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Of all publications in the section: 6
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Article
Kristjansson A. Visual Cognition. 2019. Vol. 27. No. 5-8. P. 595-608.

It is commonly assumed that we find targets faster if we know what they look like. Such top-down guidance plays an important role in theories of visual attention. A recent provocative proposal is that effects attributed to top-down guidance instead reflect attentional priming.

Added: May 29, 2020
Article
Kristjansson A., Asgeirsson A. G. Visual Cognition. 2019. Vol. 27. No. 5-8. P. 595-608.

It is commonly assumed that we find targets faster if we know what they look like. Such top-down guidance plays an important role in theories of visual attention. A recent provocative proposal is that effects attributed to top-down guidance instead reflect attentional priming. Theeuwes and van der Burg [(2011). On the limits of top-down control of visual selection. Attention, Perception, and Psychophysics73(7), 2092–2103. doi:10.3758/s13414-011-0176-9] found that observers could not use top-down set to ignore irrelevant singletons but when priming was maximal such distractors could be successfully ignored, suggesting that feature-based top-down selection is impossible but that this can be overcome when a target feature is constant on consecutive trials. Using a variant of their task, we found that participants were unable to ignore a known colour singleton, but also that repetition priming did not help participants ignore the salient distractor. Our results stand in direct contrast to the results of Theeuwes and van der Burg and cast doubt upon the claim that priming effects can explain top-down effects in visual search. Notably the priming effects we do see are mostly episodic rather than featural which means that they cannot serve as a feature-based selection mechanism.

Added: Jun 24, 2020
Article
Utochkin I. S. Visual Cognition. 2011. Vol. 19. No. 8. P. 1063-1088.

Three experiments examined spatial allocation of attention during active search for visual changes. In all experiments, there were three conditions of change location related to a centre of interest: (1) Central (most attended location itself), (2) near, and (3) far marginal change. In Experiment 1, participants showed the slowest search and the largest number of undetected changes in near condition. Moreover, they misidentified near changes more frequently than central and far ones. In Experiment 2, participants had to search for marginal changes in the presence of a once noticed central change that summoned additional attention to a central location. It resulted in further search slowing for near changes. In Experiment 3, participants searched for one of two concurrent marginal changes in the presence of a central one. They detected far changes about 2.3 times more frequently than near ones. Taken together, these results support the notion of «dead zone of attention» surrounding attentional focus. Several speculations about the nature of dead zone are discussed.

Added: Jan 20, 2013
Article
Kuskova V., Chastain G., Cheal M. Visual Cognition. 2002. No. 9(3). P. 355-381.
Added: Sep 22, 2011
Article
Thornton I. M., de’Sperati C., Kristjansson A. Visual Cognition. 2019. Vol. 27. No. 5-8. P. 626-648.

In previous studies, we have used an iPad task to explore how humans “forage” through static displays containing multiple targets from two categories. When demands on attention were increased, foraging patterns tended to shift from random category selection to exhaustive category selection. Here, we used the same task on a vertically oriented touch-screen. In separate blocks, static or dynamic target items were selected using different modalities, specifically: (a) mouse (b) touchscreen or (c) infrared hand tracker. Although the different selection modalities varied considerably in terms of familiarity and difficulty of use, there was a minimal effect on the patterns of foraging. While there was a consistent reduction in the number of category switches with increased attentional load, the tendency to use exhaustive runs was much reduced, particularly with dynamic displays. We suggest that this pattern is a consequence of generally slowed response times. These findings indicate that in addition to capacity limits, temporal constraints are likely to be an important determinant of foraging patterns in humans. We introduce the term “foraging tempo” to capture this latter notion and to emphasize the probable role played by the overall pace of the regular, repetitive selections required during multi-target search tasks.

Added: Jun 24, 2020
Article
Kristjansson A. Visual Cognition. 2019. Vol. 27. No. 5-8. P. 626-648.

In previous studies, we have used an iPad task to explore how humans “forage” through static displays containing multiple targets from two categories. When demands on attention were increased, foraging patterns tended to shift from random category selection to exhaustive category selection. Here, we used the same task on a vertically oriented touch-screen. In separate blocks, static or dynamic target items were selected using different modalities, specifically: (a) mouse (b) touchscreen or (c) infrared hand tracker. Although the different selection modalities varied considerably in terms of familiarity and difficulty of use, there was a minimal effect on the patterns of foraging. While there was a consistent reduction in the number of category switches with increased attentional load, the tendency to use exhaustive runs was much reduced, particularly with dynamic displays. We suggest that this pattern is a consequence of generally slowed response times. These findings indicate that in addition to capacity limits, temporal constraints are likely to be an important determinant of foraging patterns in humans. We introduce the term “foraging tempo” to capture this latter notion and to emphasize the probable role played by the overall pace of the regular, repetitive selections required during multi-target search tasks.

Added: May 30, 2020