Carballo-Gonzalez J A, Valdes-Sosa P, Valdes-Sosa M
Neurosciences Branch, National Centre for Scientific Research, Havana, Cuba.
Int J Neurosci. 1989 Jun;46(3-4):109-22. doi: 10.3109/00207458908986247.
A statistical approach is presented which provides efficient procedures to detect both Event Related Potential (ERP) and its spectral structure. Situations where undesirable signal or "artifact" is present, are considered. In these cases, a "noise" sample can be used which complements the insufficient knowledge given for the sample where we expect to detect the ERP. In this approach, Hotelling's T2 statistic for one and two samples arises as a natural detector of ERPs. Under the assumption of stationarity these statistics are calculated by approximate expressions in the frequency domain. For Brainstem Auditory Evoked Potentials, ROC curves confirm that the T2 statistic has higher detection rates than various indices proposed in the literature. A frequency decomposition of the T2 statistic yields a succession of complex versions of Student's t statistic that characterize the spectral structure of the ERP. Different assumptions about the recordings of ERP are discussed and several generalizations are suggested.
本文提出了一种统计方法,该方法提供了检测事件相关电位(ERP)及其频谱结构的有效程序。文中考虑了存在不良信号或“伪迹”的情况。在这些情况下,可以使用“噪声”样本,以补充我们期望检测到ERP的样本中所提供的不足信息。在这种方法中,单样本和两样本的霍特林T2统计量成为ERP的自然检测器。在平稳性假设下,这些统计量通过频域中的近似表达式来计算。对于脑干听觉诱发电位,ROC曲线证实T2统计量比文献中提出的各种指标具有更高的检测率。T2统计量的频率分解产生了一系列表征ERP频谱结构的学生t统计量的复本。文中讨论了关于ERP记录的不同假设,并提出了几种推广方法。