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Grapheme learning and grapheme-color synesthesia: toward a comprehensive model of grapheme-color association

Overview of attention for article published in Frontiers in Human Neuroscience, January 2013
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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 (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

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1 news outlet
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4 X users
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1 Facebook page

Readers on

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74 Mendeley
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Title
Grapheme learning and grapheme-color synesthesia: toward a comprehensive model of grapheme-color association
Published in
Frontiers in Human Neuroscience, January 2013
DOI 10.3389/fnhum.2013.00757
Pubmed ID
Authors

Michiko Asano, Kazuhiko Yokosawa

Abstract

Recent progress in grapheme-color synesthesia research has revealed that certain regularities, as well as individual differences, figure into grapheme-color associations. Although several factors are known to regulate grapheme-color associations, the impact of factors, including their interrelationships, on synesthesia remains unclear. We investigated determinants of synesthetic color for graphemes (characters, letters) of Hiragana, a phonetic script in the Japanese language, and the English alphabet. Results revealed that grapheme ordinality was the strongest predictor of synesthetic colors for Hiragana characters, followed by character sound, and visual shape. Ordinality and visual shapes also significantly predicted synesthetic colors for English alphabet letters, however, sounds did not. The relative impact of grapheme properties on grapheme-color associations and the differences between these two writing systems are accounted for by considering the way graphemes are processed in the brain and introduced during an individual's development. A new model is proposed which takes into account the developmental process of grapheme learning. The model provides comprehensive explanation of synesthetic grapheme-color association determination processes, including the differences across writing systems.

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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 4%
Japan 1 1%
Germany 1 1%
Unknown 69 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 24%
Student > Bachelor 13 18%
Researcher 8 11%
Student > Doctoral Student 4 5%
Professor 4 5%
Other 12 16%
Unknown 15 20%
Readers by discipline Count As %
Psychology 29 39%
Neuroscience 8 11%
Linguistics 6 8%
Engineering 4 5%
Computer Science 3 4%
Other 7 9%
Unknown 17 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 02 February 2015.
All research outputs
#2,624,754
of 22,729,647 outputs
Outputs from Frontiers in Human Neuroscience
#1,317
of 7,134 outputs
Outputs of similar age
#27,795
of 280,769 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#228
of 862 outputs
Altmetric has tracked 22,729,647 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,134 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has done well, scoring higher than 81% 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 280,769 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 90% of its contemporaries.
We're also able to compare this research output to 862 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 73% of its contemporaries.