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Neural Mechanisms of the Transformation from Objective Value to Subjective Utility: Converting from Count to Worth

Overview of attention for article published in Frontiers in Neuroscience, November 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

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Title
Neural Mechanisms of the Transformation from Objective Value to Subjective Utility: Converting from Count to Worth
Published in
Frontiers in Neuroscience, November 2016
DOI 10.3389/fnins.2016.00507
Pubmed ID
Authors

Yoanna A. Kurnianingsih, O'Dhaniel A. Mullette-Gillman

Abstract

When deciding, we aim to choose the "best" possible outcome. This is not just selection of the option that is the most numerous or physically largest, as options are translated from objective value (count) to subjective value (worth or utility). We localized the neural instantiation of the value-to-utility transformation to the dorsal anterior midcingulate cortex (daMCC), with independent replication. The daMCC encodes the context-specific information necessary to convert from count to worth. This encoding is not simply a representation of utility or preference, but the interaction of the two. Specifically, the relationship of brain activation to value is dependent on individual preference, with both positive and negative slopes across the population depending on whether each individual's preference results in enhancement or diminishment of the valuation. For a given value, across participants, enhanced daMCC activation corresponds to diminished subjective valuation, deactivation to enhanced subjective valuation, and non-modulated activation with non-modulated subjective valuation. Further, functional connectivity analyses identified brain regions (positive connectivity with the inferior frontal gyrus and negative connectivity with the nucleus accumbens) through which contextual information may be integrated into the daMCC and allow for outputs to modulate valuation signals. All analyses were replicated through an independent within-study replication, with initial testing in the gains domain and replication in the intermixed and mirrored losses trials. We also present and discuss an ancillary finding: we were unable to identify parametric value signals for losses through whole-brain analyses, and ROI analyses of the vmPFC presented non-modulation across loss value levels. These results identify the neural locus of the value-to-utility transformation, and provide a specific computational function for the daMCC in the production of subjective valuation through the integration of value, context, and preferences.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 14%
Student > Doctoral Student 2 10%
Student > Ph. D. Student 2 10%
Professor > Associate Professor 2 10%
Student > Master 2 10%
Other 3 14%
Unknown 7 33%
Readers by discipline Count As %
Psychology 7 33%
Nursing and Health Professions 1 5%
Agricultural and Biological Sciences 1 5%
Computer Science 1 5%
Medicine and Dentistry 1 5%
Other 2 10%
Unknown 8 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 November 2016.
All research outputs
#8,474,477
of 25,374,647 outputs
Outputs from Frontiers in Neuroscience
#5,364
of 11,542 outputs
Outputs of similar age
#118,349
of 319,129 outputs
Outputs of similar age from Frontiers in Neuroscience
#49
of 139 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 52% 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 319,129 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.