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A Coordinate-Based Meta-Analysis of Overlaps in Regional Specialization and Functional Connectivity across Subjective Value and Default Mode Networks

Overview of attention for article published in Frontiers in Neuroscience, January 2017
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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 (95th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
4 X users
peer_reviews
1 peer review site
wikipedia
1 Wikipedia page

Citations

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65 Dimensions

Readers on

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101 Mendeley
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Title
A Coordinate-Based Meta-Analysis of Overlaps in Regional Specialization and Functional Connectivity across Subjective Value and Default Mode Networks
Published in
Frontiers in Neuroscience, January 2017
DOI 10.3389/fnins.2017.00001
Pubmed ID
Authors

M. Yavuz Acikalin, Krzysztof J. Gorgolewski, Russell A. Poldrack

Abstract

Previous research has provided qualitative evidence for overlap in a number of brain regions across the subjective value network (SVN) and the default mode network (DMN). In order to quantitatively assess this overlap, we conducted a series of coordinate-based meta-analyses (CBMA) of results from 466 functional magnetic resonance imaging experiments on task-negative or subjective value-related activations in the human brain. In these analyses, we first identified significant overlaps and dissociations across activation foci related to SVN and DMN. Second, we investigated whether these overlapping subregions also showed similar patterns of functional connectivity, suggesting a shared functional subnetwork. We find considerable overlap between SVN and DMN in subregions of central ventromedial prefrontal cortex (cVMPFC) and dorsal posterior cingulate cortex (dPCC). Further, our findings show that similar patterns of bidirectional functional connectivity between cVMPFC and dPCC are present in both networks. We discuss ways in which our understanding of how subjective value (SV) is computed and represented in the brain can be synthesized with what we know about the DMN, mind-wandering, and self-referential processing in light of our findings.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 101 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 29%
Researcher 18 18%
Student > Master 12 12%
Student > Bachelor 7 7%
Student > Doctoral Student 6 6%
Other 19 19%
Unknown 10 10%
Readers by discipline Count As %
Psychology 31 31%
Neuroscience 24 24%
Agricultural and Biological Sciences 5 5%
Medicine and Dentistry 3 3%
Physics and Astronomy 3 3%
Other 9 9%
Unknown 26 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 23 July 2022.
All research outputs
#1,866,231
of 25,550,333 outputs
Outputs from Frontiers in Neuroscience
#990
of 11,611 outputs
Outputs of similar age
#37,543
of 421,525 outputs
Outputs of similar age from Frontiers in Neuroscience
#9
of 173 outputs
Altmetric has tracked 25,550,333 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 11,611 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. 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 421,525 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 173 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 95% of its contemporaries.