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Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling

Overview of attention for article published in Frontiers in Human Neuroscience, August 2020
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1 X user

Citations

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52 Mendeley
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Title
Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling
Published in
Frontiers in Human Neuroscience, August 2020
DOI 10.3389/fnhum.2020.00321
Pubmed ID
Authors

Minji Lee, Jae-Geun Yoon, Seong-Whan Lee

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 readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 17%
Student > Master 7 13%
Researcher 5 10%
Student > Bachelor 5 10%
Other 3 6%
Other 10 19%
Unknown 13 25%
Readers by discipline Count As %
Engineering 13 25%
Neuroscience 6 12%
Computer Science 5 10%
Medicine and Dentistry 3 6%
Sports and Recreations 2 4%
Other 6 12%
Unknown 17 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 19 August 2020.
All research outputs
#23,545,139
of 26,215,093 outputs
Outputs from Frontiers in Human Neuroscience
#7,044
of 7,808 outputs
Outputs of similar age
#371,842
of 429,743 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#131
of 148 outputs
Altmetric has tracked 26,215,093 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,808 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 429,743 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.