We propose a network model that accounts for the kinetic depth in structure from motion phenomena. Using plausible neural mechanisms, the model accounts for (1) fluctuations in perception when viewing a simple kinetic depth stimulus, (2) disambiguation of this stimulus with stereoscopic information, and (3) subsequent bias of the percept of this stimulus following stereoscopic adaptation. The model comprises two levels: a layer of monocular directionally selective motion detectors that provide input to a second layer of disparity- selective and direction-selective binocular mechanisms. The network of facilitatory and inhibitory connections between binocular mechanisms gives rise to fluctuations in network activity that mimic the fluctuations in perception of kinetic depth in the absence of disparity information. The results of a psychophysical experiment are consistent with the nature of the proposed interactions.

This study examined the effectiveness with which motion parallax information can be utilized by rhesus monkeys for depth perception. A visual display comprised of random-dots that mimicked a rigid, three-dimensional object rocking back and forth was used. Differential depth was produced by presenting sub-regions of the dots moving at different velocities from the rest of dots in the display. The tasks for the monkeys were to detect or discriminate a target region that was protruding the furthest from the background plane. To understand the role of stimulus movement, we examined the accuracy and the rapidity of the saccadic responses as a function of rocking velocity of the entire three-dimensional object. The results showed that performance accuracy improved and reaction times decreased with increasing rocking velocities. The monkeys can process the motion parallax information with remarkable rapidity such that the average reaction time ranged between 212 and 246 milliseconds. The data collected suggest that the successive activation of just two sets of cones is sufficient to perform the task.

Although a number of global mechanisms have been proposed over the years that explain how crabs might separate the rotational and translational components of their optic flow field, there has been no evidence to date that local mechanisms such as motion parallax are used in this separation. We describe here a study that takes advantage of a recently developed suite of computer-generated visual stimuli that creates a three-dimensional world surrounding the crab in which we can simulate translational and rotational optic flow. We show that, while motion parallax is not the only mechanism used in flow-field separation, it does play a role in the recognition of translational optic flow fields in that, under conditions of low overall light intensity and low contrast ratio when crabs find the distinction between rotation and translation harder, smaller eye movements occur in response to translation when motion parallax cues are present than when they are absent. Thus, motion parallax is one of many cues that crabs use to separate rotational and translational optic flow by showing compensatory eye movements to only the former.