Distinguishing between parallel and serial accounts of multiple 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.