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The EEG Split Alpha Peak: Phenomenological Origins and Methodological Aspects of Detection and Evaluation

Overview of attention for article published in Frontiers in Neuroscience, September 2017
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Title
The EEG Split Alpha Peak: Phenomenological Origins and Methodological Aspects of Detection and Evaluation
Published in
Frontiers in Neuroscience, September 2017
DOI 10.3389/fnins.2017.00506
Pubmed ID
Authors

Elzbieta Olejarczyk, Piotr Bogucki, Aleksander Sobieszek

Abstract

Electroencephalographic (EEG) patterns were analyzed in a group of ambulatory patients who ranged in age and sex using spectral analysis as well as Directed Transfer Function, a method used to evaluate functional brain connectivity. We tested the impact of window size and choice of reference electrode on the identification of two or more peaks with close frequencies in the spectral power distribution, so called "split alpha." Together with the connectivity analysis, examination of spatiotemporal maps showing the distribution of amplitudes of EEG patterns allowed for better explanation of the mechanisms underlying the generation of split alpha peaks. It was demonstrated that the split alpha spectrum can be generated by two or more independent and interconnected alpha wave generators located in different regions of the cerebral cortex, but not necessarily in the occipital cortex. We also demonstrated the importance of appropriate reference electrode choice during signal recording. In addition, results obtained using the original data were compared with results obtained using re-referenced data, using average reference electrode and reference electrode standardization techniques.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 28%
Researcher 10 16%
Student > Master 9 15%
Student > Doctoral Student 4 7%
Professor 2 3%
Other 6 10%
Unknown 13 21%
Readers by discipline Count As %
Neuroscience 17 28%
Engineering 7 11%
Medicine and Dentistry 6 10%
Psychology 5 8%
Computer Science 2 3%
Other 7 11%
Unknown 17 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 September 2017.
All research outputs
#15,745,807
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#6,691
of 11,542 outputs
Outputs of similar age
#177,749
of 323,484 outputs
Outputs of similar age from Frontiers in Neuroscience
#109
of 158 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 39th percentile – i.e., 39% 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 323,484 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.