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Effective connectivity between amygdala and orbitofrontal cortex differentiates the perception of facial expressions

Overview of attention for article published in Social Neuroscience, November 2008
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Article details
Title
Effective connectivity between amygdala and orbitofrontal cortex differentiates the perception of facial expressions
Published in
Social Neuroscience, November 2008
DOI 10.1080/17470910802453105
Pubmed ID
Authors
Abstract

Emotion research is guided both by the view that emotions are points in a dimensional space, such as valence or approach-withdrawal, and by the view that emotions are discrete categories. We determined whether effective connectivity of amygdala with medial orbitofrontal cortex (MOFC) and lateral orbitofrontal cortex (LOFC) differentiates the perception of emotion faces in a manner consistent with the dimensional and/or categorical view. Greater effective connectivity from left MOFC to amygdala differentiated positive and neutral expressions from negatively valenced angry, disgust, and fear expressions. Greater effective connectivity from right LOFC to amygdala differentiated emotion expressions conducive to perceiver approach (happy, neutral, and fear) from angry expressions that elicit perceiver withdrawal. Finally, consistent with the categorical view, there were unique patterns of connectivity in response to fear, anger, and disgust, although not in response to happy expressions, which did not differ from neutral ones.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 2 3%
United States 1 2%
Germany 1 2%
Australia 1 2%
Austria 1 2%
Unknown 55 90%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 18 30%
Researcher 12 20%
Student > Master 6 10%
Professor > Associate Professor 4 7%
Student > Doctoral Student 2 3%
Other 7 11%
Unknown 12 20%
Readers by discipline
Readers by discipline Count As %
Psychology 15 25%
Medicine and Dentistry 8 13%
Neuroscience 8 13%
Agricultural and Biological Sciences 6 10%
Computer Science 2 3%
Other 6 10%
Unknown 16 26%
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 09 January 2018.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Social Neuroscience
#437
of 595 outputs
Outputs of similar age
#90,568
of 105,691 outputs
Outputs of similar age from Social Neuroscience
#2
of 3 outputs
Altmetric has tracked 25,373,627 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 595 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.6. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 105,691 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.