Cicchini Guido Marco, D'Errico Giovanni, Burr David Charles
Institute of Neuroscience, CNR, Pisa, Italy.
Department of Neurosciences, Psychology, Drug Research and Child Health, University of Florence, Firenze, Italy.
J Vis. 2024 Dec 2;24(13):9. doi: 10.1167/jov.24.13.9.
Crowding is the inability to recognize an object in clutter, classically considered a fundamental low-level bottleneck to object recognition. Recently, however, it has been suggested that crowding, like predictive phenomena such as serial dependence, may result from optimizing strategies that exploit redundancies in natural scenes. This notion leads to several testable predictions, such as crowding being greater for nonsalient targets and, counterintuitively, that flanker interference should be associated with higher precision in judgements, leading to a lower overall error rate. Here we measured color discrimination for targets flanked by stimuli of variable color. The results verified both predictions, showing that although crowding can affect object recognition, it may be better understood not as a processing bottleneck, but rather as a consequence of mechanisms evolved to efficiently exploit the spatial redundancies of the natural world. Analyses of reaction times of judgments shows that the integration occurs at sensory rather than decisional levels.
拥挤现象是指在杂乱环境中无法识别物体,传统上被认为是物体识别的一个基本低级瓶颈。然而,最近有人提出,拥挤现象与诸如序列依赖性等预测现象一样,可能源于利用自然场景冗余的优化策略。这一观点产生了几个可检验的预测,比如对于不突出的目标,拥挤现象更严重,而且与直觉相反的是,侧翼干扰应该与更高的判断精度相关联,从而导致总体错误率更低。在这里,我们测量了被不同颜色刺激侧翼包围的目标的颜色辨别能力。结果证实了这两个预测,表明尽管拥挤现象会影响物体识别,但更好的理解可能不是将其视为一个处理瓶颈,而是作为为有效利用自然界空间冗余而进化出的机制的结果。对判断反应时间的分析表明,整合发生在感官而非决策层面。