Paul Jacob M, Reeve Robert A, Forte Jason D
Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria,
J Vis. 2017 Mar 1;17(3):16. doi: 10.1167/17.3.16.
We habitually move our eyes when we enumerate sets of objects. It remains unclear whether saccades are directed for numerosity processing as distinct from object-oriented visual processing (e.g., object saliency, scanning heuristics). Here we investigated the extent to which enumeration eye movements are contingent upon the location of objects in an array, and whether fixation patterns vary with enumeration demands. Twenty adults enumerated random dot arrays twice: first to report the set cardinality and second to judge the perceived number of subsets. We manipulated the spatial location of dots by presenting arrays at 0°, 90°, 180°, and 270° orientations. Participants required a similar time to enumerate the set or the perceived number of subsets in the same array. Fixation patterns were systematically shifted in the direction of array rotation, and distributed across similar locations when the same array was shown on multiple occasions. We modeled fixation patterns and dot saliency using a simple filtering model and show participants judged groups of dots in close proximity (2°-2.5° visual angle) as distinct subsets. Modeling results are consistent with the suggestion that enumeration involves visual grouping mechanisms based on object saliency, and specific enumeration demands affect spatial distribution of fixations. Our findings highlight the importance of set computation, rather than object processing per se, for models of numerosity processing.
当我们枚举一组物体时,我们会习惯性地移动眼睛。目前尚不清楚扫视是否是为了进行数量处理,而不同于面向对象的视觉处理(例如,物体显著性、扫描启发式)。在这里,我们研究了枚举眼动在多大程度上取决于阵列中物体的位置,以及注视模式是否随枚举需求而变化。20名成年人对随机点阵列进行了两次枚举:第一次报告集合基数,第二次判断感知到的子集数量。我们通过以0°、90°、180°和270°的方向呈现阵列来操纵点的空间位置。参与者在同一阵列中枚举集合或感知到的子集数量所需的时间相似。注视模式随着阵列旋转方向系统地移动,并且当多次显示同一阵列时,注视模式分布在相似的位置。我们使用一个简单的滤波模型对视注模式和点的显著性进行建模,并表明参与者将近距离(2°-2.5°视角)的点组判断为不同的子集。建模结果与以下观点一致,即枚举涉及基于物体显著性的视觉分组机制,并且特定的枚举需求会影响注视的空间分布。我们的研究结果强调了集合计算而非物体处理本身在数量处理模型中的重要性。