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Deep dyslexia for kanji and phonological dyslexia for kana: Different manifestations from a common source

Overview of attention for article published in Neurocase, November 2008
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user
wikipedia
1 Wikipedia page

Readers on

mendeley
37 Mendeley
citeulike
3 CiteULike
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Article details
Title
Deep dyslexia for kanji and phonological dyslexia for kana: Different manifestations from a common source
Published in
Neurocase, November 2008
DOI 10.1080/13554790802372135
Pubmed ID
Authors
Abstract

A Japanese-speaking stroke patient with disrupted phonology but relatively good semantics was severely impaired in nonword reading, with better preserved and imageability-modulated word-reading in both kanji and kana. This basic similarity of reading in the two Japanese scripts was accompanied by the following differences: (i) distinct error patterns (prominent semantic errors for kanji vs. phonological errors for kana); (ii) a more pronounced imageability effect for kanji; and (iii) a remarkable pseudohomophone advantage for kana. The combination of deep dyslexia for kanji and phonological dyslexia for kana in a single patient suggests that these are not two distinct reading disorders.

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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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Philippines 1 3%
Unknown 36 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 8 22%
Student > Bachelor 7 19%
Student > Ph. D. Student 5 14%
Professor 3 8%
Student > Doctoral Student 2 5%
Other 6 16%
Unknown 6 16%
Readers by discipline
Readers by discipline Count As %
Psychology 7 19%
Medicine and Dentistry 7 19%
Agricultural and Biological Sciences 6 16%
Linguistics 4 11%
Nursing and Health Professions 2 5%
Other 3 8%
Unknown 8 22%
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 01 March 2018.
All research outputs
#6,950,322
of 22,790,780 outputs
Outputs from Neurocase
#210
of 529 outputs
Outputs of similar age
#44,908
of 165,361 outputs
Outputs of similar age from Neurocase
#3
of 5 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 529 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one has gotten more attention than average, scoring higher than 59% 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 165,361 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 71% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.