Guided Search 6.0: An updated model of visual search

Abstract

This paper describes Guided Search 6.0 (GS6), a revised model of visual search. When we encounter a scene, we can see something everywhere. However, we cannot recognize more than a few items at a time. Attention is used to select items so that their features can be "bound" into recognizable objects. Attention is "guided" so that items can be processed in an intelligent order. In GS6, this guidance comes from five sources of preattentive information: (1) top-down and (2) bottom-up feature guidance, (3) prior history (e.g., priming), (4) reward, and (5) scene syntax and semantics. These sources are combined into a spatial "priority map," a dynamic attentional landscape that evolves over the course of search. Selective attention is guided to the most active location in the priority map approximately 20 times per second. Guidance will not be uniform across the visual field. It will favor items near the point of fixation. Three types of functional visual field (FVFs) describe the nature of these foveal biases. There is a resolution FVF, an FVF governing exploratory eye movements, and an FVF governing covert deployments of attention. To be identified as targets or rejected as distractors, items must be compared to target templates held in memory. The binding and recognition of an attended object is modeled as a diffusion process taking > 150 ms/item. Since selection occurs more frequently than that, it follows that multiple items are undergoing recognition at the same time, though asynchronously, making GS6 a hybrid of serial and parallel processes. In GS6, if a target is not found, search terminates when an accumulating quitting signal reaches a threshold. Setting of that threshold is adaptive, allowing feedback about performance to shape subsequent searches. Simulation shows that the combination of asynchronous diffusion and a quitting signal can produce the basic patterns of response time and error data from a range of search experiments.

Massive Effects of Saliency on Information Processing in Visual Working Memory

“…How saliencies of multiple relevant objects interact has-to the best of our knowledge-not yet been systematically examined, and an observation of an effect of relative saliency is therefore new not only for the VWM community but also for the visual cognition community in general. Many theories of visual search (e.g., Duncan & Humphreys, 1989;Fecteau & Munoz, 2006;Liesefeld & Müller, 2019b, 2021Wolfe, 2021) assume a preattentive spatial representation of the visual scene coding for relevance at each location and informing a second, attentive-processing stage. This assumption is needed to explain how second-stage focal attention can be allocated to the most promising objects in view without analyzing each object in detail first.…”

How do we measure attention? Using factor analysis to establish construct validity of neuropsychological tests

“…Visual search has played a central role in attentional theory for decades (Schneider & Shiffrin, 1977;Treisman & Gelade, 1980). Spatial configuration search, where targets are distinguished from distractors only by the internal arrangement of components, is widely held to index serial shifts of covert attention (Bricolo et al, 2002;Wolfe, 2021;Woodman & Luck, 1999). Here we employed the widely used spatial configuration search for T-shaped targets among L-shaped distractors.…”

A Kiosk Station for the Assessment of Multiple Cognitive Domains and Cognitive Enrichment of Monkeys

“…It also quantifies the speed of processing (baseline search speed) that is a known behavioral marker of aging. Visual search tasks are easily extended to obtain indices for multiple other domains including, for example, indices of perceptual interference by varying the target-distractor similarity or to obtain indices of reward-based capturing of attention by varying the expected value of distractors (Wolfe and Horowitz, 2017;Wolfe, 2021).…”