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Attention Score in Context
| Title |
Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice
|
|---|---|
| Published in |
Frontiers in Neuroscience, May 2017
|
| DOI | 10.3389/fnins.2017.00262 |
| Pubmed ID | |
| Authors |
Federico Chella, Antea D'Andrea, Alessio Basti, Vittorio Pizzella, Laura Marzetti |
| Abstract |
Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz), the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST). The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i) the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii) the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of considering the effects of the reference choice in the interpretation and comparison of the results of bispectral analysis of scalp EEG. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 17% |
| China | 1 | 17% |
| Switzerland | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 28% |
| Researcher | 8 | 20% |
| Professor | 4 | 10% |
| Student > Master | 4 | 10% |
| Student > Doctoral Student | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 9 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 14 | 35% |
| Engineering | 6 | 15% |
| Medicine and Dentistry | 3 | 8% |
| Computer Science | 2 | 5% |
| Psychology | 2 | 5% |
| Other | 3 | 8% |
| Unknown | 10 | 25% |
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 12 April 2018.
All research outputs
#8,264,793
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#5,239
of 11,542 outputs
Outputs of similar age
#122,057
of 325,242 outputs
Outputs of similar age from Frontiers in Neuroscience
#87
of 204 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
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 gotten more attention than average, scoring higher than 53% 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 325,242 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 61% of its contemporaries.
We're also able to compare this research output to 204 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 56% of its contemporaries.