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Mendeley readers
Attention Score in Context
| Title |
Mobile Device Applications for the Visualization of Functional Connectivity Networks and EEG Electrodes: iBraiN and iBraiNEEG
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, October 2016
|
| DOI | 10.3389/fninf.2016.00040 |
| Pubmed ID | |
| Authors |
Gonzalo M. Rojas, Jorge A. Fuentes, Marcelo Gálvez |
| Abstract |
Multiple functional MRI (fMRI)-based functional connectivity networks were obtained by Yeo et al. (2011), and the visualization of these complex networks is a difficult task. Also, the combination of functional connectivity networks determined by fMRI with electroencephalography (EEG) data could be a very useful tool. Mobile devices are becoming increasingly common among users, and for this reason, we describe here two applications for Android and iOS mobile devices: one that shows in an interactive way the seven Yeo functional connectivity networks, and another application that shows the relative position of 10-20 EEG electrodes with Yeo's seven functional connectivity networks. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 33% |
| Chile | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 4% |
| Unknown | 27 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 18% |
| Student > Master | 4 | 14% |
| Student > Bachelor | 3 | 11% |
| Student > Doctoral Student | 2 | 7% |
| Student > Ph. D. Student | 2 | 7% |
| Other | 3 | 11% |
| Unknown | 9 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 3 | 11% |
| Psychology | 3 | 11% |
| Computer Science | 2 | 7% |
| Social Sciences | 2 | 7% |
| Neuroscience | 2 | 7% |
| Other | 5 | 18% |
| Unknown | 11 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 30 November 2016.
All research outputs
#13,407,768
of 22,893,031 outputs
Outputs from Frontiers in Neuroinformatics
#431
of 751 outputs
Outputs of similar age
#164,600
of 315,872 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#6
of 13 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 751 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one is in the 41st percentile – i.e., 41% 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 315,872 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.