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High-pass filters and baseline correction in M/EEG analysis. Commentary on: 'How inappropriate high-pass filters can produce artefacts and incorrect conclusions in ERP studies of language and cognition'

机译:M / EEG分析中的高通滤波器和基线校正。评论:“不合适的高通滤波器如何在ERP语言和认知研究中产生假象和不正确的结论”

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Tanner et al. (2015. Psychophysiology, 52(8), 1009. doi: 10.1111/psyp.12437) convincingly demonstrate how a late deflection like the N400 or the P600 is reflected into both earlier and later latencies by the application of high-pass filters with cutoff frequencies higher than 0.1 Hz. It nicely underlines the importance of test-wise application of filters with different parameters to electrophysiological data to identify such unwanted filter effects. In general, we agree with their approach and conclusions, particularly with the notions that the application of a high-pass filter is reasonable if it improves the signal-to-noise ratio (SNR) of the signal of interest, and that low frequency signals may carry important information. However, we disagree in two aspects: First, the test data of Tanner et al. are not optimally suited to demonstrate the benefits of high-pass filtering as they are only minimally contaminated by low frequency noise, and second, the standard baseline correction for particular applications in M/EEG data analysis should be replaced with high-pass filtering as recommended by Widmann et al. (C) 2015 Elsevier B.V. All rights reserved.
机译:Tanner等。 (2015. Psychophysiology,52(8),1009. doi:10.1111 / psyp.12437)令人信服地展示了如何通过应用带有截止值的高通滤波器将像N400或P600这样的延迟偏转反映到早期和延迟的延迟中。频率高于0.1 Hz。它很好地强调了对具有不同参数的过滤器进行电生理数据的试验性应用以识别此类有害过滤器效果的重要性。总的来说,我们同意他们的方法和结论,尤其是这样的观念,即如果高通滤波器可以改善目标信号和低频信号的信噪比(SNR),则其应用是合理的。可能会携带重要信息。但是,我们在两个方面存在分歧:第一,Tanner等人的测试数据。并不是最适合展示高通滤波的好处,因为它们仅受到低频噪声的最小污染;其次,对于M / EEG数据分析中特定应用的标准基线校正,应按建议用高通滤波代替由Widmann等人撰写。 (C)2015 Elsevier B.V.保留所有权利。

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