A model of neural mechanisms in monocular transparent motion perception

Transparent motion is perceived when multiple motions are presented in the same part of visual space which moves in different directions. Several psychophysical as well as physiological experiments have studied the conditions un-der which motion transparency occurs. Few model mecha-nisms have been proposed to segregate multiple motions. We present a novel neural model which investigates the necessary mechanisms underlying initial motion detection, the required representations for velocity coding, and the in-tegration and segregation of motion stimuli. The model ex-tends a previously developed architecture for dorsal path-way computations, particularly, in cortical areas V1, MT, and MST, emphasizing the role of feedforward cascade processing and feedback from higher to earlier stages for selective feature enhancement and tuning. Our results demonstrate that the model reproduces several psychophys-ical findings using random dot stimuli. Moreover, the model is able to process transparent motion in real-world sequences of 3D scenes. KEY WORDS transparent motion, neural model, motion integration, area MT, area MST, feedback.