A Bioplausible Model for the Expanding Hole Illusion: Insights into Retinal Processing and Illusory Motion

TL;DR

This paper introduces a biologically inspired computational model that explains the expanding hole illusion by simulating early retinal processing and contrast-dependent lateral inhibition, shedding light on the neural basis of this visual phenomenon.

Contribution

The study presents a novel DoG-based retinal model that accounts for the illusion's perceptual and physiological effects, advancing understanding of early visual processing mechanisms.

Findings

Contrast gradients and multi-layered processing explain the illusion.

Retinal ganglion cells contribute to the perceived expansion.

The model aligns with psychophysical and physiological data.

Abstract

The Expanding Hole Illusion is a compelling visual phenomenon in which a static, concentric pattern evokes a strong perception of continuous forward motion. Despite its simplicity, this illusion challenges our understanding of how the brain processes visual information, particularly motion derived from static cues. While the neural basis of this illusion has remained elusive, recent psychophysical studies [1] reveal that this illusion induces not only a perceptual effect but also physiological responses, such as pupil dilation. This paper presents a computational model based on Difference of Gaussians (DoG) filtering and a classical receptive field (CRF) implementation to simulate early retinal processing and to explain the underlying mechanisms of this illusion. Based on our results we hypothesize that the illusion arises from contrast-dependent lateral inhibition in early visual processing. Our results demonstrate that contrast gradients and multi-layered spatial processing contribute to the perception of expansion, aligning closely with psychophysical findings and supporting the role of retinal ganglion cells in generating this illusory motion signal. Our findings provide insights into the perceptual biases driving dynamic illusions and offer a new framework for studying complex visual phenomena.