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Prioritized Detection of Personally Familiar Faces

Overview of attention for article published in PLOS ONE, June 2013
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Title
Prioritized Detection of Personally Familiar Faces
Published in
PLOS ONE, June 2013
DOI 10.1371/journal.pone.0066620
Pubmed ID
Authors

Maria Ida Gobbini, Jason D. Gors, Yaroslav O. Halchenko, Courtney Rogers, J. Swaroop Guntupalli, Howard Hughes, Carlo Cipolli

Abstract

We investigated whether personally familiar faces are preferentially processed in conditions of reduced attentional resources and in the absence of conscious awareness. In the first experiment, we used Rapid Serial Visual Presentation (RSVP) to test the susceptibility of familiar faces and faces of strangers to the attentional blink. In the second experiment, we used continuous flash interocular suppression to render stimuli invisible and measured face detection time for personally familiar faces as compared to faces of strangers. In both experiments we found an advantage for detection of personally familiar faces as compared to faces of strangers. Our data suggest that the identity of faces is processed with reduced attentional resources and even in the absence of awareness. Our results show that this facilitated processing of familiar faces cannot be attributed to detection of low-level visual features and that a learned unique configuration of facial features can influence preconscious perceptual processing.

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Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
France 1 <1%
Italy 1 <1%
United Kingdom 1 <1%
Singapore 1 <1%
China 1 <1%
Unknown 116 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 17%
Student > Master 19 16%
Researcher 17 14%
Student > Bachelor 13 11%
Professor 8 7%
Other 27 22%
Unknown 17 14%
Readers by discipline Count As %
Psychology 60 49%
Neuroscience 19 16%
Agricultural and Biological Sciences 4 3%
Biochemistry, Genetics and Molecular Biology 3 2%
Computer Science 3 2%
Other 9 7%
Unknown 24 20%