Academic journal article Perception and Psychophysics

Tracking Unique Objects

Academic journal article Perception and Psychophysics

Tracking Unique Objects

Article excerpt

Is content addressable in the representation that subserves performance in multiple-object-tracking (MOT) experiments? We devised an MOT variant that featured unique, nameable objects (cartoon animals) as stimuli. There were two possible response modes: standard, in which observers were asked to report the locations of all target items, and specific, in which observers had to report the location of a particular object (e.g., "Where is the zebra?"). A measure of capacity derived from accuracy allowed for comparisons of the results between conditions. We found that capacity in the specific condition (1.4 to 2.6 items across several experiments) was always reliably lower than capacity in the standard condition (2.3 to 3.4 items). Observers could locate specific objects, indicating a content-addressable representation. However, capacity differences between conditions, as well as differing responses to the experimental manipulations, suggest that there may be two separate systems involved in tracking, one carrying only positional information, and one carrying identity information as well.

(ProQuest-CSA LLC: ... denotes formulae omitted.)

We all live in a dynamic environment characterized by multiple, distinctive objects that move through the world. In the study of visual attention, however, when researchers have studied distinctive objects, those objects have not moved (e.g., Henderson & Hollingworth, 2003; Oliva, Torralba, Castelhano, & Henderson, 2003; Wolfe, Oliva, Horowitz, Butcher, & Bompas, 2002), and when they have instead examined the ability to attend to moving objects, those objects have not been distinctive. In this article, we will explore the role of attention in keeping track of identifiable objects as they move through the world.

In recent years, the multiple-object-tracking (MOT) task (Pylyshyn & Storm, 1988) has emerged as a primary tool for studying dynamic attention-that is, attention to objects over time. In the standard version of MOT, the observer is initially presented with a display of eight identical items, with four of the items blinking on and off to identify them as targets. All of the items then move for several seconds, during which the observer has to keep track of the targets. When the objects stop, the observer is asked to discriminate between targets and nontargets, either by pointing out all of the targets or by indicating whether a probe item is a target or a nontarget. The typical result is that humans can accurately track about four targets, although performance strongly depends on stimulus factors such as the speed of the items (Alvarez & Franconeri, 2004; Oksama & Hyönä, 2004).

The MOT paradigm has proved to be a versatile research tool. It has been used to study the nature of visual objects (Scholl & Pylyshyn, 1999; Scholl, Pylyshyn, & FeIdman, 2001), the capacity for change detection (Bahrami, 2003; Saiki, 2002), and the allocation of attention in depth (Viswanathan & Mingolla, 2002). Furthermore, despite its artificial nature, the MOT paradigm seems to capture the demands of important real-world challenges. For instance, air traffic controllers need to track the changing positions of multiple planes in an airspace (see Alien, McGeorge, Pearson, & Milne, 2004), drivers need to pay attention to other cars in their immediate vicinity, athletes need to track teammates and opponents, and daycare providers need to be aware of the movements of several children at once.

Although the MOT task can be informative, it differs from such real-world tasks in critical and related ways. First, objects in the real world (cars, children, etc.) are rarely identical; they can differ in visual features as well as in characteristic motion. second, the type of real-world answer that we demand of our visual system is typically different from the answer demanded of the observer during MOT. In the standard MOT task, observers are asked to differentiate between tracked targets and untracked nontargets. …

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