Article

Searching for unknown feature targets on more than one dimension: investigating a "dimension-weighting" account.

Birkbeck College, University of London, England.
Perception & Psychophysics (Impact Factor: 1.37). 01/1996; 58(1):88-101. DOI: 10.3758/BF03205479
Source: PubMed

ABSTRACT Search for odd-one-out feature targets takes longer when the target can be present in one of several dimensions as opposed to only one dimension (Müller, Heller, & Ziegler, 1995; Treisman, 1988). Müller et al. attributed this cost to the need to discern the target dimension. They proposed a dimension-weighting account, in which master map units compute, in parallel, the weighted sum of dimension-specific saliency signals. If the target dimension is known in advance, signals from that dimension are amplified. But if the target dimension is unknown, it is determined in a process that shifts weight from the nontarget to the target dimension. The weight pattern thus generated persists across trials, producing intertrial facilitation for a target (trial n + 1) dimensionally identical to the preceding target (trial n). In the present study, we employed a set of new tasks in order to reexamine and extend this account. Targets were defined along two possible dimensions (color or orientation) and could take on one of two feature values (e.g., red or blue). Experiments 1 and 2 required absent/present and color/orientation discrimination of a single target, respectively. They showed that (1) both tasks involve weight shifting, though (explicitly) discerning the dimension of a target requires some process additional to simply detecting its presence; and (2) the intertrial facilitation is indeed (largely) dimension specific rather than feature specific in nature. In Experiment 3, the task was to count the number of targets in a display (either three or four), which could be either dimensionally the same (all color or all orientation) or mixed (some color and some orientation). As predicted by the dimension-weighting account, enumerating four targets all defined within the same dimension was faster than counting three such targets or mixed targets defined in two dimensions.

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