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Human Amygdala Tracks a Feature-Based Valence Signal Embedded within the Facial Expression of Surprise

Overview of attention for article published in Journal of Neuroscience, September 2017
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About this Attention Score

  • In the top 5% 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 (81st percentile)

Mentioned by

news
1 news outlet
twitter
28 tweeters

Citations

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5 Dimensions

Readers on

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36 Mendeley
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Title
Human Amygdala Tracks a Feature-Based Valence Signal Embedded within the Facial Expression of Surprise
Published in
Journal of Neuroscience, September 2017
DOI 10.1523/jneurosci.1375-17.2017
Pubmed ID
Authors

M. Justin Kim, Alison M. Mattek, Randi H. Bennett, Kimberly M. Solomon, Jin Shin, Paul J. Whalen

Abstract

Human amygdala function has been traditionally associated with processing the affective valence (positive versus negative) of an emotionally charged event, especially those that signal fear or threat. However, this account of human amygdala function can be explained by alternative views, which posit that the amygdala might be tuned to either (a) more general emotional arousal (more relevant versus less relevant) or (b) more specific emotion categories (fear versus happy). Delineating the pure effects of valence independent of arousal or emotion category is a challenging task, given that these variables naturally co-vary under many circumstances. To circumvent this issue and test the sensitivity of the human amygdala to valence values specifically, we measured the dimension of valence within the single facial expression category of surprise. Given the inherent valence ambiguity of this category, we show that surprised expression exemplars are attributed valence and arousal values that are uniquely and naturally uncorrelated. We then present functional magnetic resonance imaging data from both sexes showing that the amygdala tracks these consensus valence values. Finally, we provide evidence that these valence values are linked to specific visual features of the mouth region, isolating the signal by which the amygdala detects valence information.SIGNIFICANCE STATEMENTThere is an open question as to whether human amygdala function tracks the valence value of cues in the environment, as opposed to either a more general emotionalarousal value or a more specific emotion category distinction. Here, we demonstrate the utility of surprised facial expressions, since exemplars within this emotion category take on valence values spanning the dimension of bipolar valence (positive to negative) at a consistent level of emotional arousal. Functional neuroimaging data showed that amygdala responses tracked the valence of surprised facial expressions, unconfounded by arousal Furthermore, a machine learning classifier identified particular visual features of the mouth region that predicted this valence effect, isolating the specific visual signal that might be driving the neural valence response.

Twitter Demographics

The data shown below were collected from the profiles of 28 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 19%
Student > Master 7 19%
Researcher 5 14%
Unspecified 5 14%
Student > Doctoral Student 3 8%
Other 9 25%
Readers by discipline Count As %
Psychology 13 36%
Unspecified 9 25%
Neuroscience 7 19%
Social Sciences 2 6%
Medicine and Dentistry 2 6%
Other 3 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 04 April 2018.
All research outputs
#656,481
of 13,555,081 outputs
Outputs from Journal of Neuroscience
#1,531
of 18,691 outputs
Outputs of similar age
#23,592
of 269,034 outputs
Outputs of similar age from Journal of Neuroscience
#50
of 274 outputs
Altmetric has tracked 13,555,081 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 18,691 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one has done particularly well, scoring higher than 91% 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 269,034 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 274 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.