Attention in visual search: multiple search classes

Data from visual-search tasks are typically interpreted to mean that searching for targets defined by feature differences does not require attention and thus can be performed in parallel, whereas searching for other targets requires serial allocation of attention. The question addressed here was whether a parallel-serial dichotomy would be obtained if data were collected using a variety of targets representing each of several kinds of defining features. Data analyses included several computations in addition to search rate: (1) target-absent to target-present slope ratios; (2) two separate data transformations to control for errors; (3) minimum reaction time; and (4) slopes of standard deviation as a function of set size. Some targets showed strongly parallel or strongly serial search, but there was evidence for several intermediate search classes. Sometimes, for a given target-distractor pair, the results depended strongly on which character was the target and which was the distractor. Implications from theories of visual search are discussed.