Search asymmetries: Parallel processing of uncertain sensory information

What is the mechanism underlying search phenomena such as search asymmetry? Two-stage models such as Feature Integration Theory and Guided Search propose parallel pre-attentive processing followed by serial post-attentive processing. They claim search asymmetry effects are indicative of finding pairs of features, one processed in parallel, the other in serial. An alternative proposal is that a 1-stage parallel process is responsible, and search asymmetries occur when one stimulus has greater internal uncertainty associated with it than another. While the latter account is simpler, only a few studies have set out to empirically test its quantitative predictions, and many researchers still subscribe to the 2-stage account. This paper examines three separate parallel models (Bayesian optimal observer, max rule, and a heuristic decision rule). All three parallel models can account for search asymmetry effects and I conclude that either people can optimally utilise the uncertain sensory data available to them, or are able to select heuristic decision rules which approximate optimal performance.

► Search asymmetries are often taken to support a 2-stage parallel–serial model of visual processing.
► 1-Stage parallel models offer a simpler account, but there is less empirical support.
► Search asymmetry performance in a covert orientation detection task was evaluated.
► Performance was well described by three different parallel models with different decision rules.
► Humans use noisy visual information optimally, or apply heuristic decision rules.