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The role of prediction in social neuroscience

Overview of attention for article published in Frontiers in Human Neuroscience, January 2012
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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 (97th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
38 X users
facebook
4 Facebook pages
googleplus
5 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
150 Dimensions

Readers on

mendeley
607 Mendeley
citeulike
3 CiteULike
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Title
The role of prediction in social neuroscience
Published in
Frontiers in Human Neuroscience, January 2012
DOI 10.3389/fnhum.2012.00147
Pubmed ID
Authors

Elliot C. Brown, Martin Brüne

Abstract

Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e., by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one's own and observing other's actions, rewards, errors, and emotions such as fear and pain. These general principles of the "predictive brain" are well established and have already begun to be applied to social aspects of cognition. The application and relevance of these predictive principles to social cognition are discussed in this article. Evidence is presented to argue that simple non-social cognitive processes can be extended to explain complex cognitive processes required for social interaction, with common neural activity seen for both social and non-social cognitions. A number of studies are included which demonstrate that bottom-up sensory input and top-down expectancies can be modulated by social information. The concept of competing social forward models and a partially distinct category of social prediction errors are introduced. The evolutionary implications of a "social predictive brain" are also mentioned, along with the implications on psychopathology. The review presents a number of testable hypotheses and novel comparisons that aim to stimulate further discussion and integration between currently disparate fields of research, with regard to computational models, behavioral and neurophysiological data. This promotes a relatively new platform for inquiry in social neuroscience with implications in social learning, theory of mind, empathy, the evolution of the social brain, and potential strategies for treating social cognitive deficits.

X Demographics

X Demographics

The data shown below were collected from the profiles of 38 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 607 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 15 2%
United Kingdom 12 2%
Germany 7 1%
Italy 5 <1%
Canada 5 <1%
Netherlands 4 <1%
Spain 4 <1%
France 2 <1%
Switzerland 2 <1%
Other 17 3%
Unknown 534 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 158 26%
Researcher 101 17%
Student > Master 63 10%
Student > Bachelor 48 8%
Student > Doctoral Student 42 7%
Other 122 20%
Unknown 73 12%
Readers by discipline Count As %
Psychology 265 44%
Neuroscience 64 11%
Agricultural and Biological Sciences 47 8%
Medicine and Dentistry 28 5%
Computer Science 27 4%
Other 77 13%
Unknown 99 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 48. 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 17 December 2018.
All research outputs
#871,622
of 25,394,764 outputs
Outputs from Frontiers in Human Neuroscience
#386
of 7,688 outputs
Outputs of similar age
#4,970
of 250,240 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#21
of 293 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,688 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has done particularly well, scoring higher than 94% 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 250,240 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 97% of its contemporaries.
We're also able to compare this research output to 293 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.