What attributes guide the deployment of visual attention and how do they do it?

Wolfe, Jeremy M.; Horowitz, Todd S.

doi:10.1038/nrn1411

Cited by 1,504 publications

(1,242 citation statements)

References 103 publications

Supporting

Mentioning

1,159

Contrasting

Unclassified

Order By: Relevance

“…Variation in stimulus image properties can be seen in the histograms themselves (parts c-h and m-r) as well as in the statistical comparisons of video image property profiles (parts i-j and s-t, compared by two-sample Kolmogorov-Smirnov tests). These data underscore the notion that “eyes” are a semantic content category rather than a singular stimulus image property 28 , a notion consistent with research distinguishing stimulus-driven or “bottom-up” 43–47 processes in visual saliency from those that are goal-directed or “top-down” 26,27,48–51 .…”

Section: Methodssupporting

confidence: 79%

Infant viewing of social scenes is under genetic control and is atypical in autism

Constantino

Kennon-McGill

Weichselbaum

et al. 2017

Nature

246

254

View full text Add to dashboard Cite

Long before infants reach, crawl, or walk, they explore the world by looking: they look to learn and to engage1, giving preferential attention to social stimuli including faces2, face-like stimuli3, and biological motion4. This capacity—social visual engagement—shapes typical infant development from birth5 and is pathognomonically impaired in children affected by autism6. Here we show that variation in viewing of social scenes—including levels of preferential attention and the timing, direction, and targeting of individual eye movements—is strongly influenced by genetic factors, with effects directly traceable to the active seeking of social information7. In a series of eye-tracking experiments conducted with 338 toddlers—including 166 epidemiologically-ascertained twins, 88 non-twins with autism, and 84 singleton controls—we find high monozygotic twin-twin concordance (0.91) and relatively low dizygotic concordance (0.35). Moreover, the measures that are most highly heritable, preferential attention to eye and mouth regions of the face, are also those that are differentially diminished in children with autism (Χ2=64.03, P<0.0001). These results—which implicate social visual engagement as a neurodevelopmental endophenotype—not only for autism, but for population-wide variation in social-information-seeking8—reveal a means of human biological niche construction, with phenotypic differences emerging from the interaction of individual genotypes with early life experience7.

show abstract

Section: Methodssupporting

confidence: 79%

Infant viewing of social scenes is under genetic control and is atypical in autism

Constantino

Kennon-McGill

Weichselbaum

et al. 2017

Nature

246

254

View full text Add to dashboard Cite

show abstract

“…Given this limited capacity, it is broadly held that signals compete in order to achieve detailed analysis (Desimone & Duncan, 1995;Knudsen, 2007;Rescorla & Wagner, 1972). Adding to the complexity of the problem, there are several sources of bias influencing the outcome of this competitive process, originating from the physical properties of the world (Itti & Koch, 2001;Wolfe & Horowitz, 2004), as well as a variety of internal states .…”

Section: You May Infringe the Author's Moral Rights If Youmentioning

confidence: 99%

Automaticity and cognitive control in the learned predictiveness effect.

Shone¹,

Harris²,

Livesey³

2015

Journal of Experimental Psychology: Animal Learning and Cogniti

View full text Add to dashboard Cite

In novel contexts, learning is biased toward cues previously experienced as predictive compared with cues previously experienced as nonpredictive. This is known as learned predictiveness. A recent finding has shown that instructions issued about the causal status of cues influences the expression of learned predictiveness, suggesting that controlled, volitional processes play a role in this effect. Three experiments are reported further investigating the effects of instructional manipulations on learned predictiveness. Experiment 1 confirms the influence of inferential processes, extending previous work to suggest that instructions affect associative memory as well as causal reasoning. Experiments 2 and 3 used a procedure designed to tease apart inferential and automatic contributions to the bias by presenting instructed causes that were previously predictive and previously nonpredictive. The results demonstrate that the prior predictiveness of cues influences subsequent learning over and above the effect of explicit instruction. However, it appears that the relationship between explicit instruction and predictive history is interactive rather than additive. Potential explanations for this interactivity are discussed.

show abstract

“…The effect of target‐distractor similarity on visual search performance has been demonstrated in a great number of studies (e.g., Duncan & Humphreys, 1989; Wolfe & Horowitz, 2004). We hypothesized that target‐distractor similarity modulates the impact of eye‐controlled highlighting by affecting the difficulty of the search task.…”

Section: Discussionmentioning

confidence: 99%

“…For example, Duncan and Humphreys (1989) argued that the extent of similarity between targets and distractors plays a major role in visual search performance. Wolfe and Horowitz (2004) showed that the ratio of distractor‐target saliency increases as the target shifts away from the distractors in the colour space, suggesting the crucial role of similarity in a visual search task. Using closed structure materials, Han and Cao (2010) findings were also consistent with the stimuli similarity hypothesis.…”

mentioning

confidence: 99%

The applicability of eye‐controlled highlighting to the field of visual searching

Wang

Sun

Liu

et al. 2018

Australian Journal of Psychology

View full text Add to dashboard Cite

ObjectiveWith the increasing amount of information presented on current human–computer interfaces, eye‐controlled highlighting has been proposed, as a new display technique, to optimise users’ task performances. However, it is unknown to what extent the eye‐controlled highlighting display facilitates visual search performance. The current study examined the facilitative effect of eye‐controlled highlighting display technique on visual search with two major attributes of visual stimuli: stimulus type and the visual similarity between targets and distractors.MethodIn Experiment 1, we used digits and Chinese words as materials to explore the generalisation of the facilitative effect of the eye‐controlled highlighting. In Experiment 2, we used Chinese words to examine the effect of target‐distractor similarity on the facilitation of eye‐controlled highlighting display.ResultsThe eye‐controlling highlighting display improved visual search performance when words were used as searching target and when the target‐distractor similarity was high. No facilitative effect was found when digits were used as searching target or target‐distractor similarity was low.ConclusionsThe effectiveness of the eye‐controlled highlighting on a visual task was influenced by both stimulus type and target‐distractor similarity. These findings provided guidelines for modern interface design with eye‐based displays implemented.

show abstract

What attributes guide the deployment of visual attention and how do they do it?

Cited by 1,504 publications

References 103 publications

Infant viewing of social scenes is under genetic control and is atypical in autism

Infant viewing of social scenes is under genetic control and is atypical in autism

Automaticity and cognitive control in the learned predictiveness effect.

The applicability of eye‐controlled highlighting to the field of visual searching

Contact Info

Product

Resources

About