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Attention Score in Context
| Title |
How to Build a Hybrid Neurofeedback Platform Combining EEG and fMRI
|
|---|---|
| Published in |
Frontiers in Neuroscience, March 2017
|
| DOI | 10.3389/fnins.2017.00140 |
| Pubmed ID | |
| Authors |
Marsel Mano, Anatole Lécuyer, Elise Bannier, Lorraine Perronnet, Saman Noorzadeh, Christian Barillot |
| Abstract |
Multimodal neurofeedback estimates brain activity using information acquired with more than one neurosignal measurement technology. In this paper we describe how to set up and use a hybrid platform based on simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), then we illustrate how to use it for conducting bimodal neurofeedback experiments. The paper is intended for those willing to build a multimodal neurofeedback system, to guide them through the different steps of the design, setup, and experimental applications, and help them choose a suitable hardware and software configuration. Furthermore, it reports practical information from bimodal neurofeedback experiments conducted in our lab. The platform presented here has a modular parallel processing architecture that promotes real-time signal processing performance and simple future addition and/or replacement of processing modules. Various unimodal and bimodal neurofeedback experiments conducted in our lab showed high performance and accuracy. Currently, the platform is able to provide neurofeedback based on electroencephalography and functional magnetic resonance imaging, but the architecture and the working principles described here are valid for any other combination of two or more real-time brain activity measurement technologies. |
X Demographics
The data shown below were collected from the profiles of 15 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 | 2 | 13% |
| United Kingdom | 2 | 13% |
| Italy | 1 | 7% |
| France | 1 | 7% |
| Switzerland | 1 | 7% |
| India | 1 | 7% |
| Unknown | 7 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 73% |
| Scientists | 3 | 20% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| China | 1 | 1% |
| Unknown | 83 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 22% |
| Researcher | 14 | 16% |
| Student > Master | 12 | 14% |
| Student > Doctoral Student | 7 | 8% |
| Student > Bachelor | 5 | 6% |
| Other | 11 | 13% |
| Unknown | 17 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 14 | 16% |
| Psychology | 13 | 15% |
| Engineering | 11 | 13% |
| Computer Science | 7 | 8% |
| Medicine and Dentistry | 5 | 6% |
| Other | 11 | 13% |
| Unknown | 24 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 13 December 2022.
All research outputs
#4,083,063
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#3,382
of 11,542 outputs
Outputs of similar age
#67,684
of 322,965 outputs
Outputs of similar age from Frontiers in Neuroscience
#54
of 206 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% 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 gotten more attention than average, scoring higher than 70% 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 322,965 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 79% of its contemporaries.
We're also able to compare this research output to 206 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 73% of its contemporaries.