Proceedings of the Annual Meeting of the Cognitive Science Society

handful of prominent theories have been proposed to explain a large quantity of experimental data on visual attention. We are developing a connectionist network model of visual attention which provides an alternative theory of attention based on computational principles. In this paper, we describe aspects of the model relevant to the dependence of visual search times on display size (number of objects in the stimulus image). Duncan's stimulus similarity theory provides the characterization of the experimental data which we use in simulating and evaluating our model. The characteristics of the network model that support the continuously varying dependence of search time on display size are the constraint propagation search implemented by a winner-take-all mechanism in the attention layer, and the lateral inhibition network within each primitive feature map, which provides the feature contrast needed to filter out background textures. W e report the results of simulations of the model, which agree with experimental data on visual attention in human subjects.