Configurational effects on the enumeration of dots: Counting by groups

The processing time for quantifying numerosity of two-dimensional dot patterns was investigated as a function of both number of dots and relative proximity between dots. A cluster algorithm (CODE) was first developed as a formal model of how human subjects organize neighboring dots into groups. CODE-based predictions of grouping effects on number processing latencies were then tested with patterns consisting of n dots (range n = 13–23). The results largely confirmed CODE-based predictions and thereby indicated that large collections of dots are preferably counted by groups. Small (n ≤ 5) groups are subitized and their partial results are summed to a running total. Based on criteria other than dot proximity, large (n > 5), proximity-based groups are subdivided into smaller groups of two or three dots, which are again subitized.