Learning “What” and “Where” in Visual Search

Abstract

Visual search is facilitated when observers search through repeated displays. This effect, termed contextual cueing (CC), reflects the exceptional ability of our cognitive system to utilize regularities embedded in the environment. Recent studies that tested visual search with real-world objects found that CC takes place even in heterogeneous search displays, but only when the identities ("what") and locations ("where") of the objects are both repeated. The purpose of the current study was to test whether the repetition of both "what" and "where" is not only necessary but also sufficient for CC. Consistent with previous results, Experiment 1 found robust CC when both the "what" and "where" information were repeated, and further revealed that the effect was not modulated by the number of search items. In contrast, Experiment 2 showed that the repetition of both objects' identities and locations did not benefit the search when the two were not bound together. CC was also absent in Experiment 3, where the objects' identities and locations were repeated together, however, target locations varied randomly. Together these results suggest that CC with real-world objects is robust, but critically depends on "what" and "where" binding as well as context-target associations. Visual search is not only a task that we perform many times a day, but it is probably also one of the most popular tasks in the study of human visual cognition. Consequently, extensive research has been carried out in order to understand the mechanisms underlying people's search skills (Wolfe, 1998). Visual search has also been widely used as a tool for investigating central cognitive abilities, such as attention, memory, learning, and, notably, their interaction. For instance, many researchers have tested how search history (which naturally involves learning and memory) affects basic search processes, such as attentional guidance (Chun, 2000;Jiang, Swallow, & Rosenbaum, 2013;Maljkovic & Nakayama, 1994;Zhao, Al-Aidroos, & Turk-Browne, 2013). Thus, given the complexity of the task, the various skills involved in it, and its ecological and applied uses (Mitroff et al., 2015), it is no wonder that there are more than 300,000 results when searching for "visual search" in Google scholar.A key expertise of our cognitive system is picking up regularities embedded in the environment and utilizing them to more efficiently process visual scenes (Chun & Jiang, 1998Chun & Turk-Browne, 2008;Fiser & Aslin, 2001Miller, 1988;Nissen & Bullemer, 1987; Turk-Browne, Junge, & Scholl, *Correspondence concerning this article should be sent to: Tal Makovski, Department of Psychology, The Open University of Israel, The Dorothy de Rothschild Campus, 1 University Road, P. O. Box 808, Ra'anana 43107, Israel. (E-mail: talmak@openu.ac.il) 1 I wish to thank Ayelet Golestani for help in data collection and Ido Liviatan for helpful discussions.

Meaning in learning: Contextual cueing relies on objects’ visual features and not on objects’ meaning

“…This manipulation also impaired subjects' ability to verbally name the items, but to a lesser extent, and thus it is not clear how effective it was in removing the meaning of the objects. percentage of measurement of learning was created, and benefit scores were calculated for Epochs 5 and 6 using the following formula (Makovski, 2017):…”

“…1 for an illustration of these conditions). That observers were able to take advantage of the repetition of distractors' identities and locations, even when a scene gist was absent, was found to be robust as it was not modulated by set size or memory load manipulations (Makovski, 2016(Makovski, , 2017. Furthermore, the repetition of both identities and locations did not benefit search when the two were not bound together, suggesting that CC critically depends on what and where binding (namely, the same repeated object must be at the same repeated location) rather than on the two types of information being learned independently (Makovski, 2017).…”

“…Most CC models have emphasized the spatial domain in learning (Brady & Chun, 2007;Jiang & Wagner, 2004;Olson & Chun, 2002), whereas the identities of the objects received only little attention. However, it was recently reported that when real-world objects are used in arbitrary displays, then learning is found only when the same distractors are repeated at the same locations (Makovski, 2016(Makovski, , 2017. That is, the repetition of spatial (where) information was insufficient to facilitate search when item identities (what) varied across repetitions.…”

Editorial: Search: A New Perspective to Understand Cognitive Dynamics

“…The papers in this issue are quite diverse. They cover a variety of topics across the spectrum of contemporary search research: the prevalence effect (Horowitz, 2017); the importance of scene structure (Ueda, Kamakura, & Saiki, 2017); haptic search (Kaga, Kawaguchi, Mishina, Kita, & Watanabe, 2017); contextual cueing (Higuchi & Saiki, 2017;Makovski, 2017); foraging (Jóhannesson, Kristjánsson, & Thornton, 2017); inhibition of return (Niimi, Shimada, & Yokosawa, 2017); biological motion (Mayer, Vuong, & Thornton, 2017); and the cognitive effects of mobile phone use (Ito & Kawahara, 2017). They also cover a range of search behaviors, including tactile exploration (Kaga et al, 2017), vision-guided touch responses (Jóhannesson et al, 2017), oculomotor behavior (Ueda et al, 2017), in addition to standard button-press reaction time (RT) and accuracy measures.…”

“…They also cover a range of search behaviors, including tactile exploration (Kaga et al, 2017), vision-guided touch responses (Jóhannesson et al, 2017), oculomotor behavior (Ueda et al, 2017), in addition to standard button-press reaction time (RT) and accuracy measures. Some studies focus on fundamental, basic science questions (Higuchi & Saiki, 2017;Makovski, 2017), others are concerned with "use-inspired" questions (Horowitz, 2017;Ito & Kawahara, 2017). Nevertheless, all of the papers here share a common characteristic: using rigorous experimental paradigms and data-analysis techniques to understand fundamental properties of human search behavior.…”