Number is more than meets the eye: Unveiling segmentation mechanisms in numerosity perception with visual illusions

Animals and humans possess an adaptive ability to rapidly estimate approximate numerosity, yet the visual mechanisms underlying this process remain poorly understood. Evidence suggests that approximate numerosity relies on segmented perceptual units modulated by grouping cues, with perceived numerosity decreasing when objects are connected by irrelevant lines, independent of low-level features. However, most studies have focused on physical objects.

Illusory contours (ICs) are powerful tools for exploring visual segmentation mechanisms, as “illusory” objects exhibit perceptual biases (e.g., tilt aftereffect) similar to real objects, suggesting shared processing mechanisms. To investigate whether approximate numerosity perception of ICs is influenced by connectedness, we conducted a psychophysical forced-choice task. Participants compared Ehrenstein-like ICs ensembles of varying numerosities interspersed with four task-irrelevant lines. We manipulated the number of connected pairs (0, 2, or 4) by aligning lines with the ICs-triggering gaps, while controlling low-level features across conditions. Our results revealed a monotonic underestimation of numerosity as connections increased, with constant precision reflecting Weber-like encoding. Reaction times proportionally increased with connectedness, suggesting an underlying recurrent neural mechanism. These findings demonstrate that ICs ensembles are subject to the same connectedness effect as real objects, supporting a shared visual mechanism for numerosity extraction.

This work highlights the parallels between real and illusory object processing and provides insights into segmentation mechanisms relevant to models of artificial intelligence and visual perception.