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Encoding differences affect the number and precision of own-race versus other-race faces stored in visual working memory

Overview of attention for article published in Attention, Perception, & Psychophysics, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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Title
Encoding differences affect the number and precision of own-race versus other-race faces stored in visual working memory
Published in
Attention, Perception, & Psychophysics, January 2018
DOI 10.3758/s13414-017-1467-6
Pubmed ID
Authors

Xiaomei Zhou, Catherine J. Mondloch, Stephen M. Emrich

Abstract

Other-race faces are discriminated and recognized less accurately than own-race faces. Despite a wealth of research characterizing this other-race effect (ORE), little is known about the nature of the representations of own-race versus other-race faces. This is because traditional measures of this ORE provide a binary measure of discrimination or recognition (correct/incorrect), failing to capture potential variation in the quality of face representations. We applied a novel continuous-response paradigm to independently measure the number of own-race and other-race face representations stored in visual working memory (VWM) and the precision with which they are stored. Participants reported target own-race or other-race faces on a circular face space that smoothly varied along the dimension of identity. Using probabilistic mixture modeling, we found that following ample encoding time, the ORE is attributable to differences in the probability of a face being maintained in VWM. Reducing encoding time, a manipulation that is more sensitive to encoding limitations, caused a loss of precision or an increase in variability of VWM for other-race but not own-race faces. These results suggest that the ORE is driven by the inefficiency with which other-race faces are rapidly encoded in VWM and provide novel insights about how perceptual experience influences the representation of own-race and other-race faces in VWM.

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 15%
Student > Ph. D. Student 7 13%
Student > Doctoral Student 6 11%
Researcher 5 9%
Professor > Associate Professor 5 9%
Other 11 20%
Unknown 13 24%
Readers by discipline Count As %
Psychology 30 55%
Neuroscience 4 7%
Nursing and Health Professions 2 4%
Computer Science 1 2%
Economics, Econometrics and Finance 1 2%
Other 4 7%
Unknown 13 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 January 2019.
All research outputs
#5,178,072
of 25,328,635 outputs
Outputs from Attention, Perception, & Psychophysics
#189
of 1,807 outputs
Outputs of similar age
#105,628
of 455,200 outputs
Outputs of similar age from Attention, Perception, & Psychophysics
#3
of 15 outputs
Altmetric has tracked 25,328,635 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,807 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 89% of its peers.
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 455,200 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.