The perception of entropy in rapidly moving sparse dot arrays: a nonlinear dynamic perspective

In visual fields composed of dots spatially randomly distributed but moving rigidly, the percept of coherent motion is lost once D_max is exceeded, resulting in an incoherent, random percept. We have investigated this transition both from a psychophysics perspective and in the development of a dynamic model of the visual system based on a spatially coupled array of nonlinear damped mass-springs cells. We present results of experiments using rigidly moving arrays of dots of different levels of sparseness and differing displacement magnitudes. Results show that the perception of randomness can be reliably judged and displays a transition from coherent to non-coherent motion as the motion amplitude is increased. Using standard psychophysical just noticeable difference (JND) judgements, we noted that the threshold JND was a function of displacement magnitude and sparseness and could not be explained by extant spatiotemporal filtering models. Our model qualitatively explains the important features of the data, reproducing the experimental D_max and entropy perception effects with increased stimuli motion amplitude at different spatial sparseness levels. We have then performed some numerical simulations of the model when the masses in the array are randomly distributed. Results show that sparseness plays different role if close or far from D_max in terms of motion coherence discrimination.