Dissociating stimulus information from internal representation—a case study in object recognition

Human object recognition is a function of both internal memory representation(s) and stimulus input information. The role of the latter has been so far largely overlooked, and the nature of the representation is often directly equated with recognition performance. We quantify stimulus information for three classes of objects in order of decreasing object complexity: unconnected balls, balls connected with lines, and balls connected with cylinders. In an object discrimination task, subjects' performance improved with the decreasing object complexity. We show that input information also increases with decreasing object complexity. Therefore, the results could potentially be accounted for either by differences in the object representations learned for each class of objects, or by the increased information about the three-dimensional (3D) structure inherent in images of the less complex objects, or by both. We demonstrate that, when image information is taken into account, by computing efficiencies relative to a set of ideal observers, subjects were more efficient in recognizing the less complex objects. This suggests that differences in subjects' performance for different object classes is at least partly a function of the internal representations learned for the different object classes. We stress that this conclusion cannot be achieved without the quantitative analysis of stimulus input information.