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Monitoring Different Phonological Parameters of Sign Language Engages the Same Cortical Language Network but Distinctive Perceptual Ones

Overview of attention for article published in Journal of Cognitive Neuroscience, January 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Title
Monitoring Different Phonological Parameters of Sign Language Engages the Same Cortical Language Network but Distinctive Perceptual Ones
Published in
Journal of Cognitive Neuroscience, January 2016
DOI 10.1162/jocn_a_00872
Pubmed ID
Authors

Velia Cardin, Eleni Orfanidou, Lena Kästner, Jerker Rönnberg, Bencie Woll, Cheryl M Capek, Mary Rudner

Abstract

The study of signed languages allows the dissociation of sensorimotor and cognitive neural components of the language signal. Here we investigated the neurocognitive processes underlying the monitoring of two phonological parameters of sign languages: handshape and location. Our goal was to determine if brain regions processing sensorimotor characteristics of different phonological parameters of sign languages were also involved in phonological processing, with their activity being modulated by the linguistic content of manual actions. We conducted an fMRI experiment using manual actions varying in phonological structure and semantics: (1) signs of a familiar sign language (British Sign Language), (2) signs of an unfamiliar sign language (Swedish Sign Language), and (3) invented nonsigns that violate the phonological rules of British Sign Language and Swedish Sign Language or consist of nonoccurring combinations of phonological parameters. Three groups of participants were tested: deaf native signers, deaf nonsigners, and hearing nonsigners. Results show that the linguistic processing of different phonological parameters of sign language is independent of the sensorimotor characteristics of the language signal. Handshape and location were processed by different perceptual and task-related brain networks but recruited the same language areas. The semantic content of the stimuli did not influence this process, but phonological structure did, with nonsigns being associated with longer RTs and stronger activations in an action observation network in all participants and in the supramarginal gyrus exclusively in deaf signers. These results suggest higher processing demands for stimuli that contravene the phonological rules of a signed language, independently of previous knowledge of signed languages. We suggest that the phonological characteristics of a language may arise as a consequence of more efficient neural processing for its perception and production.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 2%
Unknown 61 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 24%
Researcher 9 15%
Professor 6 10%
Student > Bachelor 5 8%
Student > Doctoral Student 5 8%
Other 14 23%
Unknown 8 13%
Readers by discipline Count As %
Neuroscience 16 26%
Psychology 14 23%
Linguistics 8 13%
Social Sciences 2 3%
Nursing and Health Professions 2 3%
Other 7 11%
Unknown 13 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 03 May 2016.
All research outputs
#2,823,625
of 23,577,654 outputs
Outputs from Journal of Cognitive Neuroscience
#427
of 2,222 outputs
Outputs of similar age
#49,140
of 397,072 outputs
Outputs of similar age from Journal of Cognitive Neuroscience
#8
of 33 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,222 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one has done well, scoring higher than 80% 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 397,072 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.