obtaining event-related potentials (ERPs) at the single-trial level is shown. We study its performance in simulated data as well as in visual and auditory ERPs. For the simulated data, the method gives a significantly better reconstruction of the single-trial event-related responses in comparison with the original data and also in comparison with a reconstruction based on conventional Wiener filtering. Moreover, with wavelet denoising we obtain a significantly better estimation of the amplitudes and latencies of the simulated ERPs. For the real data, the method clearly improves the visualization of both visual and auditory single-trial ERPs. This allows the calculation of better averages as well as the study of systematic or unsystematic variations between trials. Since the method is fast and parameter free, it could complement the conventional analysis of ERPs.
展示了一种最近提出的去噪方法在单试次水平获取事件相关电位(ERP)中的应用。我们研究了该方法在模拟数据以及视觉和听觉ERP中的性能。对于模拟数据,与原始数据相比,以及与基于传统维纳滤波的重构相比,该方法能显著更好地重构单试次事件相关反应。此外,通过小波去噪,我们能显著更好地估计模拟ERP的幅度和潜伏期。对于真实数据,该方法明显改善了视觉和听觉单试次ERP的可视化。这使得能够计算出更好的平均值,以及研究试次间的系统或非系统变化。由于该方法快速且无需参数,它可以补充ERP的传统分析。