A signal detection model predicts the effects of set size on visual searchaccuracy for feature, conjunction, triple conjunction, and disjunction displays

Recently quantitative models based on signal detection theory have been suc cessfully applied to the pre diction of human accuracy in visual search for a target that differs from distracters along a single attribute (feature s earch). The present paper extends these models for visual search accuracy t o multidimensional search displays in which the target differs from the dis tracters along more than one feature dimension (conjunction, disjunction, a nd triple conjunction displays). The model assumes that each element in the display elicits a noisy representation for each of the relevant feature di mensions. The observer combines the representations across feature dimensio ns to obtain a single decision variable, and the stimulus with the maximum value determines the response. The model accurately predicts human experime ntal data on visual search accuracy in conjunctions and disjunctions of con trast and orientation. The model accounts for performance degradation witho ut resorting to a limited-capacity spatially localized and temporally seria l mechanism by which to bind information across feature dimensions.