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Fast and Conspicuous? Quantifying Salience With the Theory of Visual Attention.

Krüger A, Tünnermann J, Scharlau I - Adv Cogn Psychol (2016)

Bottom Line: Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects.With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material.A 4th experiment substantiates its applicability to the luminance dimension.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Arts and Humanities, Paderborn University.

ABSTRACT
Particular differences between an object and its surrounding cause salience, guide attention, and improve performance in various tasks. While much research has been dedicated to identifying which feature dimensions contribute to salience, much less regard has been paid to the quantitative strength of the salience caused by feature differences. Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects. We propose Bundesen's Theory of Visual Attention (TVA) as a theoretical basis for measuring salience and introduce an empirical and modeling approach to link this theory to data retrieved from temporal-order judgments. With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material. Three experiments with orientation pop-out displays demonstrate the feasibility of the method. A 4th experiment substantiates its applicability to the luminance dimension.

No MeSH data available.


Related in: MedlinePlus

Estimated attentional weights (ω) for the probe stimuli of Experiment 1,salience condition (ωsp = weight for the salient probe) inblue and neutral (ωsp = weight for the neutral probe) in red.The weights for the reference stimuli are 1 minus the weight of therespective probe.
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Figure 5: Estimated attentional weights (ω) for the probe stimuli of Experiment 1,salience condition (ωsp = weight for the salient probe) inblue and neutral (ωsp = weight for the neutral probe) in red.The weights for the reference stimuli are 1 minus the weight of therespective probe.

Mentions: The most interesting variables in the hierarchical Bayesian graphical model areon the group level because they allow us to compare the difference between thesalience and neutral condition. The relation between the weight forTprobe in the salience conditionωsp and its counterpart in the neutral conditionωnp shows if salience has an influence on attentionparameters (see Figure 5). The parameterdistribution for the weights are depicted in Figure 5. The parameter estimations show thatwsp = .507 and ωnp = .516differ only slightly. Interestingly, the value .5 is not among the 95% of themost probable parameters for ωnp—that is, attention isnot distributed equally across the two targets in the neutral condition. Becauseall elements were equally salient in this condition, visual properties cannot bethe cause of the higher attentional weight forTprobe. The temporal properties, however, offeran explanation: Tprobe was always shown 150 ms afterdisplay onset. This fixed interval made it predictable. In order to measure theeffect of salience unbiased by that of temporal expectation, we subtracted thedeviation from the expected neutral weight .5 in the ωnpparameter from the ωsp parameter. The corrected weight isωspclean = .493. The correction shifts the weight of the saliencecondition ωsp in the opposite of the expected direction, whichwould be an increased weight for the salient stimulus. As explained earlier, theeffect is small and hence again, ωnp and ωspclean differed only slightly.


Fast and Conspicuous? Quantifying Salience With the Theory of Visual Attention.

Krüger A, Tünnermann J, Scharlau I - Adv Cogn Psychol (2016)

Estimated attentional weights (ω) for the probe stimuli of Experiment 1,salience condition (ωsp = weight for the salient probe) inblue and neutral (ωsp = weight for the neutral probe) in red.The weights for the reference stimuli are 1 minus the weight of therespective probe.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862317&req=5

Figure 5: Estimated attentional weights (ω) for the probe stimuli of Experiment 1,salience condition (ωsp = weight for the salient probe) inblue and neutral (ωsp = weight for the neutral probe) in red.The weights for the reference stimuli are 1 minus the weight of therespective probe.
Mentions: The most interesting variables in the hierarchical Bayesian graphical model areon the group level because they allow us to compare the difference between thesalience and neutral condition. The relation between the weight forTprobe in the salience conditionωsp and its counterpart in the neutral conditionωnp shows if salience has an influence on attentionparameters (see Figure 5). The parameterdistribution for the weights are depicted in Figure 5. The parameter estimations show thatwsp = .507 and ωnp = .516differ only slightly. Interestingly, the value .5 is not among the 95% of themost probable parameters for ωnp—that is, attention isnot distributed equally across the two targets in the neutral condition. Becauseall elements were equally salient in this condition, visual properties cannot bethe cause of the higher attentional weight forTprobe. The temporal properties, however, offeran explanation: Tprobe was always shown 150 ms afterdisplay onset. This fixed interval made it predictable. In order to measure theeffect of salience unbiased by that of temporal expectation, we subtracted thedeviation from the expected neutral weight .5 in the ωnpparameter from the ωsp parameter. The corrected weight isωspclean = .493. The correction shifts the weight of the saliencecondition ωsp in the opposite of the expected direction, whichwould be an increased weight for the salient stimulus. As explained earlier, theeffect is small and hence again, ωnp and ωspclean differed only slightly.

Bottom Line: Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects.With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material.A 4th experiment substantiates its applicability to the luminance dimension.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Arts and Humanities, Paderborn University.

ABSTRACT
Particular differences between an object and its surrounding cause salience, guide attention, and improve performance in various tasks. While much research has been dedicated to identifying which feature dimensions contribute to salience, much less regard has been paid to the quantitative strength of the salience caused by feature differences. Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects. We propose Bundesen's Theory of Visual Attention (TVA) as a theoretical basis for measuring salience and introduce an empirical and modeling approach to link this theory to data retrieved from temporal-order judgments. With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material. Three experiments with orientation pop-out displays demonstrate the feasibility of the method. A 4th experiment substantiates its applicability to the luminance dimension.

No MeSH data available.


Related in: MedlinePlus