A new method to detect event-related potentials based on Pearson's correlation.

EURASIP journal on bioinformatics & systems biology Pub Date : 2016-06-07 eCollection Date: 2016-12-01 DOI:10.1186/s13637-016-0043-z
William Giroldini, Luciano Pederzoli, Marco Bilucaglia, Simone Melloni, Patrizio Tressoldi
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引用次数: 13

Abstract

Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience.  Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise.  The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N, where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP's waveform, these waveforms being time- and phase-locked.  In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson's correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase-in consonance with the stimuli-in EEG signal correlation over all channels.  This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs.  These hidden components seem to be caused by variations (between each successive stimulus) of the ERP's inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology.  The method we are proposing can be directly used in the form of a process written in the well-known Matlab programming language and can be easily and quickly written in any other software language.

Abstract Image

Abstract Image

Abstract Image

基于Pearson相关的事件相关电位检测新方法。
事件相关电位在脑机接口和神经科学中有着广泛的应用。正常的脑电图活动具有丰富的背景噪声,因此,为了检测erp,通常需要从多次试验中取平均值,以减少该噪声的影响。脑电图活动本身产生的噪声与ERP波形不相关,因此,通过计算平均值,噪声降低了一个与N的平方根成反比的因子,其中N是平均epoch的数量。这是目前用于检测ERP的最简单的策略,它基于计算所有ERP波形的平均值,这些波形是时间和锁相的。本文提出了一种新的计算ERP的方法GW6,该方法仅使用基于Pearson相关的数学方法来计算ERP。结果是一个与经典ERP具有相同时间分辨率的图,并且在所有通道上仅显示正峰,表示与刺激一致的脑电图信号相关性的增加。该方法还可以选择性地识别和突出一些ERP响应中不锁相的隐藏成分,这些成分通常隐藏在基于所有时代平均的标准和简单方法中。这些隐藏的成分似乎是由ERP固有相位潜伏期(抖动)的变化(在每个连续刺激之间)引起的,尽管相同的刺激在所有EEG通道中产生一个相当恒定的相位。因此,这种新方法可能非常有助于研究ERP反应的这些隐藏成分,并开发用于科学和医学目的的应用。此外,这种新方法比标准的平均计算更能抵抗脑电图伪影,在研究和神经学方面非常有用。我们提出的方法可以直接以众所周知的Matlab编程语言编写的过程的形式使用,并且可以轻松快速地用任何其他软件语言编写。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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