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Hearing the Sound in the Brain: Influences of Different EEG References

Overview of attention for article published in Frontiers in Neuroscience, March 2018
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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 (86th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Title
Hearing the Sound in the Brain: Influences of Different EEG References
Published in
Frontiers in Neuroscience, March 2018
DOI 10.3389/fnins.2018.00148
Pubmed ID
Authors

Dan Wu

Abstract

If the scalp potential signals, the electroencephalogram (EEG), are due to neural "singers" in the brain, how could we listen to them with less distortion? One crucial point is that the data recording on the scalp should be faithful and accurate, thus the choice of reference electrode is a vital factor determining the faithfulness of the data. In this study, music on the scalp derived from data in the brain using three different reference electrodes were compared, including approximate zero reference-reference electrode standardization technique (REST), average reference (AR), and linked mastoids reference (LM). The classic music pieces in waveform format were used as simulated sources inside a head model, and they were forward calculated to scalp as standard potential recordings, i.e., waveform format music from the brain with true zero reference. Then these scalp music was re-referenced into REST, AR, and LM based data, and compared with the original forward data (true zero reference). For real data, the EEG recorded in an orthodontic pain control experiment were utilized for music generation with the three references, and the scale free index (SFI) of these music pieces were compared. The results showed that in the simulation for only one source, different references do not change the music/waveform; for two sources or more, REST provide the most faithful music/waveform to the original ones inside the brain, and the distortions caused by AR and LM were spatial locations of both source and scalp electrode dependent. The brainwave music from the real EEG data showed that REST and AR make the differences of SFI between two states more recognized and found the frontal is the main region that producing the music. In conclusion, REST can reconstruct the true signals approximately, and it can be used to help to listen to the true voice of the neural singers in the brain.

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X Demographics

The data shown below were collected from the profiles of 23 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 21%
Student > Master 11 18%
Researcher 10 16%
Student > Bachelor 3 5%
Professor > Associate Professor 3 5%
Other 6 10%
Unknown 16 26%
Readers by discipline Count As %
Neuroscience 11 18%
Psychology 7 11%
Computer Science 6 10%
Engineering 5 8%
Medicine and Dentistry 4 6%
Other 13 21%
Unknown 16 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 24 November 2020.
All research outputs
#2,296,196
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#1,359
of 11,542 outputs
Outputs of similar age
#48,744
of 351,846 outputs
Outputs of similar age from Frontiers in Neuroscience
#50
of 256 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
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 has done well, scoring higher than 88% 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 351,846 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 86% of its contemporaries.
We're also able to compare this research output to 256 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.