title: Global scene layout modulates contextual learning in change detection.
abstract: Change in the visual scene often goes unnoticed - a phenomenon referred to as "change blindness." This study examined whether the hierarchical structure, i.e., the global-local layout of a scene can influence performance in a one-shot change detection paradigm. To this end, natural scenes of a laid breakfast table were presented, and observers were asked to locate the onset of a new local object. Importantly, the global structure of the scene was manipulated by varying the relations among objects in the scene layouts. The very same items were either presented as global-congruent (typical) layouts or as global-incongruent (random) arrangements. Change blindness was less severe for congruent than for incongruent displays, and this congruency benefit increased with the duration of the experiment. These findings show that global layouts are learned, supporting detection of local changes with enhanced efficiency. However, performance was not affected by scene congruency in a subsequent control experiment that required observers to localize a static discontinuity (i.e., an object that was missing from the repeated layouts). Our results thus show that learning of the global layout is particularly linked to the local objects. Taken together, our results reveal an effect of "global precedence" in natural scenes. We suggest that relational properties within the hierarchy of a natural scene are governed, in particular, by global image analysis, reducing change blindness for local objects through scene learning.
authors.affiliation: Allgemeine und Experimentelle Psychologie, Department Psychologie, Ludwig-Maximilians-Universität München München, Germany.
authors.forename: Markus
authors.initials: M
authors.lastname: Conci
authors.affiliation: Allgemeine und Experimentelle Psychologie, Department Psychologie, Ludwig-Maximilians-Universität München München, Germany.
authors.forename: Hermann J
authors.initials: HJ
authors.lastname: Müller
keywords: change blindness; change detection; contextual learning; local/global processing; natural scenes; visual attention