Categorization is an essential cognitive and perceptual process, which happens spontaneously. However, earlier research often neglected the spontaneous nature of this process by mainly adopting explicit tasks in behavioral or neuroimaging paradigms. Here, we use frequency-tagging (FT) during electroencephalography (EEG) in 22 healthy human participants (both male and female) as a direct approach to pinpoint spontaneous visual categorical processing. Starting from schematic natural visual stimuli, we created morph sequences comprising 11 equal steps. Mirroring a behavioral categorical perception discrimination paradigm, we administered a FT-EEG oddball paradigm, assessing neural sensitivity for equally sized differences within and between stimulus categories. Likewise, mirroring a behavioral category classification paradigm, we administered a sweep FT-EEG oddball paradigm, sweeping from one end of the morph sequence to the other, thereby allowing us to objectively pinpoint the neural category boundary. We found that FT-EEG can implicitly measure categorical processing and discrimination. More specifically, we could derive an objective neural index of the required level to differentiate between the two categories, and this neural index showed the typical marker of categorical perception (i.e., stronger discrimination across as compared with within categories). The neural findings of the implicit paradigms were also validated using an explicit behavioral task. These results provide evidence that FT-EEG can be used as an objective tool to measure discrimination and categorization and that the human brain inherently and spontaneously (without any conscious or decisional processes) uses higher-level meaningful categorization information to interpret ambiguous (morph) shapes.

分类是一个重要的认知和感知过程，它是自发发生的。然而，早期的研究往往忽视了这一过程的自发性，主要采用行为或神经影像范式中的明确任务。在这里，我们在 22 名健康人类参与者（男性和女性）的脑电图 (EEG) 过程中使用频率标记 (FT) 作为精确定位自发视觉分类处理的直接方法。从示意性自然视觉刺激开始，我们创建了包含 11 个相等步骤的变形序列。反映行为分类感知歧视范式，我们采用了 FT-EEG 奇怪范式，评估刺激类别内和刺激类别之间同等大小差异的神经敏感性。同样，为了反映行为类别分类范式，我们采用了扫描 FT-EEG 奇怪范式，从变形序列的一端扫描到另一端，从而使我们能够客观地查明神经类别边界。我们发现 FT-EEG 可以隐式测量分类处理和歧视。更具体地说，我们可以得出区分两个类别所需水平的客观神经指数，并且该神经指数显示了类别感知的典型标志（即，与类别内相比，跨类别的辨别力更强）。隐式范式的神经发现也使用显式行为任务进行了验证。这些结果提供了证据，表明 FT-EEG 可以用作测量辨别和分类的客观工具，并且人脑固有地和自发地（没有任何意识或决策过程）使用更高级别的有意义的分类信息来解释模糊（变形）形状。