A laminar cortical model of stereopsis and later stages of 3D surface perception is developed and simulated. The model describes how initial stages of monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface filling-in in the lateral geniculate nucleus and cortical areas V1, V2, and V4. In particular, it details how interactions between layers 4, 3B, and 2/3A in V1 and V2 contribute to stereopsis, and clarifies how binocular and monocular information combine to form 3D boundary and surface representations. Along the way, the model modifies and significantly extends the disparity energy model. Neural explanations are given for psychophysical data concerning: contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, Panum's limiting case, the Venetian blind illusion, stereopsis with polarity-reversed stereograms, da Vinci stereopsis, and various lightness illusions. By relating physiology to psychophysics, the model provides new functional insights and predictions about laminar cortical architecture.

In everyday life, observers often need to visually track moving objects. Currently, there is a debate as to whether observers utilize motion information in doing this or whether they rely purely on positional information (e.g., frame-by-frame locations). In our experiments, we had observers keep track of a subset of moving objects. In one condition, the objects moved in straight lines and their future positions were thus predictable. In a second condition, the objects changed directions randomly. Across three experiments, tracking performance was better in the predictable condition, suggesting that observers can use motion to help them track objects, at least when tracking just two. When tracking four objects, performance was not different between the two conditions. We discuss these findings in relation to several theories of object tracking.

Humans can track multiple moving objects. Is this accomplished by attending to all the objects at the same time or do we attend to each object in turn? We addressed this question using a novel application of the classic simultaneous-sequential paradigm. We considered a display in which objects moved for only part of the time. In one condition, the objects moved sequentially, whereas in the other condition they all moved and paused simultaneously. A parallel model would predict that the targets are tracked independently, so the tracking of one target should not be influenced by the movement of another target. Thus, one would expect equal performance in the two conditions. Conversely, a simple serial account of object tracking would predict that an observer's accuracy should be greater in the sequential condition because in that condition, at any one time, fewer targets are moving and thus need to be attended. In fact, in our experiments we observed performance in the simultaneous condition to be equal to or greater than the performance in the sequential condition. This occurred regardless of the number of targets or how the targets were positioned in the visual field. These results are more directly in line with a parallel account of multiple object tracking.

The attentional processes for tracking moving objects may be largely hemisphere-specific. Indeed, in our first two experiments the maximum object speed (speed limit) for tracking targets in one visual hemifield (left or right) was not significantly affected by a requirement to track additional targets in the other hemifield. When the additional targets instead occupied the same hemifield as the original targets, the speed limit was reduced. At slow target speeds, however, adding a second target to the same hemifield had little effect. At high target speeds, the cost of adding a same-hemifield second target was approximately as large as would occur if observers could only track one of the targets. This shows that performance with a fast-moving target is very sensitive to the amount of resource allocated. In a third experiment, we investigated whether the resources for tracking can be distributed unequally between two targets. The speed limit for a given target was higher if the second target was slow rather than fast, suggesting that more resource was allocated to the faster of the two targets. This finding was statistically significant only for targets presented in the same hemifield, consistent with the theory of independent resources in the two hemifields. Some limited evidence was also found for resource sharing across hemifields, suggesting that attentional tracking resources may not be entirely hemifield-specific. Together, these experiments indicate that the largely hemisphere-specific tracking resource can be differentially allocated to faster targets.

Observers often need to attentively track moving objects. In everyday life, such objects are often visually distinctive. Previous studies have shown that tracking accuracy is increased when the targets contain a visual feature (e.g., a color) not possessed by the distractors. Conversely, a gain in tracking accuracy was not observed when the targets differed from the distractors by only a conjunction of features (Makovski and Jiang, 2009a). In this study we confirm that some conjunction targets have relatively little effect on tracking accuracy, but show that other conjunction targets can significantly aid tracking. For example, tracking accuracy is relatively high when the targets are small red squares and half the distractors are large red squares while the remaining distractors are small green squares. This seems to occur because the targets have a set of features (small and red) not shared by any one distractor. Attending to these features directs attention more to the targets than the distractors, thereby making the targets easier to track. Existing theories of attentive tracking cannot explain these results.

The footsteps illusion (FI) demonstrates that an object's background can have a profound effect on the object's perceived speed. This illusion consists of a yellow bar and a blue bar that move over a black-and-white, striped background. Although the bars move at a constant rate, they appear to repeatedly accelerate and decelerate in antiphase with each other. Previously, this illusion has been explained in terms of the variations in contrast at the leading and trailing edges of the bars that occur as the bars traverse the striped background. Here, we show that this explanation is inadequate and instead propose that for each bar, the bar's leading edge, trailing edge, lateral edges, and the surrounding background edges all contribute to the bar's perceived speed and that the degree to which each edge contributes to the motion percept is determined by that edge's contrast. We show that this theory can explain all the data on the FI as well as the belly dancer and Wenceslas illusions. We conclude by presenting a new illusion, the kickback illusion, which, although geometrically similar to the FI, is mediated by a different mechanism, namely, reverse phi motion.

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White's effect (also known as the Munker White effect) is a lightness illusion in which, contrary to expectations based on simultaneous contrast and Wallach's rule, a gray rectangle predominantly surrounded by white appears lighter than an identical rectangle that is mainly surrounded by black. The illusion is often explained in terms of T-junctions that are formed by the three-way intersection of the gray rectangle, a black stripe, and a white stripe. I present a circular variant of White's effect in which all the junctions have been removed without significantly affecting the strength of the illusion, suggesting that junctions are not an important consideration in all versions of White's effect.