Author:
Cohen-Duwek Hadar,Spitzer Hedva
Abstract
abstractMotion estimation is an essential ability for sighted animals to survive in their natural environment. Many anatomical and electrophysiological studies on low visual levels have been based on the classic pioneering HRC (Hassenstein & Reichaedt Correlator) computational model. The accumulated experimental findings, which have given rise to a debate in the current computational models regarding the interaction between the On and Off pathways. The previous algorithms were challenged to correctly predict physiological experiment results and the two types of motion: a) Phi motion, also termed apparent motion. b) Reverse-phi motion that is perceived when the image contrast flips during the rapid succession. We have developed a computational model supported by simulations, which for the first time leads to correct predictions of the behavioral motions (phi and reverse-phi), while considering separated On and Off pathways and is also in agreement with the relevant electrophysiological findings. This has been achieved through the well-known neuronal response: the rebound response or “Off response”. We suggest that the rebound response, which has not been taken into account in the previous models, is a key player in the motion mechanism, and its existence requires separation between the On and the Off pathways for correct motion interpretation. We furthermore suggest that the criterial reverse-phi effect is only an epiphenomenon of the rebound response for the visual system. The theoretical predictions are confirmed by a psychophysical experiment on human subjects. Our findings shed new light on the comprehensive role of the rebound response as a parsimonious spatiotemporal detector for motion and additional memory tasks, such as for stabilization and navigation.
Publisher
Cold Spring Harbor Laboratory