Abstract
People are faster and more accurate at detecting a certain feature, say, a left parenthesis, when presented within a context, “( )”, than when presented alone, “(” (Pomerantz et al, 1977; 2003). Similarly, people seem be better at identifying a given facial feature, say a nose, within the context of a face, than when the nose is presented alone. According to theories of configural processing, highly symmetrical (“good figures”) or highly learned (faces) figures are processed as a Gestalt, and that holistic experience aids in the resolution of comprising parts. We applied System Factorial Technology, developed by Townsend and Nozawa (1995), to examine whether the influence of configuration can be measured in terms of architecture, capacity, stopping rule and (in)dependence. The participants performed in a redundant target search task, in which a single stimulus was presented on each trial, comprised of a diagonal line (either left, “”, or right, “/”) and the shape “L” (presented normally, or as a horizontal mirror image). Participants had to detect the target items “/”, rotated “L”, or both. In experiment 1, the two items were combined together such that they formed a Gestalt. The results showed no redundancy gains. In fact, Participants were faster on single target trials (449.8 ms) then they were on redundant target trials (634.1 ms). Capacity, calculated as the ratio between the integrated hazard functions of redundant target and the sum of single target conditions, was severely limited, suggesting that configural processing was actually stronger for the single target displays than for the redundant target displays. In addition, topological similarity may also play an important role in RT tasks. In further experiments, we constructed the stimuli such that the comprising parts did not necessarily formed “good” configurations. Results were different both in terms of mean RTs and in terms of the properties of the underlying cognitive system (i.e., its architecture, capacity etc.).
This research was supported by NIH-NIMH Grant MH057717.