Department of Psychology, University of Milano-Bicocca.
Department of Brain and Behavioral Sciences, University of Pavia.
J Exp Psychol Hum Percept Perform. 2021 Mar;47(3):423-441. doi: 10.1037/xhp0000844. Epub 2021 Jan 25.
The past few years have witnessed a fervent theoretical debate about the exact visual mechanisms supporting nonsymbolic number processing. The idea that quantity information is extracted through a primitive visual segmentation algorithm has been challenged by recent models, which rather tap on low-level features confounded with numerosity (i.e., density, convex hull, or total area). Here we used an original manipulation based on visual illusions to disentangle whether visual numerosity processing operates over discrete units or rather over continuous variables. In particular, we generated a set of stimuli composed by open inducers (e.g., like a pac-man shape) that simulate physical connections with Kanizsa-like illusory contours (ICs). Test sets contained pairs of collinear open inducers items that prompted 0 IC, 2 IC, or 4 IC lines connecting 2 objects. Critically, low-level visual features were fully controlled across connectedness levels. We found a systematic underestimation as we increased the IC connections when participants had to select the larger between 2 sets of objects (Experiment 1) but not in the case of aligned closed inducers preventing illusory lines (Experiments 2A and 2B). We also found a systematic numerosity underestimation when both IC connections and continuous features (e.g., convex hull) were independently manipulated in test stimuli (Experiment 3). Finally, these results were shown to be task independent because the same effects of IC connections were replicated in an estimation task (Experiment 4). Taken together, our findings indicate that numerosity perception relies on basic visual-segmentation mechanisms, pointing out the need of new theoretical frameworks integrating both continuous and discrete perceptual number signals. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
过去几年见证了一场关于支持非符号数量加工的确切视觉机制的热烈理论辩论。最近的模型提出,数量信息是通过一种与数量混淆的原始视觉分割算法提取的,而不是通过与数量混淆的低水平特征(即密度、凸壳或总面积)提取的。在这里,我们使用了一种基于视觉错觉的原始操作来区分视觉数量加工是在离散单元上还是在连续变量上进行。具体来说,我们生成了一组由开放式诱导物(例如像 pac-man 形状)组成的刺激,这些刺激模拟与 Kanizsa 错觉轮廓(IC)的物理连接。测试集包含一对共线开放式诱导物项目,这些项目提示连接两个对象的 0IC、2IC 或 4IC 线。关键是,在连接水平上,低水平视觉特征得到了完全控制。当参与者必须在两组对象之间选择较大的对象时,我们发现随着 IC 连接的增加,系统地低估了(实验 1),但在防止错觉线的对齐封闭诱导物的情况下(实验 2A 和 2B)则不是这样。当在测试刺激中独立地操纵 IC 连接和连续特征(例如凸壳)时,我们也发现了系统的数量低估(实验 3)。最后,由于在估计任务中复制了 IC 连接的相同效果(实验 4),这些结果被证明是任务独立的。总之,我们的研究结果表明,数量感知依赖于基本的视觉分割机制,这表明需要新的理论框架来整合连续和离散的感知数量信号。(PsycInfo 数据库记录(c)2021 APA,保留所有权利)。