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.