SIAM, a model of structural similarity, is presented. SIAM, along with models of analogical reasoning, predicts that the relative similarity of different scenes will vary as a function of processing time. SIAM's prediction Is empirically tested by having subjects make speeded judgements about whether two scenes have the same objects. The similarity of two scenes with different objects is measured by the percentage of trials on which the scenes are called the same. Consistent with SIAM's prediction, similarity becomes increasingly influenced by the global consistency of feature matches with time. Early on, feature matches are most influential if they belong to similar objects. Later on, feature matches are most influential if they place objects in alignment in a manner that is consistent with other strong object alignments. The similarity of two scenes, rather than being a single fixed quantity, varies systematically with the time spent on the comparison.

Two methods of representing concepts are distinguished and empirically investigated. Negatively defined concepts are defined in terms of other concepts at the same level of abstraction. Positively defined concepts do not make recourse to other concepts at the same level of abstraction for their definition. In two experiments, subjects are biased to represent concepts underlying visual patterns in a positive manner by instructing subjects to form an image of the the learned concepts and by initially training subjects on minimally distorted concept instances. Positively defined concepts are characterized by a large use of nondiagnostic features in concept representations, relative to negatively defined concepts. The distinction between positively and negatively defined concepts can account for the dual nature of natural concepts - as directly accessed during the recognition of items, and as intricately interconnected to other concepts.