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Regional differences in trait-like characteristics of the waking EEG in early adolescence

Overview of attention for article published in BMC Neuroscience, October 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Citations

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27 Mendeley
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Title
Regional differences in trait-like characteristics of the waking EEG in early adolescence
Published in
BMC Neuroscience, October 2013
DOI 10.1186/1471-2202-14-117
Pubmed ID
Authors

Dominik C Benz, Leila Tarokh, Peter Achermann, Sarah P Loughran

Abstract

The human waking EEG spectrum shows high heritability and stability and, despite maturational cortical changes, high test-retest reliability in children and teens. These phenomena have also been shown to be region specific. We examined the stability of the morphology of the wake EEG spectrum in children aged 11 to 13 years recorded over weekly intervals and assessed whether the waking EEG spectrum in children may also be trait-like. Three minutes of eyes open and three minutes of eyes closed waking EEG was recorded in 22 healthy children once a week for three consecutive weeks. Eyes open and closed EEG power density spectra were calculated for two central (C3LM and C4LM) and two occipital (O1LM and O2LM) derivations. A hierarchical cluster analysis was performed to determine whether the morphology of the waking EEG spectrum between 1 and 20 Hz is trait-like. We also examined the stability of the alpha peak using an ANOVA.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 15%
Researcher 4 15%
Student > Doctoral Student 4 15%
Student > Bachelor 3 11%
Other 2 7%
Other 6 22%
Unknown 4 15%
Readers by discipline Count As %
Psychology 8 30%
Neuroscience 5 19%
Engineering 2 7%
Medicine and Dentistry 2 7%
Computer Science 1 4%
Other 5 19%
Unknown 4 15%
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 02 November 2013.
All research outputs
#7,376,686
of 22,725,280 outputs
Outputs from BMC Neuroscience
#367
of 1,241 outputs
Outputs of similar age
#69,533
of 209,651 outputs
Outputs of similar age from BMC Neuroscience
#13
of 51 outputs
Altmetric has tracked 22,725,280 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,241 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 70% 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 209,651 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 66% of its contemporaries.
We're also able to compare this research output to 51 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 74% of its contemporaries.