Attentional capture by size singletons is determined by top‐down search goals

Kiss, Mónika; Eimer, Martin

doi:10.1111/j.1469-8986.2010.01145.x

Cited by 42 publications

(51 citation statements)

References 15 publications

(24 reference statements)

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“…The effect of physical size is consistent with previous work showing that larger items capture attention more than do smaller items (Proulx, 2010;Proulx & Egeth, 2008), although finding this effect was surprising, because we expected participants to adopt a top-down strategy to attend to numerical rather than physical size (Kiss & Eimer, 2011). In this context, the interaction between physical size and display size was illuminating.…”

Section: Discussionsupporting

confidence: 78%

“…Apparently, the participants in Experiment 3 but not Experiment 4 noticed that the visually salient item was always the target. Participants' failure to rely on the salience of the target's physical size in Experiment 4 lends support to the claim that physical size differences require a combination of bottom-up and top-down processing to capture attention (Kiss & Eimer, 2011). However, the results from Experiment 1, in which search was faster for dense (nine-digit) displays than for less dense (seven-digit) displays, suggests that sufficiently salient physical size differences can eliminate the need for topdown attentional settings.…”

Section: Discussionmentioning

confidence: 80%

“…Although physical-size singletons have been shown to capture attention (Proulx, 2010;Proulx & Egeth, 2008), this seems to be attributable to the combination of bottom-up salience and top-down task settings (Kiss & Eimer, 2011). Thus, we hypothesized that the physicalsize singleton target should elicit bottom-up processing in Experiment 1, but in Experiment 2 it should elicit both bottom-up and top-down processing.…”

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confidence: 99%

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Bottom-up and top-down attentional contributions to the size congruity effect

Sobel

Puri

Faulkenberry

2016

Atten Percept Psychophys

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The size congruity effect refers to the interaction between the numerical and physical (i.e., font) sizes of digits in a numerical (or physical) magnitude selection task. Although various accounts of the size congruity effect have attributed this interaction to either an early representational stage or a late decision stage, only Risko, Maloney, and Fugelsang (Attention, Perception, & Psychophysics, 75, 1137-1147) have asserted a central role for attention. In the present study, we used a visual search paradigm to further study the role of attention in the size congruity effect. In Experiments 1 and 2, we showed that manipulating top-down attention (via the task instructions) had a significant impact on the size congruity effect. The interaction between numerical and physical size was larger for numerical size comparison (Exp. 1) than for physical size comparison (Exp. 2). In the remaining experiments, we boosted the feature salience by using a unique target color (Exp. 3) or by increasing the display density by using threedigit numerals (Exps. 4 and 5). As expected, a color singleton target abolished the size congruity effect. Searching for threedigit targets based on numerical size (Exp. 4) resulted in a large size congruity effect, but search based on physical size (Exp. 5) abolished the effect. Our results reveal a substantial role for top-down attention in the size congruity effect, which we interpreted as support for a shared-decision account.

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Section: Discussionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 80%

mentioning

confidence: 99%

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Bottom-up and top-down attentional contributions to the size congruity effect

Sobel

Puri

Faulkenberry

2016

Atten Percept Psychophys

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“…Trials in which the target feature from the previous trial was directly repeated were classified as repeat trials and served as a baseline. Note that the search displays were identical across the different conditions (repeat, feature change, dimension change), so that differences between conditions cannot be attributed to physical differences between the targets (e.g., Kiss & Eimer, 2011).…”

Section: Methodsmentioning

confidence: 99%

Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI

2014

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Publisher's copyright statement: NOTICE: this is the author's version of a work that was accepted for publication in NeuroImage. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be re ected in this document. Changes may have been made to this work since it was submitted for publication. A de nitive version was subsequently published in NeuroImage, 102, Part 2, 15 November 2014, 10.1016/j.neuroimage.2014.08.058. Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractIn visual search, responses are slowed, from one trial to the next, both when the target dimension changes (e.g., from a color target to a size target) and when the target feature changes (e.g., from a red target to a green target) relative to being repeated across trials. The present study examined whether such feature and dimension switch costs can be attributed to the same underlying mechanism(s). Contrary to this contention, an EEG study showed that feature changes influenced visual selection of the target (i.e., delayed N2pc onset), whereas dimension changes influenced the later process of response selection (i.e., delayed s-LRP onset). An fMRI study provided convergent evidence for the two-system view: Compared with repetitions, feature changes led to increased activation in the occipital cortex, and superior and inferior parietal lobules, which have been implicated in spatial attention. By contrast, dimension changes led to activation of a frontoposterior network that is primarily linked with response selection (i.e., pre-motor cortex, supplementary motor area and frontal areas). Taken together, the results suggest that feature and dimension switch costs are based on different processes. Specifically, whereas target feature changes delay attention shifts to the target, target dimension changes interfere with later response selection operations.

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“…Attention can be captured in a bottom-up fashion by the appearance of salient items (Theeuwes, 1991(Theeuwes, , 1992; this has obvious evolutionary advantages, allowing quick reactions to potentially dangerous events, but the accompanying distractibility may impede the performance of goal-directed tasks. Crucially, then, this process interacts with and is influenced by top-down cognitive control, which attempts to wrest attention away from salient but irrelevant aspects of the environment in order to focus on achieving specific goals (Folk and Remington, 1998;Folk et al, 1992;Kiss and Eimer, 2011;Muller et al, 2009;Proulx and Egeth, 2006). Attentional control is largely achieved by the biased selection of percepts that match some internal representation; for example, when searching for a yellow apple in a supermarket, items that are the wrong colour (e.g.…”

Section: Introductionmentioning

confidence: 99%

Functional connectivity between ventral and dorsal frontoparietal networks underlies stimulus-driven and working memory-driven sources of visual distraction

Greene

Soto

2014

NeuroImage

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Publication informationNeurolmage, 84 (2014): 290-298Publisher Elsevier Item record/more information http://hdl.handle.net/10197/6144 Publisher's statementThis is the author's version of a work that was accepted for publication in Neurolmage. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Neurolmage (VOL 84, ISSUE 2014, (2014

show abstract

Attentional capture by size singletons is determined by top‐down search goals

Cited by 42 publications

References 15 publications

Bottom-up and top-down attentional contributions to the size congruity effect

Bottom-up and top-down attentional contributions to the size congruity effect

Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI

Functional connectivity between ventral and dorsal frontoparietal networks underlies stimulus-driven and working memory-driven sources of visual distraction

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