Parallel and serial processes in visual search.

Thornton, Thomas L.; Gilden, David L.

doi:10.1037/0033-295x.114.1.71

Cited by 140 publications

(190 citation statements)

References 94 publications

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“…Thus, models are primarily intended to describe the processes that mediate selection, whether these are largely top-down or bottom-up, or whether search is serial or parallel in nature, or hybridized between the two (Cave, 1999;Grossberg, Mingolla, & Ross, 1994;Hoffman, 1979;Humphreys & Muller, 1993;Itti & Koch, 2000;Thornton & Gilden, 2007;Treisman & Gelade, 1980;Tsotsos et al, 1995;Verghese, 2001;Wolfe, 1994;Wolfe, Cave, & Franzel, 1989).…”

Section: Discussionmentioning

confidence: 99%

Looming motion primes the visuomotor system.

Skarratt¹,

Gellatly²,

Cole³

et al. 2014

Journal of Experimental Psychology: Human Perception and Perfor

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A wealth of evidence now shows that human and animal observers display greater sensitivity to objects that move toward them than to objects that remain static or move away. Increased sensitivity in humans is often evidenced by reaction times that increase in rank order from looming, to receding, to static targets. However, it is not clear whether the processing advantage enjoyed by looming motion is mediated by the attention system or the motor system. The present study investigated this by first examining whether sensitivity is to looming motion per se or to certain monocular or binocular cues that constitute stereoscopic motion in depth. None of the cues accounted for the looming advantage. A perceptual measure was then used to examine performance with minimal involvement of the motor system. Results showed that looming and receding motion were equivalent in attracting attention, suggesting that the looming advantage is indeed mediated by the motor system. These findings suggest that although motion itself is sufficient for attentional capture, motion direction can prime motor responses.

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Section: Discussionmentioning

confidence: 99%

Looming motion primes the visuomotor system.

Skarratt¹,

Gellatly²,

Cole³

et al. 2014

Journal of Experimental Psychology: Human Perception and Perfor

View full text Add to dashboard Cite

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“…Other work has modeled search termination (Chun & Wolfe, 1996;Cousineau & Shiffrin, 2004;Hong, 2005;Zenger & Fahle, 1997). We are currently working on the details of a model that combines those two decisions into a single RT model (see also Thornton & Gilden, 2007). Figure 19 presents the results of a simulation embodying the three assumptions laid out above: errors are based on criterion position; criterion position is based on an effort to equate miss and false alarm numbers; and the underlying ROC has a slope of about 0.6.…”

Section: Assumption One Changes In Target Prevalence Cause Changes Imentioning

confidence: 99%

Low target prevalence is a stubborn source of errors in visual search tasks.

Wolfe

Horowitz

Wert

et al. 2007

Journal of Experimental Psychology: General

340

532

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In visual search tasks, observers look for targets in displays containing distractors. Likelihood that targets will be missed varies with target prevalence, the frequency with which targets are presented across trials. Miss error rates are much higher at low target prevalence (1-2%) than at high prevalence (50%). Unfortunately, low prevalence is characteristic of important search tasks like airport security and medical screening where miss errors are dangerous. A series of experiments show this prevalence effect is very robust. In signal detection terms, the prevalence effect can be explained as a criterion shift and not a change in sensitivity. Several efforts to induce observers to adopt a better criterion fail. However, a regime of brief retraining periods with high prevalence and full feedback allows observers to hold a good criterion during periods of low prevalence with no feedback.

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“…To date, neither of these two theories has been unequivocally disproved. Overall performance in the search task itself is not directly informative, because both theories predict an increase in RT with the number of distracters (11,12). One alternative is to use briefly flashed probes to test for the deployment of attention at a specific location and time.…”

mentioning

confidence: 99%

Attention searches nonuniformly in space and in time

Dugué

McLelland

Lajous

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Difficult search tasks are known to involve attentional resources, but the spatiotemporal behavior of attention remains unknown. Are multiple search targets processed in sequence or in parallel? We developed an innovative methodology to solve this notoriously difficult problem. Observers performed a difficult search task during which two probes were flashed at varying delays. Performance in reporting probes at each location was considered a measure of attentional deployment. By solving a second-degree equation, we determined the probability of probe report at the most and least attended probe locations on each trial. Because these values differed significantly, we conclude that attention was focused on one stimulus or subgroup of stimuli at a time, and not divided uniformly among all search stimuli. Furthermore, this deployment was modulated periodically over time at ∼7 Hz. These results provide evidence for a nonuniform spatiotemporal deployment of attention during difficult search.V isual search tasks (e.g., to find a target embedded among similar looking distracters) have long been used to investigate the deployment of attention (1-6). Certain tasks are performed "efficiently," in which case the search time and accuracy are independent of the number of distracters. Other tasks are more difficult, or "inefficient," characterized by an increase in reaction times (RTs) and/or a decrease in accuracy with the number of distracting elements, a result typically attributed to the need to allocate attention (4-7). For more than 30 y now, since the pioneering study of Treisman and Gelade in 1980 (4), two opposing theories of attention deployment during difficult search have persisted. Attention could either be allocated nonuniformly to the stimuli, such that in some cases it would switch sequentially from one stimulus (or group of stimuli) to another (4, 5), or be divided uniformly to process all of the stimuli in parallel, but with a drop in efficiency for increasing distractor numbers (2,(8)(9)(10). To date, neither of these two theories has been unequivocally disproved. Overall performance in the search task itself is not directly informative, because both theories predict an increase in RT with the number of distracters (11,12). One alternative is to use briefly flashed probes to test for the deployment of attention at a specific location and time. With two probes, it should be possible to differentiate parallel and sequential processing strategies: The strict parallel theory predicts that both probes should receive equal amounts of attention, whereas the sequential theory predicts that one of the probes will receive more attention than the other. Of course, the most attended probe may not be the same one on every trial, but a simple mathematical manipulation, the solution of a quadratic equation, allows us to access this information despite the need to average performance over trials.In recent years, a second, related, debate has arisen in the literature concerning the temporal behavior of attention. It has been p...

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Parallel and serial processes in visual search.

Cited by 140 publications

References 94 publications

Looming motion primes the visuomotor system.

Looming motion primes the visuomotor system.

Low target prevalence is a stubborn source of errors in visual search tasks.

Attention searches nonuniformly in space and in time

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