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Combined effects of expectations and visual uncertainty upon detection and identification of a target in the fog

Overview of attention for article published in Cognitive Processing, July 2015
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Title
Combined effects of expectations and visual uncertainty upon detection and identification of a target in the fog
Published in
Cognitive Processing, July 2015
DOI 10.1007/s10339-015-0673-1
Pubmed ID
Authors

Boris Quétard, Jean-Charles Quinton, Michèle Colomb, Giovanni Pezzulo, Laura Barca, Marie Izaute, Owen Kevin Appadoo, Martial Mermillod

Abstract

Detecting a pedestrian while driving in the fog is one situation where the prior expectation about the target presence is integrated with the noisy visual input. We focus on how these sources of information influence the oculomotor behavior and are integrated within an underlying decision-making process. The participants had to judge whether high-/low-density fog scenes displayed on a computer screen contained a pedestrian or a deer by executing a mouse movement toward the response button (mouse-tracking). A variable road sign was added on the scene to manipulate expectations about target identity. We then analyzed the timing and amplitude of the deviation of mouse trajectories toward the incorrect response and, using an eye tracker, the detection time (before fixating the target) and the identification time (fixations on the target). Results revealed that expectation of the correct target results in earlier decisions with less deviation toward the alternative response, this effect being partially explained by the facilitation of target identification.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 16%
Researcher 7 16%
Student > Bachelor 5 12%
Professor > Associate Professor 3 7%
Professor 3 7%
Other 11 26%
Unknown 7 16%
Readers by discipline Count As %
Psychology 12 28%
Engineering 5 12%
Agricultural and Biological Sciences 4 9%
Neuroscience 3 7%
Nursing and Health Professions 3 7%
Other 7 16%
Unknown 9 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 July 2015.
All research outputs
#20,290,425
of 22,826,360 outputs
Outputs from Cognitive Processing
#294
of 338 outputs
Outputs of similar age
#219,928
of 263,290 outputs
Outputs of similar age from Cognitive Processing
#17
of 18 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 338 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 263,290 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.