Logical Rules and the Classification of Integral-Dimension Stimuli.

A classic distinction in perceptual information processing is whether stimuli are composed of separable dimensions, which are highly analyzable, or integral dimensions, which are processed holistically. Previous tests of a set of logical-rule models of classification have shown that separable-dimension stimuli are processed serially if the dimensions are spatially separated and as a mixture of serial and parallel processes if the dimensions are spatially overlapping (Fifić, Little, & Nosofsky, 2010; Little, Nosofsky, & Denton, 2011). In the current research, the logical-rule models are applied to predict response-time (RT) data from participants trained to classify integral-dimension color stimuli into rule-based categories. In dramatic contrast to the previous results for separable-dimension stimuli, analysis of the current data indicated that processing was best captured by a single-channel coactive model. The results converge with previous operations that suggest holistic processing of integral-dimension stimuli and demonstrate considerable generality for the application of the logical-rule models to predicting RT data from rule-based classification experiments.