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Fixed-target efficient search has logarithmic efficiency with and without eye movements

Overview of attention for article published in Attention, Perception, & Psychophysics, July 2018
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Title
Fixed-target efficient search has logarithmic efficiency with and without eye movements
Published in
Attention, Perception, & Psychophysics, July 2018
DOI 10.3758/s13414-018-1561-4
Pubmed ID
Authors

Gavin Jun Peng Ng, Alejandro Lleras, Simona Buetti

Abstract

Stage 1 processing in visual search (e.g., efficient search) has long been thought to be unaffected by factors such as set size or lure-distractor similarity (or at least to be only minimally affected). Recent research from Buetti, Cronin, Madison, Wang, and Lleras (Journal of Experimental Psychology: General, 145, 672-707, 2016) showed that in efficient visual search with a fixed target, reaction times increase logarithmically as a function of set size and, further, that the slope of these logarithmic functions is modulated by target-distractor similarity. This has led to the proposal that the cognitive architecture of Stage 1 processing is parallel, of unlimited capacity, and exhaustive in nature. Such an architecture produces reaction time functions that increase logarithmically with set size (as opposed to being unaffected by it). However, in the previous studies, eye movements were not monitored. It is thus possible that the logarithmicity of the reaction time functions emerged simply as an artifact of eye movements rather than as a reflection of the underlying cognitive architecture. Here we ruled out the possibility that eye movements resulted in the observed logarithmic functions, by asking participants to keep their eyes at fixation while completing fixed-target efficient visual search tasks. The logarithmic RT functions still emerged even when participants were not allowed to make eye movements, thus providing further support for our proposal. Additionally, we found that search efficiency is slightly improved when eye movements are restricted and lure-target similarity is relatively high.

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Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 33%
Student > Doctoral Student 3 17%
Student > Ph. D. Student 2 11%
Professor 1 6%
Other 1 6%
Other 2 11%
Unknown 3 17%
Readers by discipline Count As %
Psychology 9 50%
Computer Science 1 6%
Linguistics 1 6%
Neuroscience 1 6%
Engineering 1 6%
Other 0 0%
Unknown 5 28%
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 18 July 2018.
All research outputs
#16,287,458
of 24,003,070 outputs
Outputs from Attention, Perception, & Psychophysics
#848
of 1,773 outputs
Outputs of similar age
#212,121
of 331,074 outputs
Outputs of similar age from Attention, Perception, & Psychophysics
#12
of 16 outputs
Altmetric has tracked 24,003,070 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,773 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
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We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.