An inter-item similarity model unifying feature and conjunction search

We propose a model of visual search to address the hitherto unresolved issue of reconciling serial deployment of attention accounts with inter-item similarity effects. Target-distractor and distractor-distractor similarity were systematically varied in 85 (17x5) set type-size conditions over seven experiments, including univariate feature and bivariate conjunction search. The model, a power (square root) function of dimension-specific target-distractor and distractor-distractor similarity in linear combination with set size, accounted for 98% of the variance on type-size means. It suggests that much of efficient and inefficient search can be unified under a single theory involving item similarity.