Academic journal article Attention, Perception and Psychophysics

Additional-Singleton Interference in Efficient Visual Search: A Common Salience Route for Detection and Compound Tasks

Academic journal article Attention, Perception and Psychophysics

Additional-Singleton Interference in Efficient Visual Search: A Common Salience Route for Detection and Compound Tasks

Article excerpt

In efficient search for feature singleton targets, additional singletons (ASs) defined in a nontarget dimension are frequently found to interfere with performance. All search tasks that are processed via a spatial saliency map of the display would be predicted to be subject to such AS interference. In contrast, dual-route models, such as feature integration theory, assume that singletons are detected not via a saliency map, but via a nonspatial route that is immune to interference from cross-dimensional ASs. Consistent with this, a number of studies have reported absent interference effects in detection tasks. However, recent work suggests that the failure to find such effects may be due to the particular frequencies at which ASs were presented, as well as to their relative saliency. These two factors were examined in the present study. In contrast to previous reports, cross-dimensional ASs were found to slow detection (target-present and target-absent) responses, modulated by both their frequency of occurrence and saliency (relative to the target). These findings challenge dual-route models and support single-route models, such as dimension weighting and guided search.

Detection and attentional selection of a unique item in the visual scene are frequent requirements for observers in both natural and laboratory environments. In detection tasks, one decides whether a unique item (target) is present in or absent from a set of other items (nontargets, or distractors). By contrast, in compound tasks (Bravo & Nakayama, 1992; Duncan, 1985), one must attentionally select and further analyze the unique item in order to permit the reporting of some response-critical attribute. There is general agreement that the uniqueness of an item in the visual scene can be represented topographically in a saliency map (Itti & Koch, 2000; Koch & Ullman, 1985; Wolfe, 1994), but there is a debate about how this map is involved in detection and attentional selection.

Although some authors have assumed that both detection tasks and tasks involving attentional selection are processed via a saliency map-see, for instance, Found and Müller's (1996) dimension-weighting account (DWA), Wolfe's (1994) Guided Search 2.0 (GS), and Müller, Heller, and Ziegler (1995)-others have proposed a dual-route hypothesis. For example, feature integration theory (FIT; Treisman & Gelade, 1980; Treisman & Gormican, 1988; Treisman & Sato, 1990) assumes that only tasks involving attentional selection are processed via a master (saliency) map. In contrast, according to FIT, detection tasks are processed via so-called dimensional modules, which signal that a unique item is present within a particular dimension, but in a nonspatial manner; in other words, they signal the presence of, but not the location of, a unique item. Thus, if the target dimension is known in advance (within-dimension search), detection decisions can be based on monitoring the output of a single, prespecified module: "The 'odd one out' pops out within a single, prespecified dimensional module" (Treisman, 1988, p. 207). In contrast, when the singletondefining dimension varies randomly across trials (crossdimension search), "each different module may need to be separately checked to determine which of them contains the [odd-one-out item]" (Treisman, 1988, p. 207). This notion of dimensional modules was introduced to explain two findings-namely, singleton detection's being (1) faster in within-dimensional than in cross-dimensional search (see also Müller et al., 1995) and (2) faster when there is distractor heterogeneity in non-target-defining dimensions, rather than in the target-defining dimension.

The notion of dimensional modules has recently been revived by Chan and Hayward (2009) and Kumada (1999) on the basis of a comparison of detection tasks (for which spatial information is not strictly necessary) with compound and localization tasks, which require spatial information. …

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