Search termination when the target is absent: The prevalence of coarse processing and its intertrial influence.

Cho, Jieun; Chong, Sang Chul

doi:10.1037/xhp0000686

Cited by 5 publications

(7 citation statements)

References 75 publications

(143 reference statements)

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“…Alternatively, one can propose that an internal signal accumulates toward some quitting threshold and that search is terminated if that threshold is reached (Chun & Wolfe, 1996;Wolfe & Van Wert, 2010). Some models have aspects of both processes (Hong, 2005) and there are other approaches, for example, proposing a role for coarse to fine processing (Cho & Chong, 2019).…”

Section: Search Terminationmentioning

confidence: 99%

Guided Search 6.0: An updated model of visual search

2021

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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.

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Section: Search Terminationmentioning

confidence: 99%

Guided Search 6.0: An updated model of visual search

2021

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“…In this study, we examine whether this influence of ensemble encoding on visual search performance changes between the central and peripheral visual fields. More important, previous studies have typically focused on the effect of target–distractor discriminability ( Duncan & Humphreys, 1989 , Palmer, Verghese & Pavel, 2000 ), segmentability of distractor features ( Utochkin & Yurevich, 2016 ; Cho & Chong, 2019 ), or of summary statistics ( Rosenholtz et al 2012 ) on visual search performance. In contrast, our methodology allows us to investigate the effect of the shape of the distractor distribution while keeping all those other factors as constant as possible.…”

Section: Introductionmentioning

confidence: 99%

Encoding perceptual ensembles during visual search in peripheral vision

Tanrıkulu

Chetverikov²,

Kristjánsson

2020

Journal of Vision

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Observers can learn complex statistical properties of visual ensembles, such as their probability distributions. Even though ensemble encoding is considered critical for peripheral vision, whether observers learn such distributions in the periphery has not been studied. Here, we used a visual search task to investigate how the shape of distractor distributions influences search performance and ensemble encoding in peripheral and central vision. Observers looked for an oddly oriented bar among distractors taken from either uniform or Gaussian orientation distributions with the same mean and range. The search arrays were either presented in the foveal or peripheral visual fields. The repetition and role reversal effects on search times revealed observers' internal model of distractor distributions. Our results showed that the shape of the distractor distribution influenced search times only in foveal, but not in peripheral search. However, role reversal effects revealed that the shape of the distractor distribution could be encoded peripherally depending on the interitem spacing in the search array. Our results suggest that, although peripheral vision might rely heavily on summary statistical representations of feature distributions, it can also encode information about the distributions themselves.

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“…What is more likely, we believe, is that candidate heterogeneity changes the quitting rule for target absent trials (likely a nonvisual process), inviting more revisitations (e.g., candidate heterogeneity might disrupt the memory representations of what items or locations have been already visited and rejected). Note that quitting rules in target-absent trials are notoriously difficult to understand, let alone predict (Cho & Chong, 2019; Chun & Wolfe, 1996; Fleck et al, 2010; Mitroff et al, 2015; Wolfe & Van Wert, 2010).…”

Section: Discussionmentioning

confidence: 99%

Prioritization in visual attention does not work the way you think it does.

Ng¹,

Buetti²,

Patel³

et al. 2021

Journal of Experimental Psychology: Human Perception and Perfor

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A common assumption in attention theories is that attention prioritizes search items based on their similarity to the target. Here, we tested this assumption and found it wanting. Observers searched through displays containing candidates (distractors that cannot be confidently differentiated from the target by peripheral vision) and lures (distractors that can be). Candidates had high or low similarity to the target. Search displays were either candidate-homogeneous (all items of same similarity) or candidate-heterogeneous (equal numbers of each similarity). Response times to candidate-heterogeneous displays were equivalent to the average of high- and low-similarity displays, suggesting that attention was allocated randomly, rather than toward the high-similarity candidates first. Lures added a response time cost that was independent of the candidates, suggesting they were rejected prior to candidates being inspected. These results suggest a “reverse” prioritization process: Distributed attention discards least target-similar items first, while focused spatial attention is randomly directed to target-similar items.

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Search termination when the target is absent: The prevalence of coarse processing and its intertrial influence.

Cited by 5 publications

References 75 publications

Guided Search 6.0: An updated model of visual search

Guided Search 6.0: An updated model of visual search

Encoding perceptual ensembles during visual search in peripheral vision

Prioritization in visual attention does not work the way you think it does.

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