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Is it the real deal? Perception of virtual characters versus humans: an affective cognitive neuroscience perspective

Overview of attention for article published in Frontiers in Psychology, May 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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1 news outlet
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13 X users

Citations

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108 Dimensions

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255 Mendeley
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Title
Is it the real deal? Perception of virtual characters versus humans: an affective cognitive neuroscience perspective
Published in
Frontiers in Psychology, May 2015
DOI 10.3389/fpsyg.2015.00576
Pubmed ID
Authors

Aline W. de Borst, Beatrice de Gelder

Abstract

Recent developments in neuroimaging research support the increased use of naturalistic stimulus material such as film, avatars, or androids. These stimuli allow for a better understanding of how the brain processes information in complex situations while maintaining experimental control. While avatars and androids are well suited to study human cognition, they should not be equated to human stimuli. For example, the uncanny valley hypothesis theorizes that artificial agents with high human-likeness may evoke feelings of eeriness in the human observer. Here we review if, when, and how the perception of human-like avatars and androids differs from the perception of humans and consider how this influences their utilization as stimulus material in social and affective neuroimaging studies. First, we discuss how the appearance of virtual characters affects perception. When stimuli are morphed across categories from non-human to human, the most ambiguous stimuli, rather than the most human-like stimuli, show prolonged classification times and increased eeriness. Human-like to human stimuli show a positive linear relationship with familiarity. Secondly, we show that expressions of emotions in human-like avatars can be perceived similarly to human emotions, with corresponding behavioral, physiological and neuronal activations, with exception of physical dissimilarities. Subsequently, we consider if and when one perceives differences in action representation by artificial agents versus humans. Motor resonance and predictive coding models may account for empirical findings, such as an interference effect on action for observed human-like, natural moving characters. However, the expansion of these models to explain more complex behavior, such as empathy, still needs to be investigated in more detail. Finally, we broaden our outlook to social interaction, where virtual reality stimuli can be utilized to imitate complex social situations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 255 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Netherlands 1 <1%
Portugal 1 <1%
Spain 1 <1%
Italy 1 <1%
Unknown 249 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 18%
Student > Master 44 17%
Researcher 29 11%
Student > Bachelor 27 11%
Student > Doctoral Student 15 6%
Other 33 13%
Unknown 60 24%
Readers by discipline Count As %
Psychology 60 24%
Computer Science 31 12%
Neuroscience 20 8%
Engineering 14 5%
Medicine and Dentistry 8 3%
Other 46 18%
Unknown 76 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 16 August 2023.
All research outputs
#1,794,262
of 25,359,594 outputs
Outputs from Frontiers in Psychology
#3,667
of 34,248 outputs
Outputs of similar age
#22,118
of 271,075 outputs
Outputs of similar age from Frontiers in Psychology
#64
of 497 outputs
Altmetric has tracked 25,359,594 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 34,248 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. 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 271,075 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 497 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.