title: Discriminating contrast discontinuities: asymmetries, dipper functions, and perceptual learning.
abstract: In a visual search task, a target has to be found among distractors. For two given elements A and B, the search difficulty can depend on which of the two elements is defined as the target, a phenomenon called search asymmetry. Here, we study to what degree an element's ability to 'win' in a search asymmetry depends on its absolute contrast (first-stage signal) and to what degree it depends on its contrast difference from the background (second-stage signal). One quadrant contained a target texture (2 x 2 Gabor patches of contrast c(tg)), and the other three quadrants contained distractor textures (2 x 2 Gabor patches of contrast c(dt)). These four 'foreground textures' were embedded in a background texture consisting of patches with contrast c(bg). The task was to identify which quadrant contained the target. Quadrants are referred to as increments (foreground contrast c(fg)>c(bg)), or decrements (c(fg)<c(bg)). We found that the second-stage signal determines which element wins the performance asymmetry, i.e. it is easier to find strong increments (decrements) among weak increments (decrements) than vice versa. A comparison of our data with the prediction of the independent-processing model [Vision Res. 40 (2000) 2677] shows that the observed performance asymmetries are in general too large to be attributed to noise differences alone. Rather, asymmetries might reflect a global competition between salient elements. Moreover, performance asymmetries can reverse during practice. We characterize a dipper-shaped nonlinearity on the second stage: discrimination of increment (decrement) signals x and x+Delta x first improves for increasing x, and then deteriorates.
authors.affiliation: Sektion Visuelle Sensorik, Universitäts-Augenklinik Tübingen, Germany. barbara@white.stanford.edu
authors.forename: B
authors.initials: B
authors.lastname: Zenger-Landolt
authors.forename: M
authors.initials: M
authors.lastname: Fahle
mesh_terms: D015350:Contrast Sensitivity / Q000502:physiology*; D004193:Discrimination Learning / Q000502:physiology; D004192:Discrimination, Psychological / Q000502:physiology*; D006801:Humans; D008960:Models, Psychological; D012372:ROC Curve