Numerosity perception is largely governed by two mechanisms. The first so-called subitizing system allows one to enumerate a small number of items (up to three or four) without error. The second system allows only an approximate estimation of larger numerosities. Here, we investigate the neural bases of the two systems using sequentially presented numerosity. Sequential numerosity (i.e., the number of events presented over time) starts as a subitizable set but may eventually transition into a larger numerosity in the approximate estimation range, thus offering a unique opportunity to investigate the neural signature of that transition point, or subitizing boundary. If sequential numerosity is encoded by two distinct perceptual mechanisms (i.e., for subitizing and approximate estimation), neural representations of the sequentially presented items crossing the subitizing boundary should be sharply distinguishable. In contrast, if sequential numerosity is encoded by a single perceptual mechanism for all numerosities and subitizing is achieved through an external postperceptual mechanism, no such differences in the neural representations should indicate the subitizing boundary. Using the high temporal resolution of the EEG technique incorporating a multivariate decoding analysis, we found results consistent with the latter hypothesis: No sharp representational distinctions were observed between items across the subitizing boundary, which is in contrast with the behavioral pattern of subitizing. The results support a single perceptual mechanism encoding sequential numerosities, whereas subitizing may be supported by a postperceptual attentional mechanism operating at a later processing stage.

中文翻译：

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脑电图信号的解码显示没有证据表明序列数性中存在神经特征。

数量感知主要由两种机制控制。第一个所谓的 subitizing 系统允许一个人列举少量的项目（最多三个或四个）而不会出错。第二个系统仅允许对较大数量进行近似估计。在这里，我们使用顺序呈现的数量来研究两个系统的神经基础。顺序数量（即随着时间的推移呈现的事件数量）作为一个可子化的集合开始，但最终可能会转变为近似估计范围内的更大数量，从而提供一个独特的机会来研究该过渡点的神经特征，或子化边界. 如果序列数由两种不同的感知机制编码（即用于子化和近似估计），跨越子化边界的顺序呈现项目的神经表征应该是清晰可辨的。相比之下，如果顺序数字由所有数字的单一感知机制编码，并且通过外部后感知机制实现子化，则神经表征中的此类差异不应指示子化边界。使用结合多变量解码分析的 EEG 技术的高时间分辨率，我们发现结果与后一个假设一致：跨 subitizing 边界的项目之间没有观察到明显的表征差异，这与 subitizing 的行为模式相反。结果支持编码顺序数字的单一感知机制，