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John Thompson
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A silent compromise was reached through no agreement on my part. Mary climbed onto my lap and attached herself. It made driving difficult especially when she bounced up and down obstructing my view and I began to swerve out of my lane.

Unlimited-capacity models posit that divided attention among multiple objects does not limit perception, because there is no system-level limit on perceptual processing. Importantly, unlimited-capacity processing does not necessarily imply fast or accurate object recognition, because perception is still noise-limited at the level of local mechanisms. The definitive property of unlimited-capacity models is that the rate of individual stimulus processing is not degraded by divided attention. The prototype model of this class is the standard parallel model in which multiple analyses occur in parallel, with the rate of each analysis unaffected by the number of objects being analyzed (Gardner, 1973). A less intuitive example model is the super-capacity serial model in which only one analysis can be carried out at a time, but the speed of each analysis increases proportionally with the number of objects of interest so that system-level capacity is unlimited (Townsend, 1974). The standard parallel model and super-capacity serial model can make equivalent predictions for many experiments, making them difficult to distinguish.

In contrast, fixed-capacity models assume an inflexible limit on the overall rate of information accrual. An intuitive example is the standard serial model in which one object process must be completed before another can begin (Davis, Shikano, Peterson, & Michel, 2003; Townsend, 1974). Parallel processing can also have fixed capacity, for example, if multiple concurrent analyses are carried out with efficiency inversely proportional to the number of relevant stimuli (e.g., the parallel sampling model of Shaw, 1980).

A second common method of investigating perceptual capacity limitations is the psychophysical dual-task experiment, in which observers make two independent psychophysical judgment concurrently (Bonnel, Stein, & Bertucci, 1992; Sperling & Melchner, 1978). Performance in the dual task can then be compared to single-task controls to determine whether dividing attention in the dual-task condition caused performance decrements. The challenge with this method is to determine whether any performance decrements are due to loss in perceptual sensitivity or to interference in decision and/or response mechanisms because the number of stimuli to be monitored is confounded with the number of decisions and responses to be made.

Biederman, Blickle, Teitelbaum, and Klatsky (1987) used the response time search task with line drawings of familiar objects as stimuli (e.g., car, fire hydrant, filing cabinet). Following a brief display of an array of objects, subjects indicated whether or not a specific object had been present. Both error rate and response time increased with set size, effects that were interpreted as evidence for limited-capacity object perception. However, Biederman et al.'s use of the response-time set-size paradigm makes this interpretation ambiguous, because the set-size effect could be explained by an effect on the decision processes as described above. Furthermore, the semantic categorization required by the task confounds object shape recognition with semantic categorization.

More recent work by Rousselet, Fabre-Thrope, and Thorpe (2002) used search studies in which subjects searched for animals or vehicles among distracter images that did not contain those targets. Rousselet et al. compared speed and accuracy performance to the predictions of unlimited-capacity models. The results were consistent with standard parallel models of object perception, at least in the special case of animal and vehicle searches. However, as others have pointed out, such categories of image might easily be discriminated by non-shape image features, either those intrinsic to the object (e.g., furriness; Evans & Treisman, 2005) or those induced by the style of photography used in images containing animals (sharp focus and blurred background, Wichmann, Drewes, Rosas, & Gegenfurtner, 2010). Thus, although object recognition tasks yielded unlimited capacity results in these studies, it is not clear if parallel search was accomplished on the basis of object shape recognition or on the basis of non-shape diagnostic features.


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