A long‐standing question in the field of vision research is whether scalp‐recorded EEG activity contains sufficient information to identify stimulus chromaticity. Recent multivariate work suggests that it is possible to decode which chromaticity an observer is viewing from the multielectrode pattern of EEG activity. There is debate, however, about whether the claimed effects of stimulus chromaticity on visual evoked potentials (VEPs) are instead caused by unequal stimulus luminances, which are achromatic differences. Here, we tested whether stimulus chromaticity could be decoded when potential confounds with luminance were minimized by (1) equating chromatic stimuli in luminance using heterochromatic flicker photometry for each observer and (2) independently varying the chromaticity and luminance of target stimuli, enabling us to test whether the pattern for a given chromaticity generalized across wide variations in luminance. We also tested whether luminance variations can be decoded from the topography of voltage across the scalp. In Experiment 1, we presented two chromaticities (appearing red and green) at three luminance levels during separate trials. In Experiment 2, we presented four chromaticities (appearing red, orange, yellow, and green) at two luminance levels. Using a pattern classifier and the multielectrode pattern of EEG activity, we were able to accurately decode the chromaticity and luminance level of each stimulus. Furthermore, we were able to decode stimulus chromaticity when we trained the classifier on chromaticities presented at one luminance level and tested at a different luminance level. Thus, EEG topography contains robust information regarding stimulus chromaticity, despite large variations in stimulus luminance.

中文翻译：

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从 EEG 活动模式解码色度和亮度

视觉研究领域的一个长期问题是头皮记录的 EEG 活动是否包含足够的信息来识别刺激色度。最近的多变量工作表明，可以从 EEG 活动的多电极模式中解码观察者正在观察的色度。然而，关于所声称的刺激色度对视觉诱发电位 (VEP) 的影响是否是由不等的刺激亮度引起的，这是一个争论色差。在这里，我们测试了当与亮度的潜在混淆最小化时是否可以解码刺激色度，方法是 (1) 使用异色闪烁光度法为每个观察者将亮度中的色度刺激等同起来，以及 (2) 独立地改变目标刺激的色度和亮度，使我们能够测试给定色度的模式是否在亮度的广泛变化中泛化。我们还测试了亮度变化是否可以从头皮电压的地形中解码。在实验 1 中，我们在不同的试验中呈现了三个亮度级别的两种色度（呈现红色和绿色）。在实验 2 中，我们展示了两种亮度级别的四种色度（呈现红色、橙色、黄色和绿色）。使用模式分类器和 EEG 活动的多电极模式，我们能够准确地解码每个刺激的色度和亮度水平。此外，当我们在一个亮度级别呈现的色度上训练分类器并在不同的亮度级别进行测试时，我们能够解码刺激色度。因此，尽管刺激亮度变化很大，但脑电图地形包含有关刺激色度的可靠信息。