Caponi Camilla, Castaldi Elisa, Grasso Paolo Antonino, Arrighi Roberto
Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Florence, Italy.
Department of Physics and Astronomy, University of Florence, Florence, Italy.
Proc Biol Sci. 2025 Jan;292(2039):20241841. doi: 10.1098/rspb.2024.1841. Epub 2025 Jan 29.
Perceptual adaptation has been widely used to infer the existence of numerosity detectors, enabling animals to quickly estimate the number of objects in a scene. Here, we investigated, in humans, whether numerosity adaptation is influenced by stimulus feature changes as previous research suggested that adaptation is reduced when the colour of adapting and test stimuli did not match. We tested whether such adaptation reduction is due to unspecific novelty effects or changes of stimuli identity. Numerosity adaptation was measured for stimuli matched or unmatched for low-level (colour, luminance, shape and motion) or high-level (letters' identity and face emotions) features. Robust numerosity adaptation occurred in all conditions, but it was reduced when adapting and test stimuli differed for colour, luminance and shape. However, no reduction was observed between moving and still stimuli, a readable change that did not affect the item's identity. Similarly, changes in letters' spatial rotations or face features did not affect adaptation magnitude. Overall, changes in stimulus identity defined by low-level features, rather than novelty in general, determined the strength of the adaptation effects, provided these changes were readily noticeable. These findings suggest that numerosity mechanisms operate on categorized items in addition to the total quantity of the set.
知觉适应已被广泛用于推断数字探测器的存在,使动物能够快速估计场景中物体的数量。在这里,我们研究了在人类中,数字适应是否会受到刺激特征变化的影响,因为先前的研究表明,当适应刺激和测试刺激的颜色不匹配时,适应会减弱。我们测试了这种适应减弱是由于非特异性的新奇效应还是刺激身份的变化。针对低水平(颜色、亮度、形状和运动)或高水平(字母身份和面部表情)特征匹配或不匹配的刺激测量数字适应。在所有条件下都出现了强大的数字适应,但当适应刺激和测试刺激在颜色、亮度和形状上不同时,适应会减弱。然而,在动态和静态刺激之间未观察到减弱,这种明显的变化并不影响物体的身份。同样,字母的空间旋转或面部特征的变化也不影响适应程度。总体而言,由低水平特征定义得刺激身份变化,而非一般的新奇性,决定了适应效应的强度,前提是这些变化很容易被注意到。这些发现表明,数字机制除了作用于集合的总量外,还作用于分类后的项目。