Guided Search 4.0: Current Progress With a Model of Visual Search

performance, specifically of search tasks in which an observer looks for a target object among some number of distracting items. Classically, models have described two mechanisms of search: serial and parallel (Egeth, 1966). In serial search, attention is directed to one item at a time, allowing each item to be classified as a target or a distractor in turn (Sternberg, 1966). Parallel models propose that all (or many) items are processed at the same time. A decision about target presence is based on the output of this processing (Neisser, 1963). GS evolved out of the two-stage architecture of models like Treisman’s feature integration theory (FIT; Treisman & Gelade, 1980). FIT proposed a parallel, preattentive first stage and a serial second stage controlled by visual selective attention. Search tasks could be divided into those performed by the first stage in parallel and those requiring serial processing. Much of the data comes from experiments measuring reaction time (RT) as a function of set size. The RT is the time required to respond that a target is present or absent. Treisman proposed that there was a limited set of attributes (e.g. color, size, motion) that could be processed in parallel, across the whole visual field (Treisman, 1985, 1986; Treisman & Gormican, 1988). These produced RTs that were essentially independent of the set size. Thus, slopes of RT set size functions were near zero. In FIT, targets defined by two or more attributes required the serial deployment of attention. The critical difference between preattentive search tasks and serial tasks was that the serial tasks required a serial “binding” step (Treisman, 1996; von der Malsburg, 1981). One piece of brain might analyze the color of an object. Another might analyze its orientation. Binding is the act of linking those bits of information into a single representation of an object—an object file (Kahneman, Treisman, & Gibbs, 1992). Tasks requiring serial deployment of attention from one item to the next produce RT set size functions with slopes markedly greater than zero (typically, about 20–30 ms/item for target-present trials and a bit more than twice that for target-absent). 8